Tech Mahindra has announced a collaboration with Microsoft to enhance workplace experiences for its 1,200+ customers and over 10,000 employees across 15 locations through the adoption of Copilot for Microsoft 365. This partnership positions Tech Mahindra as a prominent Global Systems Integrator (GSI) in the realm of Copilot for Microsoft 365.

The collaboration aims to boost workforce efficiency and streamline processes using Microsoft’s trusted cloud platform and generative AI capabilities. Additionally, Tech Mahindra will deploy GitHub Copilot for 5,000 developers, anticipating a productivity increase of 35% to 40%.

Tech Mahindra is committed to empowering employees with AI tools to drive innovation, value, and sustainable growth. The organisation plans to extend the capabilities of Copilot with plugins to leverage multiple data sources and enhance creativity and productivity. The focus is on increasing efficiency, reducing effort, and improving quality and compliance across the board.

Mohit Joshi, CEO and Managing Director of Tech Mahindra, emphasised the transformative potential of this partnership, stating, “Our vision is to redefine the workplace experience by empowering every employee to excel and innovate using cutting-edge AI technology. We are not just adopting a tool; we are shaping the future of work for our employees and customers. The collaboration with Microsoft, and the introduction of Copilot for Microsoft 365 and GitHub Copilot also marks a significant stride in Tech Mahindra commitment to making AI accessible to everyone.”

As part of this initiative, Tech Mahindra has launched a dedicated Copilot practice to help customers unlock the full potential of AI tools. This includes workforce training for assessment and preparation, critical for integrating AI across all functions of an organisation. 

Tech Mahindra will offer comprehensive solutions to help customers assess, prepare, pilot, and adopt business solutions using Copilot for Microsoft 365, providing a scalable and personalised user experience.

Judson Althoff, Executive Vice President and Chief Commercial Officer at Microsoft, remarked, “Our collaboration with Tech Mahindra will empower its employees with new generative AI capabilities to enhance workplace experiences and increase developer productivity through the adoption of Copilot for Microsoft 365 and GitHub Copilot. With a focus on driving AI innovation and skilling, Tech Mahindra is poised to deliver new solutions and greater value for its customers across industries.”

This collaboration aligns with Tech Mahindra’s ongoing efforts to enhance workforce productivity using GenAI tools. Recently, Tech Mahindra launched a unified workbench on Microsoft Fabric, designed to help organisations accelerate the adoption of Microsoft Fabric and create complex data workflows with ease.

The longstanding partnership between Microsoft and Tech Mahindra has also led to the development of industry-leading solutions such as:

• Generative AI-powered Enterprise Knowledge Search: Integrates Microsoft Azure OpenAI Service, Azure Cognitive Search, and Azure Language understanding to enhance organisational knowledge.
• Green CodeRefiner: Transforms existing code into energy-efficient code, optimising emissions.
• SenTindra: A cloud-based virtual security operations centre developed on Microsoft Sentinel.
• COMPASS-Cloud Security Assessment and Global System Integrator solutions: Focused on fortifying security frameworks and data governance capabilities.

The post Tech Mahindra Partners with Microsoft to Transform Workplace Experiences Using Generative AI appeared first on AIM.

In a keynote speech at the MachineCon GCC Summit 2024, CP Gurnani, co-founder of AIonOS and former CEO of Tech Mahindra, challenged the notion that India could not develop its own LLMs and highlighted India’s rapid advancements in AI.

“Sam Altman challenged everybody that India will never be able to have an LLM,” Gurnani said, referring to OpenAI’s CEO. “I spoke to my chief innovation officer that time at Tech Mahindra… Six hours later, he says I have a plan,” he added.

Gurnani revealed that Tech Mahindra was able to develop an Indian LLM for local languages and 37+ dialects in just 5 months, spending less than $5 million. “When ET covered the 7 best AI companies, which will have an Indian LLM, they covered Tata, NVIDIA, and Tech Mahindra,” he said.

He further added, “Tata, NVIDIA, now you can assume what the budget would look like. And Tech Mahindra, I am happy to share that they spent less than 5 million dollars on what Sam Altman said, India will never be able to deliver.”

Grand Vision for India’s AI & Tech Landscape

The tech veteran argued that AI is now mainstream and part of our daily lives, but questioned whether enterprises have fully adopted the technology. However, he cited statistics suggesting AI could improve productivity by up to 40% in areas like customer experience, quality assurance, and sales.

Further, Gurnani confidently stated that the country looks confident to make strides in the tech and AI landscape and truly be Atmanirbhar. “I’m very convinced that in India, as the semiconductor industry develops, 5-7 years later, we would not be looking at someone else.”

As a comparative measure, Gurnani gave an Indian example and emphasised the importance of “frugal plus innovation plus technology plus people leadership” as the secret to success for Indian companies like IndiGo and Airtel in their competition with behemoths like Jio.

He also added that his own new venture, AIonOS, aims to transform industries like travel, logistics, hospitality and transportation using AI.

How is Project Indus Going to Fair?

Incidentally, Tech Mahindra launched its Project Indus today. This indigenous large language model (LLM) is designed to engage in conversations across a wide array of Indic languages and dialects, marking a significant step towards linguistic inclusivity in the realm of artificial intelligence.

In the initial phase, Project Indus will concentrate on developing an LLM specifically tailored for the Hindi language and its extensive range of over 37 dialects.

By focusing on this widely spoken language, Tech Mahindra aims to bridge the linguistic gap and empower a substantial portion of the population to interact with cutting-edge AI technology in their native tongue.

To bring Project Indus to life, Tech Mahindra has forged strategic collaborations with industry leaders Dell Technologies and Intel.

The model will be implemented using ‘GenAI in a Box’ solution, which harnesses the power of Dell Technologies’ state-of-the-art computing, storage, and networking capabilities.

Additionally, the solution incorporates Intel-based infrastructure, including Intel® Xeon® Processors and the OneAPI software suite, ensuring optimal performance and scalability.

Nikhil Malhotra, Global Head of Makers Lab at Tech Mahindra, expressed his enthusiasm for the project, stating, “Project Indus is our seminal effort to develop an LLM from the ground up. Through Makers Lab, our R&D arm, we created a roadmap, collected data from the Hindi-speaking population, and built the Indus model. Our collaboration with Dell Technologies & Intel will help deliver cutting-edge AI solutions that enable enterprises to scale at speed.”

The collaboration between Tech Mahindra, Dell Technologies, and Intel aims to revolutionise AI-driven solutions across various industries. By leveraging Tech Mahindra’s expertise in developing localized and verticalized industry-agnostic LLMs, the partnership will enable the creation of tailored use cases and applications in sectors such as healthcare, rural education, banking, agriculture, and telecom.

Denise Millard, Chief Partner Officer at Dell Technologies, emphasized the significance of accessibility and scalability in the adoption of GenAI.

“With the Dell AI Factory, LLMs like Project Indus leverage AI-optimized technologies with an open ecosystem of partners, validated and integrated solutions, services and best practices, accelerating the adoption of AI to drive growth, optimize productivity and promote innovation,” she remarked.

Santhosh Viswanathan, Vice President & Managing Director for India at Intel, highlighted the company’s dedication to advancing the frontiers of AI. “We are proud to collaborate with Tech Mahindra on Project Indus, which will enable seamless deployment of advanced AI models across industries and empower enterprises to unlock GenAI’s full potential for enhanced operational efficiency and a competitive edge,” he stated.

Project Indus represents a pivotal milestone in the evolution of the global GenAI landscape, which is projected to expand to a staggering $1.3 trillion over the next decade. The model will initially prioritise key use cases and pilot projects, offering scalable AI solutions to enterprises.

Conclusively, as India strives for sovereignty and leadership in the AI landscape with AI initiatives, time will tell how Gurnani’s daring challenge and the product that came out of it will fare.

The post CP Gurnani Proves Altman Wrong, Tech Mahindra Builds Indian LLM Under $5M appeared first on AIM.

Tech Mahindra today announced the much-awaited launch of its Project Indus.

This indigenous large language model (LLM) is designed to engage in conversations across a wide array of Indic languages and dialects, marking a significant step towards linguistic inclusivity in the realm of artificial intelligence.

In the initial phase, Project Indus will concentrate on developing an LLM specifically tailored for the Hindi language and its extensive range of over 37 dialects.

By focusing on this widely spoken language, Tech Mahindra aims to bridge the linguistic gap and empower a substantial portion of the population to interact with cutting-edge AI technology in their native tongue.

To bring Project Indus to life, Tech Mahindra has forged strategic collaborations with industry leaders Dell Technologies and Intel.

The model will be implemented using ‘GenAI in a Box’ solution, which harnesses the power of Dell Technologies’ state-of-the-art computing, storage, and networking capabilities.

Additionally, the solution incorporates Intel-based infrastructure, including Intel® Xeon® Processors and the OneAPI software suite, ensuring optimal performance and scalability.

Nikhil Malhotra, Global Head of Makers Lab at Tech Mahindra, expressed his enthusiasm for the project, stating, “Project Indus is our seminal effort to develop an LLM from the ground up. Through Makers Lab, our R&D arm, we created a roadmap, collected data from the Hindi-speaking population, and built the Indus model. Our collaboration with Dell Technologies & Intel will help deliver cutting-edge AI solutions that enable enterprises to scale at speed.”

The collaboration between Tech Mahindra, Dell Technologies, and Intel aims to revolutionise AI-driven solutions across various industries. By leveraging Tech Mahindra’s expertise in developing localized and verticalized industry-agnostic LLMs, the partnership will enable the creation of tailored use cases and applications in sectors such as healthcare, rural education, banking, agriculture, and telecom.

This initiative has the potential to drive innovation, optimise productivity, and promote growth in these critical domains.

Denise Millard, Chief Partner Officer at Dell Technologies, emphasized the significance of accessibility and scalability in the adoption of GenAI.

“With the Dell AI Factory, LLMs like Project Indus leverage AI-optimized technologies with an open ecosystem of partners, validated and integrated solutions, services and best practices, accelerating the adoption of AI to drive growth, optimize productivity and promote innovation,” she remarked.

Santhosh Viswanathan, Vice President & Managing Director for India at Intel, highlighted the company’s dedication to advancing the frontiers of AI. “We are proud to collaborate with Tech Mahindra on Project Indus, which will enable seamless deployment of advanced AI models across industries and empower enterprises to unlock GenAI’s full potential for enhanced operational efficiency and a competitive edge,” he stated.

Project Indus represents a pivotal milestone in the evolution of the global GenAI landscape, which is projected to expand to a staggering $1.3 trillion over the next decade. The model will initially prioritise key use cases and pilot projects, offering scalable AI solutions to enterprises.

This collaboration underscores Tech Mahindra’s unwavering commitment to enabling enterprises to scale rapidly with technological advancements, fostering a future where AI solutions are accessible, scalable, and responsible.

Tech Mahindra’s recent announcement of developing an LLM to preserve Bahasa Indonesia and its dialects further highlights the company’s dedication to linguistic diversity and inclusivity in the AI domain.

With Project Indus, Tech Mahindra is poised to reshape the AI landscape, empowering businesses and individuals alike to harness the potential of advanced language models in their native languages.

The post Tech Mahindra Finally Launches Project Indus, Indic LLM with 37+ Hindi Dialects appeared first on AIM.

Tech Mahindra has teamed up with Indosat Ooredoo Hutchison to build ‘Garuda,’ a Large Language Model (LLM) to preserve Bahasa Indonesia, the official and national language of Indonesia and its dialects.

Garuda will be built on the principles of Tech Mahindra’s indigenous LLM ‘Project Indus‘, a foundational model designed to converse in a multitude of Indic languages and dialects.

The IT giant signed a Memorandum of Understanding (MoU) at Mobile World Congress (MWC) 2024.

As part of this partnership, Tech Mahindra will leverage its technology expertise to gather and curate data in the Indonesian language, which will be pre-trained and released as a conversational model for Indosat.

Garuda will be developed with 16 billion original Bahasa tokens, providing 1.2 billion parameters to shape the model’s understanding of the Bahasa language. These parameters will influence how the model processes input and formulates output.

A beta version of the Garuda model will be released for testing by Indosat and Bahasa Indonesia speakers. The model will be further improved using RLHF (Reinforcement Learning from Human Feedback) techniques to ensure its robustness for conversation. Additionally, any specialized use cases will be developed using the LIMA (Less is More for Alignment) method.

“The LLM market is expected to reach 40.8 billion USD by 2029. In this direction, the emergence of LLMs such as Garuda and Indus can enable people and enterprises to communicate online in their local dialects and languages, creating new opportunities in the digital world.

“We believe that the model will significantly promote Indonesia’s linguistic diversity and unlock new business opportunities for enterprises in the region,” said Harshvendra Soin, President – Asia Pacific and Japan Business, Tech Mahindra.

The post Tech Mahindra to Build LLM for Indonesia on Project Indus Principles appeared first on AIM.

The assertion that “AI models are only as good as the data they’re trained on” has been reiterated by experts countless times, and the statement affirms the undeniable truth. 

ChatGPT, the popular chatbot by OpenAI, is so impressive because it has been trained on a dataset called WebText2, which is a library of over 45 terabytes of text data which includes articles, blogs, forums, and other publicly available written content.

However, for India to flourish in India, it needs to create AI models that understand India’s linguistic nuances and cultural complexities. 

So far, we have already seen a host of Indic large language models (LLMs) come up within a short period of time from Tech Mahindra and Sarvam AI on an enterprise level. 

Besides, various Indic adaptations of Meta’s widely used open-source LLM, LLama, have been created for languages like Tamil, Kannada, Telugu, and more. However, the critical challenge lies in the necessity for robust data on the diverse set of languages spoken across the country, a resource currently lacking in building effective Indic LLMs.

The necessity to develop good Indic datasets 

India boasts linguistic diversity, encompassing hundreds of languages and thousands of dialects. Generating datasets for such a vast array of languages is a challenging endeavour. Presently, even though datasets are available for the 22 official languages, hundreds of other languages are actively spoken in the country. 

“Large language models require very large amounts of high-quality data. For many Indian languages, we do not have this right now,” Pratyush Kumar, co-founder at Sarvam AI and AI4Bharat, an open-source AI research initiative focused on Indian language AI, told AIM. 

However, several initiatives are in progress to collect datasets for Indic languages. One such effort is Project Vaani, a collaboration between the Indian Institute of Sciences (IISc) and Google, which focuses on gathering speech datasets to facilitate the training of Indic LLMs.

Additionally, AI4Bharat is also building Indic language datasets like ‘IndicCorp v2, which is the most extensive collection of texts for Indic languages, comprising 20.9 billion tokens, out of which 14.4 billion tokens cover 23 Indic languages. And then there is Bhashini, which is an Indian government’s initiative to create an open-source Indic language dataset.

However, even though these are good datasets, there is a need for more data. “The current volume of this type of data is relatively small; we need to collect even more,” Vivek Raghavan, co-founder of Sarvam AI, told AIM.

Collecting data is not easy 

Building datasets remains the most challenging task for those wanting to build Indic LLMs. It will involve digitisation of books, collaborating with linguists, engaging communities, organising content creation workshops, and partnering with local institutions. Surveys, interviews, and transcription services will also play a crucial role.

Tech Mahindra, which recently completed developing its Hindi LLM consisting of 539 million parameters and 10 billion Hindi+ dialect tokens, sent its crew to Northern India to collect data.

“We went to Madhya Pradesh, Rajasthan, and parts of Bihar. The team’s task was to collect Hindi and dialect data by interacting with professors and leveraging the Bhasha-dan portal available on ProjectIndus.in,” Nikhil Malhotra, global head at Makers Lab, Tech Mahindra and the brain behind Project Indus, told AIM.

He also highlighted the initiative to involve Tech Mahindra employees in contributing everyday interactions through sentences like ‘Main ghar se bahar jata hoon’ to the portal to gather diverse linguistic prompts.

Similarly, Swecha Telangana, an open-source advocacy group, recently collaborated with  25-30 colleges and over 10,000 students, who were involved in translation, correction and digitalisation of 40,000-45,000 pages of Telugu folk tales. The dataset was then used to train a 7 billion parameter Telugu small language model (SLM) called ‘AI Chandamama Kathalu’.

Bhashini, too, is making similar efforts to build Indic language datasets. “We lack digital data on low-resource languages, such as Bodo or Sindhi. For these languages, we approach individuals proficient in both Bodo and English,” Amitabh Nag, CEO at Bhashini, told AIM. He explained that they help create a training dataset by providing parallel text in English corresponding to the content written in Bodo.

These efforts stand as a testament to the arduous task ahead for those involved in building good Indic LLMs. Nonetheless, Krutrim, which is an AI startup by Ola founder Bhavesh Aggarwal, claims to have built a model from scratch which understands the 22 official languages of India. 

Similarly, earlier this month, Qx Lab AI launched Ask Qx, which also understands 22 official languages. However, neither company has revealed the details of the datasets their models have been trained on. 

It’s worth highlighting that ChatGPT, leveraging the capabilities of both GPT-3.5 and GPT-4, exhibits multilingual proficiency, including an understanding of Indic languages like Hindi, Bengali, and Assamese. 

However, the chatbot occasionally encounters challenges in distinguishing between Bengali and Assamese. This issue arises due to the quality of datasets on which the models have been trained, particularly for these specific languages.

An ecosystem needs to develop

Kumar believes building good datasets for the 22 official languages will take a reasonable while and, “We should as an ecosystem continue to focus on that because we want to support these languages,” he said.

What India truly requires is a unified and collaborative endeavour, where individuals, organisations, and enterprises join forces, extending support whenever necessary. The encouraging aspect is that a significant portion of the ongoing initiatives is adopting an open-source approach. 

This not only promotes transparency and accessibility but also facilitates a collective and inclusive effort towards the common goal of advancing linguistic technologies in the country. 

“I believe you will observe a notable shift, particularly in languages spoken more frequently, gaining momentum sooner. However, with time, I am confident that we have the capability to encompass all languages, including their various dialects and nuances,” Raghavan said.

The post India Needs Quality Data for Indic LLMs appeared first on AIM.

For Indian IT, the year 2023 unfolded as a narrative of paradoxes and challenges. While luminaries like TCS, Infosys, HCLTech, Wipro, and Tech Mahindra celebrated record-high deal wins, the overarching ambiguity surrounding revenue growth cast a shadow over the sector’s trajectory for the entire year. 

Industry pundits, reflecting on the incidents of 2023, echoed sentiments of a sector grappling with its weakest performance since the recession of 2008. In the midst of this uncertainty, the beacon of hope for the Indian IT sector emanates from the realm of generative AI. 

Can 2024 be the year of AI deals?

Pareekh Jain, CEO of EIIRTrend, predicts that around 2% of the revenue in the coming year would be through generative AI directly. He also highlighted how AI was one of the positive things in 2023 for Indian IT, and this would influence a lot of partnerships and deals in 2024.

On the contrary, the $1.5 billion Infosys AI deal that got cancelled would also play a major impact in the industry. “A lot of companies would realise that moving too fast and investing in technologies would not be ideal. Thus, they would move with a lot of caution,” said Jain. But he believes that deals would definitely be a big focus this year.

As industry analysts predict a transformation from Q3 onwards, a nuanced narrative of deal divergence and recalibration unfolds. Large deals are anticipated to derive impetus from vendor consolidation, steering away from conventional digital transformation paradigms. 

As generative AI emerges as a focal point of interest, its potential impact on revenue is forecasted to crystallise in the third quarter of 2024. Jain said that though in 2023 AI was not the focus of deal in Indian IT, it was one of the biggest factors of the deals. “Generative AI could also be a deal breaker in 2024,” said Jain, highlighting that it would be the focus. 

That said, direct generative AI focused deals would definitely be the focus. “More than 50% of the deals would be directly influenced by generative AI,” said Jain.

For example, HCLTech announced a slew of new deals, where it will be involved in digital and cloud transformation, alongside generative AI initiatives. TCS also predicts that Indian IT firms would be a major focus globally and expects a lot of new deals in the year, along with 12 million more net jobs by 2025. 

LTIMindtree has expressed its commitment to integrating generative AI into its products and solutions, revealing that they have participated in more than 100 discussions and currently have over 20 active engagements with clients.

Wipro has doubled the number of customers as compared to the last quarter, and would focus on large deals in 2024. HCLTech is working with a handful of customers with generative AI projects, while LTIMindtree is engaged in over 20 clients for generative AI.  

Infosys, along with a few other parties including Elon Musk, AWS and others donated USD 1 billion to OpenAI. TCS and Wipro also announced generative AI capabilities in partnership with Google Cloud.

A lot in the pipeline

Companies have actively discussed various ongoing experiments and proof of concepts (PoCs) in their pipelines. In the previous month, Accenture disclosed an industry-leading generative AI pipeline valued at $450 million in new bookings, a significant increase from the $300 million reported for the entire fiscal year of FY23. 

This along with a $3billion investment in AI for three years. The company anticipates a shift from general AI experimentation to more proof of concepts and pilot projects in 2024.

Similarly, TCS reported having over 250 generative AI opportunities in its pipeline, Infosys is engaged in over 50 active generative AI projects, and HCLTech is involved in more than 140 generative AI PoCs at various stages. 

However, the caveat is that these PoCs are still in the pre-production stage and are far from generating immediate revenue. Analysts believe that only 10% of the PoCs will move to production. Considering this, a rapid recovery in the IT services sector in 2024 seems unlikely. 

Analysts from Kotak note that despite high expectations for a recovery in discretionary spending in 2024, enterprises across most sectors are still focused on cost reduction. Many have set cost-saving targets extending into 2024, and the reprioritisation of spending toward areas of investment is not yet complete.

2023 continued?

During the earnings call, CP Gurnani, former managing director of Tech Mahindra said, “Tech Mahindra is now working in about 60 customer locations on actually using generative AI to enhance operations, innovation, and productivity.” 

On the other hand, Indian IT firms have also largely stopped hiring freshers. This trend might continue this year, along with rampant possible layoffs.

In the initial half of fiscal year 2024, the top-tier IT firms collectively shed 39,000 employees, signalling a strategic recalibration in response to evolving market dynamics. Delays in lateral hires and adjustments in compensation strategies underscored a pragmatic approach to talent acquisition.

Overall, the Indian IT majors have trained close to seven lakh employees in generative AI, in partnership with companies like Google, Microsoft, Oracle and NVIDIA. The monetary impact of the same would be on the forefront of discussions in 2024.

The post What to Expect from Indian IT in 2024 appeared first on AIM.

Tech Mahindra’s outgoing chief, CP Gurnani, shared a Project Indus update on X, highlighting the development of an LLM specifically designed for Hindi and its 37 dialects.

Retiring after 19 years at Tech Mahindra he said, “I feel proud to share that the GenerativeAI project challenge I took up earlier has been successfully accomplished by our brilliant research team at Makers Lab.” Project Indus is in the beta testing phase within TechM. The pure Hindi LLM consists of 539 million parameters and 10 billion Hindi+ dialect tokens, as shared by Gurnani. 

“The model is probably the only one in the world that has all Hindi tokens and has been trained from the ground up. It will set the stage for the years to come as our prowess in deep tech,” he said.

“I now pass the baton over to Mohit Joshi, Nikhil Malhotra, and the team, as well as my talented Tech Mighties, who will take this one notch higher. Thank you for everything, team!” he added.

In October, Tech Mahindra announced its plan to release Project Indus by the end of December or early January. Introduced in August, the model is initially set to support 40 different Hindi dialects, with plans to add more languages and dialects in subsequent releases. Over the last two months, the 15-member Project Indus team has collected 1.2 terabytes of data in Hindi and related dialects.

The update by Gurnani comes in the backdrop of last week, which witnessed a slew of announcements from Indian companies and startups launching their large language models (LLMs). This includes Google-backed CoRover’s BharatGPT, Khosla Ventures-backed Sarvam.ai’sOpenHathi, Microsoft-backed Kissan AI’s Dhenu, and Ola’s Krutrim.

The post Tech Mahindra Completes Project Indus, to Launch Soon  appeared first on AIM.

Number 19 is special for CP Gurnani, who recently celebrated a dual milestone — his 65th birthday (on December 19) and a fond farewell to his illustrious career, after a fulfilling 19 years at Tech Mahindra. 

“I relived 19 years in just a few hours yesterday. And now, I relive those hours in just a few minutes,” said Gurnani, adding that there are no words to describe how overwhelming this is – “just like there are no words to describe how grateful I am”. 

The past few days have taken Gurnani on an emotional roller coaster ride as he bids farewell to his illustrious career. He shared an emotional post on X, revealing that the Tech Mahindra team had 19 gifts for him — one for each of his years at the company. 

The most special one, #TechMKiMitti, was an hourglass with sand collected from their campuses all over, to always let him have a bit of TechM with him. “This almost had me teary-eyed,” he wrote. 

Last month, CP Gurnani announced that he would step down from the position of MD and CEO of Tech Mahindra on December 19 as well as from the roles of non-executive, non-independent director of the IT major on December 21. Following him, Mohit Joshi who resigned from Infosys on March 11, 2023, will join Tech Mahindra as the next CEO and managing director. 

What’s Next? 

While Gurnani has not publicly revealed his future plans, insiders at Tech Mahindra indicate that he is poised to relinquish all responsibilities within the company, directing his attention towards personal life and endeavours. 

However, Gurnani expresses his readiness for a transition, shifting from the role of a captain to that of a ‘coach’. “I don’t think I am even close to retiring. I will be shifting gears and transitioning into a new phase as a coach,” he said in a recent interview.

Dedicating a significant portion of his life to the tech industry, having attaining the position of CXO at 38, Gurnani now looks to explore a slightly different path. “I want to pursue endeavours that deeply resonate with my passions and values. I see it as a good time to embark on this personal journey of self-discovery after a long, fulfilling career,” he shared. 

Techno Optimist 

Gurnani has always been optimistic about the future, holding the opposite view to the prevailing opinion that AI may take away jobs. According to him, generative AI has the potential to create more jobs than it is expected to eliminate, despite widespread discussions on its potential to disrupt the job market on social media.

“The use cases of generative AI are still being defined, which means that it has the potential to create more job opportunities in the future. Undoubtedly, the possibilities are just opening up, and there is more to come,” said Gurnani. 

Not to forget, Gurnani was among the first ones to accept OpenAI’s ‘challenge’ promising to create something akin to ChatGPT. In June, Gurnani and Sam Altman, the CEO of OpenAI, engaged in Twitter exchanges, during which Gurnani asserted that India would create its own generative AI chatbot. 

Subsequently, Tech Mahindra revealed Project Indus a few weeks later, with the objective of constructing a foundational language model with a specific focus on Indian languages, notably Hindi and various dialects. Gurnani was the one who led this project, along with Rajesh Dhuddhu and Nikhil Malhotra.

With Gurnani retiring and new management taking over, it will be interesting to see how Project Indus shapes up. 

Believes in Hard Work 

Recently, Infosys founder Narayan Murthy’s remarks about youngsters working 70 hours a week was heavily debated, and Gurnani defended it. He said that young people should invest the 10,000 hours if that’s what it takes to become a master in their field. He added that this could involve burning the midnight oil to become an expert. 

He mentioned that when Murthy spoke about 70 hours, it didn’t necessarily mean for the company. Instead, he suggested that youngsters should allocate 40 hours for the company and reserve 30 hours for their personal development.

Gurnani’s Journey 

CP Gurnani graduated with a bachelor of engineering degree in chemical engineering from NIT- Rourkela. Subsequently, he commenced his early career as a process engineer at JK Synthetics, dedicating three years to the role. 

Following this initial stint, he transitioned to the technology firm HCL, where he held various significant positions, including roles at HCL Hewlett-Packard, HCL Perot System, and Perot Systems, accumulating a substantial 18 years of service from 1986 to 2004. 

By this point, Gurnani had already made a name for himself within the tech industry. In 2004, he made the pivotal move to Tech Mahindra, initially assuming the responsibility for the company’s international operations, sales, and marketing.

At Tech Mahindra, his most significant business accomplishment involved the acquisition of Satyam Computers, a feat spotlighted in a Harvard case study. Satyam Computers, was reeling from a major scandal with an uncertain future.

However, Gurnani saw Satyam’s crisis as an opportunity. He believed Satyam’s strong talent pool, global presence, and established clientele could be revitalized if paired with Mahindra’s financial stability and business expertise.

As his journey at Tech Mahindra comes to an end, Gurnani is overwhelmed with the love he received from his employees. “With so much love flowing in from all corners, I feel like a 5-year-old grandkid, not a 65-year-old grandfather,” he said. 

The post 19 Years of CP Gurnani  appeared first on AIM.

Being one of the most watched sporting events in the world, the National Football League’s (NFL) championship game is broadcast in over 130 countries in more than 30 languages. The final game, Super Bowl, is the most watched broadcast every year in the US, with over 115 million viewers tuned in to this year’s edition in February. While the game has been dominating the country, it is being backed by not just the greatest brands in the world pouring in millions of dollars, but also supported by the biggest tech companies in the world. 

Amazon Brings AI to NFL

In Amazon’s Q3 earnings, of the many high points in the results, NFL has been a key player. The subscription revenue has increased by 14% to $10.2 billion and is driven by the NFL. The company is in the second season of a 11-year exclusive deal of $11 billion to distribute Thursday Night Football (TNF are NFL games scheduled to be played on Thursday evenings during the NFL season) through Prime Video. 

Amazon has brought AI to TNF, making it an interactive experience for their viewers. Features such as ‘X-Ray’, gives fans real-time access to live statistics and data, ‘Rapid Recap’ generates 13 two-minute-long highlights to help viewers catch up on games, and many other features. 

‘Prime Vision with Next Gen Stats’ powered by AWS, provides insights by capturing real-time data on player’s location, speed, and acceleration using sensors hidden within their shoulder pads. Amazon collects over 300 million data points per season to train their machine learning models for gaining insights from every game. The insights on pass and position are shown real-time, giving viewers the ability to observe and predict the game strategy, akin to a quarterback (key player). 

As per Amazon’s Q3 results, the TNF season opener attracted 15.1 million viewers, and was the Prime Video’s most watched TNF game ever. The first six games brought an average of 12.9 million viewers, which was an increase of 25% from the previous season. Interestingly, Amazon has committed to paying $1 billion annually for the exclusive streaming rights to NFL games. 

Tussle for Broadcast Rights 

Last year, the National Football League revealed a multi-year deal with Google, giving Youtube TV and Youtube Primetime Channels exclusive rights to distribute NFL Sunday Ticket, that allows viewers to watch Sunday afternoon NFL games that are not typically available on local channels. 

The deal is said to be around $2 billion annually for seven years. DirecTV was previously paying $1.5 billion a year for the rights. However, as per a new report, Youtube is said to lose over $8.86 billion from now to 2029 with yearly declines of about $1.27 billion. 

Interestingly, Apple was one of the forerunners to bag the deal, however, the agreement did not fall through, as Apple wanted to reportedly pay less for the deal, so as to offer the product at lower prices. Though this deal failed, Apple was not completely left out. The NFL announced Apple Music as the new sponsor of the Super Bowl halftime show from 2023. Taking over Pepsi, who were the sponsors for 10 years, Apple will pay $50 million annually over a five- year span. 

Big ‘Technology’ Partners

In 2021, Cisco, an enterprise networking and security company, signed a multi-year deal to become the official technology partner for NFL. The partnership aims to create a unified platform and establish a robust technological foundation for NFL’s operations and communications with improved speed, intelligence and security measures. 

Every NFL stadium’s replay control room is built on Cisco technology, and almost all of the league’s official partners and two-thirds of NFL stadiums, including SoFi Stadium in LA and State Farm Stadium in Arizona, that hosted Super Bowls, is powered by Cisco technology.  

In Tech Mahindra’s recent Q2 earnings call, CP Gurnani, CEO and MD of the company announced that they are working with NFL. In 2018, the company signed a multi-year deal to be the technology, analytics and strategy partner for Jacksonville Jaguars (NFL team).  

The Best ‘Playground’

The first Super Bowl that was held in 1967 had close to 50 million viewers, and was the only year to have two networks broadcast it (CBS and NBC). The viewership has more than doubled with the latest edition (57th) in February, reaching 115.1 million viewers, making it the most watched Super Bowl of all time, and becoming the most popular TV program of all time. 

Tech firms understand that the NFL guarantees a large audience, and there’s no better platform than the game’s coverage. By partnering with such a major sporting event, companies leverage their technology and brand power : a probable win for them. 

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Amid a not-so-good quarter, owing to increasing expenses and reduced client spending in a challenging macroeconomic environment when the companies’ profits dropped by 62% from Q2 of previous year, Tech Mahindra seems rather cheerful.

The company, in its latest earnings call, emphasised on the need for innovation and diversification, and shifted its focus towards sports, chess and cricket. 

Cricket Connection 

In collaboration with BCCI, Tech Mahindra set up an innovation lab to enhance fan experience at the Ahmedabad stadium. The innovation centre was launched during the IPL finals, this year. 

The Joint Innovation Center is set up at the Narendra Modi Stadium, and Gurnani confirmed that a similar innovation lab will come up at two more stadiums — Dharamshala and Wankhede, Mumbai. 

Interestingly, the Narendra Modi Stadium in Ahmedabad, which is the largest cricket stadium in the world, where the IPL finals for 2022 and 2023 were held, witnessed over 1 lakh spectators. This is also where the World Cup Finals for this year will be held, thereby, proving to be the right place for Tech Mahindra’s fan centre. 

The company’s foray into cricket vertical is not a new development. In 2020, during the pandemic, Tech Mahindra, partnered with IPL team Kings XI Punjab to enhance the fan experience and reach a wide audience. It launched an engagement app on Android and iOS for fans to connect with the team, and were also working on introducing holographic virtual fans in the stadium.

Furthermore, the company also collaborated with another IPL team in 2021. Team Rajasthan Royals partnered with the company to enhance fan loyalty and monetisation. The collab looked to triple the value of the team’s fan base by using Tech Mahindra’s digital platform, and also find ways to create revenue streams for the team. Digital campaigns via social media, email and other avenues were part of the plan. 

Sporting Revolution 

Moving beyond cricket, Tech Mahindra’s sports vertical has invested and partnered with diverse sports companies and universities too. In the earnings call, Gurnani confirmed that they are working with NFL (National Football League) and ‘Mahindra Racing’ that competes in electric FIA Formula E Championship (a motor racing team competing with an Indian racing licence), and have branded the platform as Fan NXT.NOW. 

In 2021, Tech Mahindra partnered with Loughborough University in England, whose expertise lies in exceptional athletes, world-class facilities, top-tier coaching, research capabilities, and active collaborations with sports entities. The partnership focussed to combine both their prowess by jointly advancing sports innovation and exploring options around 5G, AR, VR and further research on shaping the future of sports consumption.

A few years ago, Tech Mahindra partnered with Fanisko, a fan-engagement platform that enhances mobile fan retention and digital engagement. The collaboration was aimed to leverage cutting-edge technologies to improve fan engagement and introduce innovative monetisation models for sports organisations globally. 

Tech Mahindra is also synonymous with chess. The company is preparing to grow the league by introducing four additional teams in response to interest from both international and Indian businesses looking to invest in the franchise-based competition – Global Chess League. In June 2022, Tech Mahindra was the first corporate organisation to back the FIDE Chess Olympiad. 

Towards Diversification and Innovation

“We, as a company, will continue to invest in innovation; we’ll continue to invest in new verticals; and we’ll continue to diversify,” said the CEO and MD of Tech Mahindra, CP Gurnani, during the company’s earnings call. 

Tech Mahindra’s focus on generative AI has been rampant this year, with the company seeing it as means for talent utilisation and innovative work. The company announced its plans to train 8,000 employees to cater to the demand of generative AI and quantum computing.

This year, the company announced a number of initiatives such as Generative AI Studio, to drive customer excellence, and have even announced the Indus Project, which is working towards building an Indic language model, an effort towards making an indigenous language model for Indian context. 

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In a recent earnings call, Tech Mahindra announced its plans to achieve big milestones in generative AI. During the call, CP Gurnani, managing director, Tech Mahindra said, “Tech Mahindra is now working in about 60 customer locations on actually using generative AI to enhance operations, innovation, and productivity.” 

In contrast, TCS  is engaged in hundreds of GenAI projects for its clients across segments. Meanwhile, Infosys is working on 90 generative AI programs, Wipro has doubled the number of customers as compared to the last quarter. HCLTech is working with a handful of customers with generative AI projects, while LTIMindtree is engaged in over 20 clients for generative AI.  

Tech Mahindra currently sees generative AI as a means to automate routine tasks and freeing up talent for more innovative work among other initiatives. In August, the company had announced that it plans to train about 8,000 employees as it readies itself to cater to demand around generative AI and quantum computing. 

Source: Belamy (AI Weekly Newsletter) 

Slew of GenAI Solutions 

In April, Tech Mahindra became the first IT giant to launch something like a Generative AI Studio. ​​The IT solution provider introduced TechM amplifAI0->∞, a comprehensive suite of Artificial Intelligence (AI) offerings and solutions aimed at democratizing and responsibly scaling AI deployment. Over time, the company has continuously integrated new tools into this suite.

In August, Tech Mahindra partnered with Google AI to develop generative AI-powered Email AmplifAIer, a solution that uses generative AI to automate email responses and to personalise email communications. 

Last month, the company introduced another solution called ‘Ops amplifAIer’ solution. It aims to enhance the productivity of support engineers by offering a unified integrated view with all the contextual information and tools needed to resolve issues. It also facilitates team collaboration and generative AI assistance capabilities, ensuring that processes are future-proofed in a responsible manner.

Tech Mahindra’s Ops amplifAIer solution integrates with existing ITOps tools to collect the contextual information related to an IT ticket/alert and uses generative AI to analyze the collected data. It further identifies the probable root cause, diagnoses, recommends remediation actions, and generates the corresponding automation scripts. The solution comes with an enterprise automation catalogue that enables the reuse of automation artefacts like scripts or workflows across the enterprise.

Early this month, Tech Mahindra released ‘Vision amplifAIer’ solution. This solution is designed to enhance computer vision-related use cases for enterprises, offering comprehensive end-to-end lifecycle management for computer vision (CV) projects. The emphasis is placed on streamlining the entire process, making it more accessible and efficient.

Apart from the enterprise solutions, Tech Mahindra is working on an indigenous LLM called Project Indus that would have the ability to speak in many Indic languages, most notably Hindi. The model will have the ability to speak in 40 different Indic languages, to begin with. 

Tech Mahindra is not alone 

During a recent earnings call, TCS’ executive vice president and global head of human resources Milind Lakkad highlighted their workforce’s readiness for generative AI, boasting over 100,000 GenAI-ready employees. TCS CEO K Krithivasan emphasised their success with TCS Cognix, utilising generative AI for operating model transformation deals, enabling businesses through dashboards and predictive analytics.

Infosys, under CEO Salil Parekh, discussed their generative AI capability, Topaz, which significantly increased their market share. Parekh revealed Infosys’ engagement in over 90 generative AI programs, emphasising their commitment to helping clients navigate the future with deep technical expertise. To support this, Infosys trained 57,000 employees in generative AI principles.

“We have trained as many as 180,000 employees in basic GenAI principles,” said Wipro chief Thierry Delaporte. He said that the company has rolled out personal-based learning pathways to create a pool of specialised talent with deeper technical expertise. It has ambitions to train over 250,000 employees in the coming months. Recently, it also launched a new GenAI Center of Excellence, in collaboration with IIT Delhi. 

Delaporte said it is rapidly integrating generative AI into its processes, solutions and offerings. “Thousands of our employees have or are starting to use generative AI. Today, we are seeing a doubling of GenAI active projects than we did just one quarter ago,” added Delaporte, pointing out how healthcare, consumer and financial services, high tech and utilities are seeing rapid adoption. 

HCLTech also announced a slew of new deals, where it will be involved in digital and cloud transformation, alongside generative AI initiatives. 

HCLTech chief C Vijayakumar said that the company is working on a two-pronged approach – for its clients, it looks to generate early-stage opportunities, alongside training its delivery organisation to leverage generative AI for core development, deployment, and testing and managed services. So far, it looks to train close to 18,000 employees. 

LTIMindtree has expressed its commitment to integrating generative AI into its products and solutions, revealing that they have participated in more than 100 discussions and currently have over 20 active engagements with clients, according to LTIMindtree chief, Debashis Chatterjee.

Additionally, the company is set to launch two new offerings: Canvas Lite, designed for developers focusing on productivity use cases, and Canvas Control Claim, which facilitates secure, moderated, and responsible AI use. This offering provides clients with the option to choose from commercial open-source and custom element models. Chatterjee also shared the company’s plan to train over 10,000 employees by the end of the third quarter.

In conclusion, Tech Mahindra is a unique player in Indian IT, which is making strides in generative AI, while others – TCS, Infosys, Wipro, HCLTech, and LTIMindtree – are focusing on enterprise solutions, upskilling and reskilling, alongside experimenting with real use cases.

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Mahindra Lifespace Developers Limited (MLDL), a subsidiary of the Mahindra Group specialising in real estate and infrastructure development, has introduced India’s inaugural Metaverse home-buying experience. This novel offering, known as Bastion at Mahindra Citadel, marks the launch of Phase 2 of the project.

What Does Metaverse Bring?

The announcement was made through a drone display held at the project site in Pimpri-Chinchwad. Over 500 drones illuminated the night sky, showcasing key features of the project, including the ecotone design and home automation capabilities. Prospective buyers can explore their potential future homes prior to making a commitment. Users also have the ability to engage with various elements within these virtual homes and customise the interiors according to their preferences.

Amit Kumar Sinha, MD & CEO of Mahindra Lifespace Developers Ltd, expressed enthusiasm for the launch and its relevance to Pune, which is a significant market for Mahindra Lifespaces. He emphasised Pune’s dynamic real estate environment and its propensity for innovation, underscoring the immersive and interactive nature of the Metaverse experience

Future-Forward

The initiative is a first-of-its-kind where a home-buying experience is brought to a Metaverse, in India. However, it’s not the first time for the Mahindra group to enable business via Metaverse. In 2022, the company announced that it is working on 60 metaverse projects, spanning over projects in ed-tech, retail, automotive dealer management, and others. 

Last year, Mahindra also launched a metaverse platform called XUV400Verse for buyers to experience a virtual showroom for their upcoming car XUV400. 

In yesterday’s Q2 earnings call, C.P Gurnani, CEO of Tech Mahindra had also emphasised on how the company will continue to innovate and diversify into different vertices.

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JanAI is a play on the word janta, which means people. The vision of creating AI for the people is something Jaspreet Bindra has been advocating for the country. Bindra, the founder of Tech Whisperer Limited in the UK, a consulting and advisory firm specialising in digital technologies such as AI and Web3, has an extensive background in the digital transformation space. 

He believes that the concept where “JanAI is treated as a digital public good” can help facilitate the growth of startups and organisations that can be created as part of the digital public infrastructure.

Bindra has served as the group chief digital officer of Mahindra Group and as a regional director at Microsoft, among other positions. His vision is to create an India-centric LLM (Bharat LLM), which aims to establish it as a second layer of the India stack, delivering it as a digital public good to 1.4 billion Indians, ‘much like UPI and Aadhaar’.

“If we have to create a million creators, a creator economy, this is a creative tool,” exclaimed Bindra. 

Making AI in India, For India 

Bindra has highlighted the need to have our own LLM as a necessity stemming from the need of bringing an Indian context into the training model. “If you look at ChatGPT or Bard, they are all trained on the internet, where almost 80 to 90% of the data is English, and West-oriented. It doesn’t have vernacular data nor an Indian context,” said Bindra.

“For example, land is measured differently in every Indian state. You have bigha in one place and kanal in another, and these are words that a foreign LLM will not make sense of, especially when you want to deliver to rural India.” 

Bindra even spoke about how UAE has Falcon and Jais, which are contextual to their own culture. He even spoke about the availability of large datasets within our country citing an example of how using ‘All India Radio insertion recordings’ will be amazing.  

Apart from the data being widely different, the concept of privacy and guardrails in India are also different, which is why Bindra believes a model for the country that caters to the privacy rules here will make more sense. 

Indian LLM in WIP 

There is already significant progress in the lines of large language models that cater to the Indian market. Tech Mahindra is working on Project Indus, a model that will have the ability to speak in 40 Indic languages with more languages that will be subsequently added.

Similarly, Bhashini, a government initiative, also looks to leverage AI to break language barriers, and help the underserved communities. “Bharat LLM and multiple elements will be created and that’s great. The JanAI bit is about how to take those LLMs and put them as part of the India stack,” said Bindra.  

Interestingly, co-founder of Infosys, Nandan Nilekani, the architect of Aadhaar, who was also instrumental in bringing major banks in India to collaborate on UPI, is also actively involved in building LLMs for Indic languages through AI4Bharat.

Nilekani has contributed INR 36 crore for launching Nilekani Centre at AI4Bharat in partnership with IIT Madras, and a total of INR 400 crore to IIT Bombay.

Forward-Looking But Not Obstacle-Free

Bindra believes that the adoption of such a platform in India may not be a challenge. Speaking about how Aadhaar and UPI have been massively adopted by people — touching over 1 billion now — Bindra is confident that as a country we know how to reach that level of adoption. 

“The way we have done it as a country is when we’ve taken these critical technologies and products and served them as a digital public good. DPG is what the government gives to its citizens,” said Bindra.   

In order for such an idea to come to fruition, Bindra believes there are four essential components — talent, data, money and the delivery model/governance. “Reliance and Tata have all signed with NVIDIA and we’ll get the infrastructure in place, but governance mechanism is the most important, which is missing,” said Bindra.

Bindra however, believes that the biggest challenge is to get the right sponsorship for the idea that people think is worth having. “It needs to be adopted, sponsored and owned by the government as there’s no other way.”

Collaboration 

Bindra spoke about how countries such as the US and China have their own models and have lots of money, making them the leaders, and a country such as the UK is focusing on the ethics and governance part of it. “What we can do uniquely is to ride on the whole thing like we did with UPI, Aadhaar, etc. and deliver generative AI to 1.4 billion people. That can become the model for the world,” said Bindra. 

With India ready to get 25,000 GPUs, Bindra believes that such kind of strategic partnerships will help divide the tasks and the costs will come down. “The ROI is nation building,” – referring to the jobs and creator economy that can be built with the JanAI-type of model. 

Speaking about whether the model has to be completely India-made, Bindra’s vision is not restricted. “When it comes to technology, we can’t really claim that everything will certainly be built by an Indian company. One of the people evangelising this along with me is Thoughtworks in Bangalore, which is not an Indian company.”

He also said that the company was also responsible for building large parts of ONDC and the India stack for UPI.

AI’s NOT a Hype

Bindra believes that every technology brings some element of hype which he deems is necessary as it brings in innovation and investment. However, he said that there needs to be a “hype-to-reality ratio”. 

“If you take the Metaverse, the hype-to-reality ratio is bad. If you go into Metaverse, either Meta’s Metaverse or Roblox’s Metaverse, you will find 37 people or 74 in the game, but if you look at the sheer amount of news it created versus the people using it, the ratio is extremely large. However, with generative AI, we know there are over 100 million people using it. It’s been 11 months and sure, there is a hype but there also is reality there,” concluded Bindra. 

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A few weeks ago, Tech Mahindra announced the launch of Project Indus – an Indic-based foundational model for Indian languages, which could potentially prove to be its most important project ever. Large language models (LLMs) like the GPT models by OpenAI, despite their multilingual capabilities, have been predominantly trained on English datasets, which limits their proficiency in comprehending and generating content in Indic languages. Hence, an open-source Indic LLM will be hugely beneficial for India. 

According to Tech Mahindra’s chief CP Gurnani, the model will be the biggest Indic LLM and could possibly cater to 25% of the world’s population. While Tech Mahindra has not revealed the cost associated with the project or when the model is expected to be launched, the aim is to build a 7-billion parameter LLM to begin with, Nikhil Malhotra, global head-Makers Lab, Tech Mahindra, told AIM.

The model is expected to initially support 40 different Hindi dialects and more languages and dialects will be added subsequently. “We understand that much work has been done on the Indic suite like Bhashini and AI4 Bharat, etc., but a foundation model still needs to be developed. As we continue to develop the model, we are constantly learning and improving the process. Our interface could have voice and textual information; however, we haven’t considered incorporating a chat interface like ChatGPT yet,” Malhotra said.

The primary goal for Tech Mahindra is to first create an LLM for continuation of text and then provide a dialogue. “Once we are clear that the model performs well and generates dialects well, we would launch it in the open source.” 

Benefits of building India’s biggest Indic LLM

ChatGPT, driven by OpenAI’s GPT models, has undoubtedly been groundbreaking. Hence, developing an LLM, primarily designed for Indic languages could be highly beneficial for India for a wide array of reasons. Understanding the nuances of local cultures and contexts is essential for effective communication. An Indic LLM can be designed to prioritise cultural sensitivity, ensuring that the generated content respects local customs and norms. An Indic LLM could also democratise AI and cater to the wider section of non-English speakers in the country. 

“One of the benefits of a foundation model is its versatility. For instance, a language model is capable of performing multiple tasks such as Q&A, fill-in-the-blanks, etc. using the same model. This approach is beneficial for specialised healthcare, retail, and tourism industries,” Malhotra said.

Moreover, the cost of tokens is significantly higher for the Indic languages in the GPT models when compared to English. Hence, an Indic LLM offers a more cost-effective solution for generating content in Indic languages without token pricing constraints. “It represents unrepresented languages and hence helps preserve them. Being the forerunner in this space, Tech Mahindra stands to benefit from the model. In fact, techniques from the model can be leveraged to benefit our customers,” he added.

Building Indic datasets

The effectiveness of an AI model hinges on the quality of its datasets. While ample English datasets are readily accessible, there is a scarcity of datasets for Indic languages and dialects. Recognising this challenge, various stakeholders, including the Indian government, are actively engaged in the creation of such datasets. 

Last year, Prime Minister Narendra Modi launched the Bhasini project, which aims to develop language translation technologies that can effectively translate content from one Indian language to another. The initiative also aims to crowd-source voice datasets in multiple Indian languages to enhance the availability and accessibility of digital services in local languages. 

Moreover, educational institutions such as the Indian Institute of Science (IISc) and IIT Madras (Ai4Bharat) and even Microsoft are involved in building datasets for Indic languages. “Despite various efforts, in India, datasets for languages other than Hindi are scarce and incomplete. Additionally, even Hindi data is fragmented,” Malhotra said. Additionally, he confirmed that Tech Mahindra is actively in talks with leading universities and other stakeholders for Project Indus. 

Tech Mahindra is sourcing information from various platforms, including Common Crawl, newspapers, Wikipedia and YouTube descriptions. “The information on dialects is primarily available through YouTube videos or spoken language samples. We are also sourcing information commonly available on the internet from books written in specific dialects.” Besides, Malhotra has also acknowledged that the requirement for computation and its accessibility is a key challenge for the tech giant. 

Banking on Bhasha Daan

For Tech Mahindra and for the success of Project Indus, the biggest challenge is gathering data for different dialects. For this, the IT giant is seeking contributions from the speakers of these dialects to help build the datasets. “For this reason, we have opened a portal to get a bhasha daan from Indians who speak that dialect. 

By clicking “Make a Contribution” on our website, you will find a user-friendly interface with all the dialects in which we collect data. Once you select a dialect, you can listen to a sample voice recording of how Hindi is spoken in that particular dialect. Users can then scroll down and anonymously record a sentence by clicking the record button.”

Gurnani took to X (formerly Twitter) to request contributions from the general public to assist in the creation of datasets for Indic dialects. “We humbly request a bit of bhasha daan from you. Please lend us your expressions, your vocabulary, your conversations and help us train India’s biggest indigenous LLM,” he posted.

Mitigating biases in datasets 

Oftentimes, the biases that manifest in AI models originate from biases present within the datasets. Since LLMs learn from a vast amount of text data available on the internet, when not appropriately addressed, these biases can impact the output generated by the models. 

While building datasets from scratch, Tech Mahindra must put guardrails in place to ensure this does not happen. “When we collect the data at the first phase, it is essential to realise that this data would have to go through cleaning to ensure there is no bias. To address this challenge, we would be using both human annotation and automatic techniques to ensure there is no racial, ethnic, or gender bias, etc.,” Malhotra said.

While it’s a commendable move, the success of the project hinges upon various factors such as robust data collection, efficient model training, and addressing linguistic nuances.

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UAE recently launched an Arabic language model Jais, which is an open source model containing 13 billion parameters built on a trove of Arabic and English-language data. With this launch, the UAE has elevated its position in the global AI race. In May, Abu Dhabi’s Technology Innovation Institute (TII) launched UAE’s first large-scale open-source model, Falcon 40B, and it ranked 1st in Hugging Face’s Open LLM leaderboard.  

A few days ago, China sprung back in the global race of AI chatbots. Five Chinese tech firms — Baidu (Ernie bot), SenseTime Group, along with AI startups Baichun Intelligent Technology, Zhipu AI and MiniMaz launched their AI chatbots to the public. Considering that it is a tightly regulated market where companies are required to submit security assessments for clearance before launching AI products to the public, the release of these models could be interpreted as a strategic move by the Chinese government to compete globally, particularly against the US.

Considering how it is a strict market and companies need to submit security assessments for clearance to launch AI products to the public, the release of the models can be construed as China government’s push to take on global competition especially the US. Interestingly, within 12 hours of its launch, Ernie bot ranked 1st in popularity in Apple’s app store in China. Baidu also plans to release ‘AI-native’ apps. 

Amidst such progress, does a country’s ecosystem facilitate this type of development, and where does India stand globally in such a race? 

Source: Stanford University AI Index Report

Indian Government Needs to Accelerate AI Investments

While countries are heating up in the global race, India stood at 8th position globally in terms of private investments in AI. 

Earlier this year, in the Union Budget 2023, Nirmala Sitharaman announced that three centres of excellence for artificial intelligence will be set up in top educational institutions. Pushing for a vision of ‘Make AI in India’ and ‘Make AI work in India,’ the Finance Minister emphasised on industry players partnering with research for AI solutions. However, there was no budget allocated from the government’s end to facilitate any type of AI development. 

Pushing for CoE in educational institutes alone might not lead to immediate development. Research institutes such as AI4Bharat are already doing that, but to have an accelerated pace of development, private players need to be involved. This would also involve setting up AI infrastructure projects, incubators, AI dedicated tech parks, and probably doubling down on AGI research funds. 

In the US, there are special exemptions for companies that invest in green and sustainable energy. Thereby inviting a number of big tech leaders investing in the segment. Offering incentives or tax redemptions of any kind to investors that can contribute in the AI space can help. Considering how there are tax exemptions for startups under DPIIT, introducing a niche segment for AI investments can boost growth. 

In the recent G20 Summit, Narendra Modi called for a global framework on cryptocurrency, artificial intelligence (AI) and other emerging technologies. Ironically, no government investments on crypto or AI have happened. 

Uncertain data regulatory measures in the past had put big tech companies on a cautionary mode, however, with the Digital Bill that was passed recently can help streamline future investments. 

The government needs to quickly step up AI investments else it would lead to a missed opportunity. Similar to how we arrived late in capitalising on manufacturing smartphones, semiconductors and GPUs, the same should not be repeated for AI and quantum computing. 

While the government needs to step up, efforts are materialising in the private segment. 

Atmanirbhar Bharat? 

IBM Chairman and CEO Arvind Krishna in his recent visit to India for the B20 summit, said that India should develop its own sovereign capability in AI, and consider establishing a national AI computing center. He even suggested that the government and private companies should be able to leverage computing and data infrastructure in ways that can harness AI for the country’s distinct goals and requirements. 

While over-ambitious plans are always in the making, there are obstacles that hinder big tech companies from freely operating or accessing information from the country. In May, Rajeev Chandrashekar, said that the foreign firms like Google have to invest in Indian AI startups in order to access the country’s data set, and that the government’s focus is in supporting intellectual property creation by domestic deep tech startups in AI and semiconductors. 

The government has always been clear in promoting development within India. Furthermore, as per a Linkedin report, India has the highest AI skills penetration in the world, which is an indication of the rich talent pool that can be capitalised. 

For accelerated growth, an effective collaboration between government and think-tanks or relevant private players might be the way. For instance, the latest Arabic model was launched through a collaborative effort – California-based AI company Cerebras in collaboration with Mohamed Bin Zayed University of Artificial Intelligence, and Abu Dhabi-based technology holding company G42. 

Last month, Cerebras Systems had signed a $100million AI supercomputer deal with G42 committing to delivering nine AI supercomputers. Cerebras’ supercomputer Galaxy Condor was used for training Jais. 

Such levels of partnerships and support are sprouting in India as well. AI4Bharat, a research lab at IIT Madras, has been on the forefront of building Indic large language models. AI4Bharat is also supported by Microsoft. In collaboration with the big tech, a generative AI-driven chatbot for government assistance called Jugalbandi was launched. The research lab is set to raise $12M funding from Peak XV and Lightspeed Ventures. 

Slowly Materialising 

Just when we were thinking how Indian tycoons were shying away from generative AI investments, there has been a string of announcements from Indian entrepreneurs and tech leaders in the last couple of weeks. 

Tech Mahindra announced Project Indus, an indigenous large language model that would support multiple languages. In the initial phase, the model aims to cover 40 Hindi dialects, and people can contribute to the model by lending their voice via specific prompts. 

Mukesh Ambani, recently announced Jio’s plan to develop India-specific AI models that will benefit various sectors including government, business, and consumers. The company also intends to invest in creating 2000MW of AI-ready computing capacity. 

While private players are waking up to actively spearhead an AI revolution of sorts, unless the Indian government actively steps in, advancements will only slowly move. With AI estimated to contribute massively to a nation’s economy, India’s AI investment at the right time can push it ahead in the global race – as of now, AI is only talk no action for the Indian government. 

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At Reliance’s 46th Annual General Meeting (AGM), Mukesh Ambani announced that his networking giant Jio is set to build “India-specific AI models” that will benefit different verticals of the country including government, business and consumers to make them accessible for “everyone, everywhere”. The company is also investing in developing up to 2,000 MW of AI-ready computing capacity.

Last year, Reliance acquired a 25% stake in Silicon Valley-based Two Platforms, a company focused on advanced technological projects aimed at creating interactive and immersive experiences through AI interactions with a sum of $15 million. “India has scale. India has data. India has talent. But we also need AI-ready digital infrastructure that can handle AI’s immense computational demands,” said Ambani.

Ambani added that seven years ago, Jio had pledged to provide broadband connectivity to everyone, and delivered on that promise. He mentioned that today, Jio is promising AI accessibility to everyone, everywhere, and he assured that they would fulfil this commitment.

The update comes soon after Indian IT Tech Mahindra announced that they are building their proprietary large language model called Project Indus. The open-source large language model aims to speak over 40 Indic languages in the first phase, including Kinnauri, Kangri, Chambeli, Garhwali, Kumaoni, Jaunsari and more. The initiative will be carried out by the Makers Lab of Tech Mahindra to develop India’s foundational model for various Indian languages, starting with Hindi. 

Read more: Generative AI is Just Fluff Talk for Indian IT

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After launching the Generative AI Studio under its amplifAI0->∞ suite of AI offerings and solutions, Tech Mahindra chief executive and managing director CP Gurnani recently took to X to share that it is the first major Indian IT company to be working on their proprietary large language model called Project Indus. 

The open-source large language model aims to speak over 40 Indic languages in the first phase, including Kinnauri, Kangri, Chambeli, Garhwali, Kumaoni, Jaunsari and more. 

The “​​civilisational” initiative will be carried out by the Makers Lab of Tech Mahindra to develop India’s foundational model for various Indian languages, starting with Hindi. The project collects Hindi dialect speech data to train a language model using NLP algorithms. Contributors can anonymously submit short to extended speech samples with the option to delete recorded data. 

According to the official website, mobile numbers are optionally collected for reference and gamification purposes, with encryption and a retention period of up to seven years. No personal information will be shared with third parties. 

However, it is not yet clear whether Makers Lab will build the model from scratch or base it on top of any existing LLMs like GPT-4 or Llama 2 like Stanford’s Alpaca and Vicuna-13B.

Unpacking the Gen AI Vows of Indian IT

When it comes to generative AI, all other Indian IT giants have also poured sufficient funds. However, their excitement in channelling the full potential of generative AI has led to no real use cases. 

The Indian IT giants are forming partnerships to advance generative AI adoption. In an earlier interaction with AIM, Wipro CTO Subha Tatavarti said that the company has been working around generative AI for the past two years. Wipro teamed up with IIT Delhi to establish a Center of Excellence (CoE) as part of their USD 1 billion AI-driven innovation initiative in the Wipro ai360 ecosystem. They aim to combine Google Cloud’s generative AI with Wipro’s AI IP, business accelerators, and industry solutions. 

Meanwhile, HCL partnered with Microsoft and AWS to enhance their generative AI efforts, while TCS is collaborating with Google Cloud to utilise foundational models like Vertex AI and generative AI Application Builder. Infosys follows an “AI First” strategy, focusing on specialised AI models from open-source LLMs, using them to accelerate clients’ AI initiatives through their Topaz framework, which encompasses generative AI-based services, solutions, and platforms.

No Moat, Only Fluff Talk

This is not the first time that we have seen ITs jumping onto the bandwagon of something new, something that is trending in the tech ecosystem. When Meta introduced Metaverse with much fanfare, we saw a similar reaction. 

TCS started the trend, followed by Tech Mahindra and Infosys, all announcing their metaverse-related products and services in February of 2022. As a part of the metaverse programme, TCS’ “themaTiCS” suite targets improving remote work experiences where only 25% of employees are in the office at any time. Following the lead, Infosys introduced the Metaverse Foundry similar to Topaz, offering ready-to-use templates and is said to have found 100 use cases for enterprises to embrace metaverse offerings spanning XR consulting, blockchain consulting, digital twin and more. Tech Mahindra also introduced the TechMVerse, leveraging its 5G capabilities to deliver immersive experiences. 

However, when Meta pulled the plug on their Metaverse dream, Indian ITs seemed to have lost interest too. 

This time, Indic Languages are coming back to riding the generative AI wave, building indigenous LLMs in India is a huge growth opportunity considering that it is home to 122 major languages and 1599 other languages, along with 22 official languages, as per Census 2001. 

At present, 58.8% of the content is in English, followed by Russian, Spanish and French. Forget about native languages like Garhwali or Kumaoni, even Hindi does not make it to the top ten highlighting a significant shortage of local language content. 

Project Bhashini, was introduced in collaboration with Microsoft. Finance Minister Nirmala Sitharaman also introduced the National Language Translation Mission (NLTM) in the 2021-22 budget.

Project Indus is an important initiative in this direction. Gurnani urged people from different vocabularies to contribute to making this project successful as an LLM is only as good as the data it is trained on. And Tech Mahindra is the only company to work on its promises.

Choosing AI Upskilling Over Model Building

When it comes to building its own LLMs, India is taking a different approach, focusing on the upskilling of their employees. This can be attributed to the fact that historically, technology adoptions have increased work volume, requiring more expertise and hands.

All the heads of these companies like K Krithivasan (TCS), Salil Parekh (Infosys) and C Vyakumar (HCL) have highlighted generative AI as the quarter one’s focal point of this year, with clients exploring its potential for enhancing productivity, content creation, and customer service. 

However, while generative AI is seeing a  strong interest, clients cutting back on IT spending is a concern for HCL and Infosys, impacting revenue growth forecasts, as per a report by The Register. Despite the short-term hype, executives believe AI will bring meaningful long-term benefits, although measuring its effectiveness remains challenging.

Tech Mahindra, Infosys, TCS, HCL and Wipro have expanded their partnerships with major tech players like AWS, Google and Microsoft partnerships to upskill employees in generative AI. Traditionally, the huge talent pool of India has been seen as beneficial for a quick adopter of technology and not building inhouse. And now with the upskilling, the process will only get faster and smoother.

Read more: Wipro’s Tryst With Generative AI Began Way Before ChatGPT

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Indian IT giant Tech Mahindra is working on an indigenous Large Language Model (LLM) that would have the ability to speak in many Indic languages, most notably Hindi.

Called Project Indus, the model will have the ability to speak in 40 different Indic languages, to begin with. More languages that have originated in the country will also be added subsequently. 

Tech Mahindra head CP Gurnani recently took to Twitter to request speakers of these languages to contribute to the project with their expressions, vocabulary, and conversations.

Building an LLM needs a big dataset, and the scarcity of Indic language datasets is a challenge. The approach taken by the IT giant is similar to that of Bhashini, a project launched by Narendra Modi to build datasets on Indic languages. 

Speakers of languages such as Dongri (Jammu & Kashmir), Kinnauri, Kangri, Chambeli, Garhwali, (Himachal), Kumaoni, Jaunsari ( Uttar Pradesh), Bhojpuri, Maithili,  and Magahi ( Bihar), among others can contribute to the project.

Previously, Gurnani, responding to a Sam Altman tweet, confirmed that Tech Mahindra is building an LLM specifically for India.

The post Project Indus: Tech Mahindra’s Initiative to Challenge OpenAI appeared first on AIM.

“AI will not replace you, but someone who uses AI will.”

Like a cautionary sign stuck on hazardous substances, the above line has been floating around for quite some time now. Economists and tech leaders have been ringing the death knell for a while cautioning about AI, which is looked upon as a potential reason for an impending apocalypse in the job market. With predictive stats on how certain jobs would be gone in an ‘xyz’ timeframe, a reality check would keep anxieties in check. So what’s the brouhaha all about? Has AI, or someone using AI replaced you? 

Executive outplacement and career consulting firm Challenger, Gray & Christmas, attributed 4000 job losses in May to artificial intelligence, making it the first time for the company to mention AI as a cause of job loss. 

Even though there have been massive layoffs owing to recession, including at big tech companies such as Microsoft, Meta, and others in the past six months, none of them have pointed to AI as a cause of it. However, observing the trend at those same companies on how each of them is adopting generative AI in their workflow, it is not difficult to connect the dots. But, having said that, the trends in the job market are reflecting another picture. 

Generative AI Fuels Job Market

With massive adoption of generative AI in enterprises, which is either fuelled by anxiety or enthusiasm, AI has indeed kick-started a job evolution in the market. As per AIM Research, the generative AI job market has witnessed a steady growth from January to June of this year. Generative AI-related job postings in the United States are said to have risen by 20% in May. From 3000 job openings in April, the job counts have risen to 4500 jobs in June. The IT sector has observed the highest number of job positions for generative AI roles. 

The figures may be indicative of jobs not seeing a decline, but job roles have been modified to suit the current wave. For instance, the role of a ‘generative AI engineer’, a role that never existed before, will require skills of engineers equipped in different fields. Therefore, the role of a generative AI engineer will encapsulate the roles of a deep learning engineer, ML, NL and also a software engineer. 

New roles that probably didn’t exist earlier are also sprouting in full vigour. The role of prompt engineers — a result of the chatbot revolution — has witnessed an uptick with companies increasingly seeking such roles. With the role offering salaries higher than Python developers, the job market is only looking positive. The massive shift brought by AI has also sparked a debate on how an entire generation will study for jobs that won’t exist. It might not be an overstatement to say that certain job roles may become redundant, but it is mostly because the nature of the job role is seeing a change. 

Together We Grow 

Enterprises are approaching the generative AI rage in a coalition of sorts — not via replacements, but through implementation and training of their employees to tame the system. TCS, which initially partnered with Google Cloud for their generative AI services, recently partnered with Microsoft Azure to train 25000 engineers on Azure OpenAI. 

In addition to implementing and training, enterprises are also building ways to support other companies thrive on generative AI. Tech Mahindra, which partnered with Microsoft to enable generative AI-powered enterprise search, unveiled their Generative AI Studio to help other enterprises kickstart their efforts in generative AI. Other IT companies have also followed suit. 

AI Over Humans? 

While most companies have found ways to work around the generative AI job buzz, there have also been companies that have openly embraced AI over human resources. Dukaan, a platform for enabling merchants to set up their e-commerce business, recently laid off 90% of their support staff replacing them with their new AI chatbot. The company claims to have saved cost and reduced customer resolution time since the move. Telecom company British Telecommunications said that over 55,000 jobs will be cut by the end of the decade, out of which a fifth will be in customer service where AI will replace staff.

There are also industries that have no choice but to embrace generative AI — travel industry being one of them. The industry that faced the biggest impact owing to the pandemic, is now slowly breathing and they all have integrated AI chatbots, ChatGPT plugins and other features — AI being the saviour. 

While you have companies and industries relying on AI, Zerodha on the other hand is all out to safeguard its employees from any form of AI job takeover. The company has been clear on its stance to adopt AI only if they deem necessary and it will not be at the cost of someone’s job. With a few companies allowing AI to replace jobs, and many others creating new jobs and also embracing AI to empower their employees to effectively use it without posing any threat to their jobs, it is fair to say that AI is becoming integral in all jobs. However, whether it will be a deciding factor to safeguard one’s job is not conclusive.

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“Anxiety or Enthusiasm?” – asked Emily Chang at the Bloomberg Technology Summit.  

“You need to have both – the thoughtfulness, the understanding, the nuance, and the tension between the two exists everywhere,” said Sam Altman, sharing his experience after travelling the Far East, speaking to users, developers and world leaders. 

Altman’s observation pretty much sums up generative AI adoption in enterprises, globally. It has been creating quite a bit of stir for enterprises, fuelling both enthusiasm and anxiety. 

AIM got in touch with technology heads and CXOs of leading companies across industries, alongside tracking the trends, to understand their adoption strategies, and the answers were quite surprising. Unlike previous AI adoption, which were mostly top-down, generative AI adoption seems to be being pushed in all the directions – i.e. top-down as well as bottom-up. 

Bottom-Up Approach 

Ironically, this is also the first time in the history of AI adoption where the bottom-up approach is gaining immense traction, where employees and teams come together, identify opportunities with use cases and PoCs, and are later supported by top management. 

This is mostly driven by enthusiasm. 

Most of the startups and growing companies fall under this category. These organisations are mostly experimenting with generative AI to address needs that benefit the company and their customers. Hopefully, along the way it might improve efficiency and increase productivity. Some of the examples include Swiggy, MakeMyTrip, Tech Mahindra and others. 

Amitkumar Banka, head growth marketing at Swiggy told AIM that the company is using generative AI to create customised food images based on specific requirements on their platform, and this is helping them serve millions of customers.

“From a Swiggy perspective, it is a bottoms up approach. Most teams, including analytics, product, design, corporate strategy have come together to form a strong point of view in terms of how Swiggy should take generative AI to the next level. Each person and team are coming up with their own use cases to take advantage of generative AI.” 

Narasimha Medeme, VP head data science at MakeMyTrip, said that the company has launched conversational bot using combination of generative AI LLM models plus speech to text models for Bharat customers (English and Hindi), and has also embedded usages in SEO and hotel review NLU systems. “Multiple other use cases and bots are being tested in beta stage for Bharat customers.”

Top-Down Approach

Top-down approach has always been a go-to strategy for most companies, as it is faster and easier to consult and adopt. For instance, of late, a lot of IT companies – the likes of TCS, Infosys, Wipro, Cognizant, Accenture, and others, are partnering with Microsoft and Google to unleash their generative AI initiatives, alongside other technology enablers like Oracle, SAP, Salesforce and Zoho. 

The adoption trickles down from the top. Qlik SVP Geoff Thomas believes that if a company wants to adopt a data culture and become a data-driven company, it would require strong sponsorship and support from the highest level of leadership. “It is often driven from the CEO, from top to bottom.” 

But, there is a flipside to this, this might be exciting for people on the top or leadership team to improve their efficiency and productivity, but it often fuels anxiety among employees and teams, particularly those who have been familiar with traditional methods and productivity tools. 

This also requires additional push from the organisation to offer training and certification programmes. Recently, Infosys announced a comprehensive and free AI certification training programme.

Hybrid Approach 

Here, most companies are following both top-down and bottom up approaches, alongside setting up a centre of excellence to fuel generative AI use cases. Some of the examples include HCL Tech, Infosys, Zoho, and others.

Infosys recently unveiled Topaz which is a set of solutions and platforms using generative technologies with 12000 AI use cases, and 150+ pretrained AI models. 

Wipro is also dwelling on a hybrid route. The company has partnered with Google Cloud to leverage its generative AI tools. Wipro will also integrate them with their own AI models, and pre-built industry solutions. 

So, What’s the Best Approach? 

In conversation with AIM, Ramprakash Ramamoorthy, Director – AI Research, Zoho Corp. vouches for hybrid approach, where he believes that the right mix of narrow and large models will be a win-win for companies and their customers. 

“Narrow AI, where one model is trained to do one task based on past experiences will thrive, helping companies automate redundant tasks. Whereas, LLM-based generative AI will augment these capabilities by offering seamless availability of information from across sources.” 

Zoho has a suite of 13 applications that is integrated with ChatGPT. “ Our focus right now will be to tightly integrate our AI stack across our product suites and also, in parallel, build in-house LLMs for businesses to provide seamless user experience in our offerings,” said Ramprakash. 

Each industry has its way of implementing generative AI in their functions. Deepika Kaushal, Deputy Vice President at Piramal Finance, confirmed to AIM that their company is still identifying use cases for generative AI applications and it is better for them to learn from the experts and later in future learn the capabilities to build in-house. 

On the other hand, Vivek Sahabadi, Head of Data Analytics at Navi, is of the opinion that the kind of data a company handles decides the right approach. “For fintech companies, where user data is critical, building their own models makes sense, whereas, in industries such as food tech, external models can be used.” 

All in all, it becomes important for companies to consider factors such as costing, expertise, data security, and in-house infra capabilities, before diving into the adoption of generative AI. Most importantly, the usefulness or second order understanding of generative AI should be established. One must not recklessly rush into it, irrespective of whether excitement or anxiety is pushing them towards it. 

The post How Companies are Botching Generative AI appeared first on AIM.

In today’s tech landscape, numerous IT companies are pouring substantial investments into Generative AI. TCS, a prominent player in the IT domain, is diligently working on developing its own alternative to GitHub Copilot to revamp enterprise code generation. Simultaneously, Accenture unveiled a new study titled ‘A New Era of Generative AI for Everyone’ exploring how generative AI and LLM serve as a compass. 

Another key player, Tech Mahindra, is taking a distinctive approach with its Generative AI Studio, empowering businesses with a user-friendly interface that facilitates a myriad of customisation options for their content. As the competitive landscape unfolds, these industry giants spearhead the charge towards AI innovation, each with their unique contributions and immense impact. 

Amidst this wave exists a notable IT giant that is leaving a profound imprint on the industry — Capgemini. Headquartered in Paris, the global IT services and consulting company offers AI-powered solutions for businesses to improve their operations, make better decisions, and gain a competitive advantage with over 360,000 employees in over 50 countries. The company’s clientele includes some of the world’s largest corporations, such as BMW, L’Oreal and more. Capgemini operates across three playing fields: customer first, intelligent industry, and enterprise management. 

“Our innovation approach is called hybrid intelligence which involves combining engineering intelligence with data science to develop a more efficient and robust solution,” Padmashree Shagrithaya, executive vice president and MD – Insights and Data GBL, at Capgemini, told AIM.

Read more: Gen AI is All Over the IT World, Except on Ground

Tech Solutions at Disposal

Capgemini employs pre-built models and frameworks such as TensorFlow and PyTorch, which can be fine-tuned for specific use cases, as well as in-house models like AI Class Box, which is used on top of other platforms to speed up the MLOps process. 

Another in-house platform is IDEA (Industrialised Data and AI Engineering Acceleration), which aims to help clients move to the cloud and ensure their total cost of operation is minimal. The company also focuses on AI-powered automation of ML processes using various platforms and partners, including open-source solutions. Containerisation is also another method to make models reusable across different domains.

Quantum Computing for the Win

IBM, one of the leaders in quantum computing plans to build a 1,000-qubit machine this year and a 4,000-qubit one next year. However, despite this progress, quantum-based products are still in the research and development stages, and quantum companies are seeking ways to bring the technology to the market. One of the companies actively working with IBM in this space is Capgemini, which has a dedicated quantum lab (QLab).  

“Our work in innovation primarily involves proof-of-concept projects with clients and promises to discuss this further as the conversation progresses,” said Shagrithaya.

Capgemini’s QLab aims to manage research initiatives that aim to create client solutions based on business objectives and cater to sectors that are expected to experience significant benefits from quantum technologies in the near future, such as life sciences, financial services, automotive, and aerospace. It is also responsible for facilitating initial experiments with clients in their pursuit of quantum advancements and enhancing in-house expertise and capabilities in this area.

Another major application of quantum computing lies in life sciences. Capgemini’s acquisition of Altran, a global leader in engineering and R&D services, which has strong capabilities in the Life Sciences space, further strengthens the company’s capabilities in the data-driven drug discovery space. However, there are several limitations of traditional methods in leveraging nature and the genome compared to quantum computing for drug discovery. It works with life sciences organisations to use quantum-based machine learning on IBM hardware.

AI Reshapes Fashion and Cosmetics

The global market for AI in the fashion industry witnessed substantial growth from $0.65 billion in 2022 to $0.91 billion in 2023 and is expected to be worth of $3.72 billion by 2027. 

In the field of fashion and cosmetics, AI is to cater to the increasing demand for transparency, safety, and sustainability. In the cosmetics industry, Capgemini is working with large cosmetic brands like Tarte that use a QR code and AI to provide consumers with comprehensive information about the product, ingredients, and how it matches the consumer’s skin type and cultural background. The information includes the comparison of the ingredients and their impact on the skin, enabling consumers to make informed decisions when purchasing a cosmetic product.  

Moreover, when it comes to designing, the popular clothing brand Levi’s already uses AI to automate and improve its denim designing process. Similarly, Capgemini is also working with popular

“AI has a significant role to play in meeting consumer demands for transparency, safety, and sustainability in both the fashion and cosmetics sectors,” Shagrithaya emphasised. “By providing detailed information to consumers and assisting companies in making sustainable choices, AI can contribute to the industry’s development and help create a more responsible and sustainable future,” she concluded. 
Read more: This Company is Paving the Way for Generative AI Services

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TCS is attempting to build its own Github Copilot alternative, which is touted to be used for enterprise code generation, the company COO N Ganapathy Subramaniam said in a recent interaction with Economics Times. 

As per him, while the project is at an initial stage, the company is looking to harness the vast internal code, data and resources TCS already has access to. The solution will be built through in-house LLM algorithms. It appears that this development is likely to be akin to the GitHub Copilot, but the model will be trained on its own data.

“The focus is really to build models and using those models, generate the code that can be deployed,” he said. He said if TCS wants to provide secure and contextual generative AI solutions to accelerate client projects, it cannot depend only on multiple large language tools from different providers but should have its own solution.

The announcement comes weeks after Analytics India Magazine reported that Infosys is planning to embrace generative AI along with the revised training of freshers to meet the growing demand for AI professionals in the IT sector.  

Could it be possible that TCS is looking to replace its employees with AI, given the recent announcement about its development of a GitHub Copilot alternative for enterprise code generation? There’s some indication in that respect. Last year, the IT giant witnessed a total reduction of 2,197 headcounts while its attrition rate stood at 21.3%. 

While Ankur Kothari, Co-founder of Automation Anywhere believes that “Automation allows companies to do more with less, enabling them to leverage new opportunities and create new roles that were not possible before,” the emphasis on ‘do more with less,’ will always be there.

Where west is headed

While the boardroom of Indian IT is still discussing the possibility and potential of generative AI in their sector, the Western counterparts have already started adopting the GAI (generative AI). Last week, IBM shocked the world with the announcement that the company would be ‘replacing the workers’ with AI. 

As per Arvind Krishna, CEO of IBM, the hiring in back-office functions, such as human resources, will be suspended or slowed. These non-customer-facing roles amount to roughly 26,000 workers, Krishna said. “I could easily see 30% (7,800) of that getting replaced by AI and automation over a five-year period.”

Recently, IBM’s Red Hat also announced a series of layoffs, with a significant number of individuals from the HR and management departments being affected. This sector is particularly susceptible to replacement by AI, making the news all the more noteworthy.

Additionally, part of any reduction would include not replacing roles vacated by attrition, as per an IBM spokesperson. 

In a similar vein, following the elimination of approximately 27,000 positions, Amazon’s CEO also acknowledged that the company will experience a more restrained approach to hiring in certain areas. “As our internal teams assess the priorities of our customers, they have made strategic decisions that may have resulted in downsizing, relocating personnel to new initiatives, or even creating new positions when the requisite skills are not currently possessed by our existing staff,” he had said.

West Admits it to be True

One trend that we can quickly observe is that all major tech companies are openly discussing their plans to reduce hiring while adopting AI technology. However, Indian IT firms are less forthcoming on the matter. For example, Infosys puts out statements such as “coding is much more structured than natural language, leading to more opportunities in data engineering and pipeline creation,” and “AI-driven solutions can help clients streamline processes and cut costs by as much as 60% to 70%.” However, the company does not mention anything about the potential job reductions resulting from these changes.

Similarly, while it is widely accepted that employees in HR & management are likely to be the first ones to fall, with many companies reducing their roles, Zoho told AIM that they don’t see AI replacing roles anytime in the near future. As per them, AI will enhance the productivity of employees and help them be more productive at work by letting them focus on problems that require human intervention rather than redundant and mundane tasks. 

Looking at the situation from far behind, it seems like that when it comes to job losses, Indian IT is trying to bury its head in the sand, while also trying to ride the wind by putting out statements here and there on Generative AI.  IT analyst and CEO of EIIRTrend, Pareekh Jain, also commented on the trend, stating that this year, Generative AI is the buzzword. He doesn’t believe anything impactful will come out of it in a couple of years. 

The post India IT Embraces AI and You Should Feel Dead Scared  appeared first on AIM.

Mohit Joshi, President of Infosys, has resigned to take up the position of Managing Director and Chief Executive Officer at Tech Mahindra. Joshi, who has been with Infosys since 2000, will succeed CP Gurnani as MD & CEO at Tech Mahindra when Gurnani retires on December 19, 2023. According to the release, Joshi will join Tech Mahindra well in advance to allow for a smooth transition.

This marks Infosys’ second leadership exit following a series of departures in the Indian IT industry. Ravi Kumar S., the former President of Infosys Global Services Organisation, also left the company to become the global CEO of Cognizant. Sukamal Banerjee, HCLTech’s Engineering and R&D head, was the most recent in the industry to step down.

At Infosys, Joshi was responsible for the company’s global financial services and healthcare business, including the banking platform ‘Finacle’ and the AI/automation portfolio. He also led sales operations and transformation, executive responsibility for all large deals, and was in charge of the company’s internal CIO function and the Infosys Knowledge Institute.

Before joining Infosys, Joshi worked with ABN AMRO and ANZ Grindlays in their Corporate and Investment bank. Mohit has been a Non-Executive Director at Aviva Plc since 2020 and is a member of its Risk & Governance and Nomination committees.

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The IT sector in India churns out nearly 2 million carbon emissions every year. Today, there is a growing consensus among large corporations to reduce their carbon footprints. IT giants such as Infosys, Wipro, Tech Mahindra and TCS, among others, have also taken significant steps to reduce their carbon emissions over the years.

However, one among them stands out for achieving carbon neutrality 30 years ahead of the 2050 timeline set by the Paris Agreement. Infosys became carbon neutral in 2020, way before others even pledged to reduce their own carbon footprint. 

In addition, the IT corporation has set a target of achieving net zero carbon emissions across all its business operations by 2040, which is a decade earlier than the goal established by the Paris Accord for 2050.

The Bengaluru-headquartered company made the commitment in 2011, four years prior to the signing of the Paris Agreement in 2015.

Infosys has achieved carbon neutrality, a feat that is yet to be replicated by its counterparts. The question remains: How did Infosys achieve this and how difficult is it to replicate?

A significant head start 

It is important to note that achieving carbon neutrality is a long-term and ongoing process that requires consistent effort and investment in sustainable practices.

While Infosys made a voluntary commitment to the United Nations (UN) to become carbon neutral almost twelve years ago, other IT giants have aligned their strategy with the goals of the Paris Agreement.

“Over a decade of focused effort has gone into becoming carbon neutral,” said Bose Varghese, ex-Head of Green Initiatives at Infosys. 

Infosys achieved carbon neutrality in 2020, whereas, during the same time, Tech Mahindra’s carbon emission was only down by 31%, with plans to be net-zero by 2050. 

Similarly, Wipro announced in 2021, its commitment to achieving Net-Zero Greenhouse Gas (GHG) emissions by 2040. During the same period, Tata Consultancy Services (TCS) also announced that it will reduce carbon emissions by 70% by 2025 and achieve net zero emissions by 2030.

Last year, Infosys president Mohit Joshi said that the company achieved its target by focusing on data and emerging technologies such as cloud computing.

For Infosys, the journey to carbon neutrality began in 2008, according to Varghese. In the following decade, Infosys hired more than 120,000 employees and expanded its office space by 178%—incorporating an additional 46 million square feet of floor space. 

Interestingly, during the same period, Infosys achieved a reduction of over 70% in emissions from their direct operations on a per capita basis.

Much of the credit goes to its founder Narayan Murthy, who was the chairman of Infosys when the IT giant began its journey to reduce its carbon footprint.

“Right from the first day, Infosys has recognised and fulfilled its responsibilities towards overcoming the challenges in our context. It has also taken on new responsibilities like reducing carbon emission, improving air quality, optimally using water and solar power,” Murthy said.

Infosys achieved its target by devising a strategy with a focus on enhancing energy efficiency and utilising renewable energy. Further, instead of purchasing offsets available in the market, Infosys was dedicated to developing its own carbon offset projects that focus on sustainable development of rural communities.

Focus on renewables 

To reduce its carbon footprint, Infosys has significantly invested in renewable energy over the years. In 2020, when Infosys achieved carbon neutrality, nearly 50% of its energy requirements were met through renewable energy sources. 

Infosys commissioned its first solar PV plant in 2011 at its Jaipur campus. Since then, the IT giant has expanded its investments in renewable energy throughout the country. With a combination of on-site and off-site systems, the organisation currently has an approximate capacity of 60 megawatts.

In 2015, Infosys also became the first Indian company to join the ‘RE100’ Renewable Energy Campaign.

Meanwhile, Tech Mahindra has proposed to increase its renewable energy consumption to 50% by 2025. Wipro’s focus on renewables, on the other hand, has been in alignment with Infosys. The company has taken an increasingly progressive stance as it plans to meet 100% of its energy needs from renewable sources by 2030. 

In 2017, only 27% of its energy needs were met from renewables.

However, the company has only accelerated its pursuit for renewable energy in the last couple of years. Last year, more than 50% of its energy needs were met from renewable sources. 

When it comes to HCL, in 2022, around 17.7% of its energy needs were met from renewable energy sources. However, it plans to increase its share of renewable energy usage to 80% by 2030.

Enhancing energy efficiency 

With nine development centres in India and more than 50 offices, Infosys is one of the largest IT companies in India. It had an employee strength of 314,015 in 2022 and serves clients in nearly 50 countries. 

A major chunk of the IT companies’ consumption of electricity is required to run their offices and data centres.

Joshi said that of the total 30 million square feet of office space that Infosys possesses, 25 million square feet has been awarded the highest rating for energy efficiency.

Further, according to Infosys, its data centres also consume 80% less energy for cooling compared to their previous setup. Infosys achieved all this through extensive research over the years and with a focus on sustainable technology. 

Infosys’ strategy for energy efficiency involves building structures that are efficient from the very beginning. This is achieved by integrating energy efficient building designs and green building technologies such as solar power, LED lighting, water conservation, and more.

The Bengaluru-headquartered IT giant has also leveraged the power of AI to become more efficient in using energy. In collaboration with BP, a UK-based energy firm, the IT giant has developed an Energy-as-a-Service (EaaS) platform that utilises cloud computing and AI to streamline operations and monitor energy consumption in real-time.

In comparison, Tech Mahindra, Wipro, TCS and HCL have undertaken various processes to enhance energy efficiency. Here, it is important to note that each company has its own unique circumstances and sustainability goals, and the path to carbon neutrality may vary depending on multiple factors such as the industry sector, geography, and available resources. 

However, Infosys was among the first Indian companies to commit to achieving carbon neutrality. With its strong focus on sustainability and technology, Infosys achieved carbon neutrality well ahead of many other companies.

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The world is scared and holding on ever-so-tight to its job. With Microsoft laying off 11,000 employees, Google planning on putting another 12,000 on the chopping board, and GitHub losing 10% of its employee base, a new danger is en route. As per recent data, in 2023 alone, more than 100k tech employees have lost their jobs. The numbers are huge and many of these techies, desperate for a job, are likely to find themselves visiting job forums on the dark web. 

According to a Kaspersky report, 61% of the total job postings on the dark web is for developers. These jobs are in demand because of the attractive perks they bring along. These developers are not required to come to work, enjoy unlimited leaves and the flexibility to choose their schedule, tasks and scope of work.

(Median salaries offered, source: Kaspersky)

Additionally, just like a regular job, the positions on the dark web are varied, like full-time, part-time, traineeships, business relationships, partnerships, or team membership. These job postings also promise incentives like performance-based commission in addition to the salary. For instance, a company advert promised a salary of $10k along with a fixed percentage to be given as a bonus. 

Not that different from surface web jobs

Interestingly, these dark web organisations even have employee referral programs that offer bonuses to those who engage new workers. The only thing that differentiates the dark web job market from the legalised job market is the lack of legally binding documents. The selection criteria too isn’t very different from the regular. Since the employers are on the dark web to seek a highly skilled workforce, the selection criteria involve test assignments, CV/portfolio check, interviews, and even probation completion. 

Of the total jobs posted, Kaspersky reports that 82% had test assignments, while 37% of them asked for CVs and portfolios. About 26% of them conducted interviews and 2% even implemented a probation period. 

Additionally, the report claims that developers were among the best paid with salaries as high as $20,000 per month. Job requirements like “Cybercrooks needs professionals with specific skills to penetrate the infrastructure of an organisation, steal confidential data, or encrypt the system for subsequent extortion,” are pretty frequent. 

Moreover, since most of the payments on the dark web are made in crypto, the developers can easily evade any tax liability via methods like peer-to-peer transactions, which again becomes a headache for government agencies. 

 (A typical structure of how organisations work on the darkweb. Credit: Securelist)

Salaries are not that great either!

Many developers go down the forbidden lane hoping for the lucrative salaries that illegal work comes with. However, not all that shines is gold. As per the report, the salaries offered on the dark web do not vary much from what devs get from legitimate jobs. Still, individuals unhappy with their jobs/office culture veer towards the dark web. As per the report, a substantial percentage of employees in the legitimate economy quit their jobs to find similar employment on the dark web market. Further, market volatility, layoffs and pay cuts too push developers to explore the dark web job markets. 

The lack of stringent requirements for these jobs, too, makes it attractive to many. Some of these jobs do not ask for higher educational qualifications, military service records, or absence of prior convictions, etc. Moreover, the lack of awareness of potential repercussions and a casual attitude towards them are more reasons why people search for work on the dark web. However, working with underground teams carries significant risks. The participants may become deanonymised and face legal action, and even receiving payments is not guaranteed.

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A host of Indian IT companies have reported their third-quarterly results, with Tech Mahindra having done so this week. While TCS emerged one of the most successful companies throughout the quarter, Tech Mahindra had a minor setback. We also saw companies like TCS increase their patents to close to one patent every day for a whole year. Let’s dive deep and see how these companies fared in Q3 2023. 

Revenue and Attrition 

Barring Tech Mahindra, most Indian IT companies registered a rise in profit growth percentage, owing to many factors including rupee depreciation which lead to a slight increase in the margins for these IT companies. 

While Infosys saw its revenue increasing by 2.4% QoQ and 13.4% YoY, TCS jumped 13.5% YoY and 4% QoQ. In a similar vein, HCL Tech’s revenue growth shot up by 19% YoY and 5.3% QoQ. Tech Mahindra on other hand, saw its revenue increasing by 12.7% YoY and 0.2% QoQ. 

And while most IT companies showed positive growth, the situation was different when it comes to the headcount. Several companies noticed a dwindling headcount, which for investors, is a bad sign as low headcount correlates with slowdown in coming quarters. TCS, for instance, saw a decline in headcount after 10 quarters and in Q3 2023, the company reported a loss of 2,197 employees.

TCS claims that the reason behind low headcount is excessive hiring in the previous quarters. As per Milind Lakkad, chief HR officer, TCS makes significant investment in terms of hiring fresh talents. “We have invested in making our hires productive. That investment is now taking shape, coupled with all the cost-efficiency measures,” says Lakkad.

However, the low headcount coupled with a declining book-to-bill ratio tells another story.

Likewise, Tech Mahindra saw a decline of 4.4% QoQ in total headcount, in Q3 2023. The company reported a loss of 6,844 employees – the highest for an Indian IT company. 

But not all is lost, bucking the trend, companies like Infosys and HCL Tech saw a rise in the headcount. Infosys added 1,627 employees in Q3 2023, while HCL Tech reported an increase of 2,945 employees. 

When it comes to revenue share by geography, almost all the companies saw a major chunk of the revenue pouring in from North America, followed by Europe. HCL Tech’s 63.4% revenue came from North America, and around 28.7% from Europe. TCS on other hand, saw 50.7% coming from North America and around 31.6% from Europe. And Infosys bagged 62% of the revenue from North America and around 25.8% from Europe. 

Tech Mahindra, perhaps, is the only company among IT giants that had less than 50% of the revenues coming from North America. For them, it was 49.7% from North America and 24.4% from Europe. Additionally, it is the only company which had over 25% of the revenue coming from geographies other than North America and Europe (25.9%). 

Revenue Sources

While companies like Infosys, TCS, Tech Mahindra, and HCL Tech claim to be IT companies born in India, are they really “IT” companies? It is a well-established fact that Indian IT companies are essentially service providers for global technology companies, but are they really working in the field of IT? For instance, Tech Mahindra, which even has ‘Tech’ in its name, receives most of its revenue from the media, entertainment & communications sector. A majority of Tech Mahindra’s acquisitions too are from this sector. 

Similarly, Infosys receives most of its revenue from the financial services & retail sector. HCL Tech, too, reported a majority of its revenue share coming from this sector. TCS, one of the largest IT companies coming from India, saw most of its revenue coming from BFSI and retail & CPG sector. 

However, when it comes to actual technology, Tech Mahindra saw a mere 10.3% of the revenue coming in from there. Infosys reported 8.1% of the revenue coming from the tech sector and TCS had 8.7%. HCL Tech perhaps has the largest share coming from technology, i.e, around 14%.

While it’s no surprise that most of these companies provide backend services to the finance, media and other sectors, there should be some push for indigenous development in the field of AI/ML.  When we consider that companies like Infosys were among the first to invest in OpenAI back in 2015, its significance increases. And while IT firms like TCS are exhibiting a little improvement in their patent filing, their research-related revenue is still not very high. 

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In 2022, when most tech companies in India unanimously lambasted moonlighting, Tech Mahindra was one of the very few companies surprisingly unfazed by it. CP Gurnani, CEO of Tech Mahindra, even went on to say that the company was working on policies for employees to pursue more than one job at a time. 

Recently, Tech Mahindra hit the headlines for numerous reasons, be it collaborating with Airtel to provide 5G services or with IQM to get ahead in the quantum computing space. The company invested in AI and analytics and heavily in the metaverse. 

Let’s review Tech Mahindra’s journey in 2022. 

Airtel, Tech Mahindra join hands

Tech Mahindra and Airtel teamed up to implement 5G for business solutions at Mahindra’s Chakan manufacturing site earlier this year, making it India’s first 5G-enabled auto manufacturing facility. Tech Mahindra is also on track to generate about $1 billion in revenue in FY23 from just 5G solutions. From $125 million in FY21 to over $600 million in FY22, Tech Mahindra’s revenue from 5G solutions has increased almost five times.

Working on 60 metaverse projects

Another major event for Tech Mahindra in 2022 was the launch of its metaverse. Gurnani had told Analytics India Magazine earlier this year that the company was working on 60 metaverse projects globally. He stated that the business is taking bold steps in building several new capabilities, including 5G, metaverse, and the Makers Lab, which they successfully set up at eight different sites. He added that Tech Mahindra would keep funding data and AI laboratories as well as sports-related tech verticals with tools like Fan, NXT.NOW, netOps.ai, and others.

In addition, Tech Mahindra and Union Bank of India collaborated to open the country’s first PSU Metaverse Lounge. For the bank, Makers Lab had created a metaverse ‘Virtual lounge’ to provide a dynamic and engaging customer experience.

Tech Mahindra plays sport

The International Chess Federation (FIDE) and the All-India Chess Federation have strengthened their partnership with Tech Mahindra to launch FIDE’s first-ever app for iOS and Android, built on the digital platform Fan Nxt. Now, on the sidelines of the 44th Chess Olympiad, organised by FIDE. 

As part of this global tie-up, Tech Mahindra will come on board as a digital partner for the FIDE chess Olympiad which will take place in India for the first time. It is also working on creating an AI-powered immersive digital platform for chess fans worldwide. 

Profit and loss

On the market side, however, Tech Mahindra’s shares didn’t perform so well. In the past one year, the share prices of Tech Mahindra fell by 43.20%, sharing the fate with other tech companies worldwide.  However, the profit went up by 3.3% QoQ in Q2 2023 and by 20.7% YoY.

Its attrition rate also declined to 19.2% in Q2 2023 from 22.2% in Q1 2023, which as per the company stands lowest among its peers, with a headcount of 163,912. 

Major partnerships 

• Tech Mahindra and Digital Economy Promotion Agency (Depa), a government agency, have signed an MoU to accelerate digital transformation in Thailand. As part of the partnership, both organisations will co-develop innovative digital solutions and execute commercially viable projects and use cases for enterprises in areas.

• Tech Mahindra partners with Google, wherein Tech Mahindra will be responsible for GIS processes from data creation, resourcing, insights generation, and the actual collection of the street-level imagery.

Looking back

In an interaction with Analytics India Magazine, Nikhil Malhotra, global head, Makers Lab, Tech Mahindra, said, “While 2022 has been a fantastic year for setting the stage for a tech-driven post-pandemic future. I believe it is now up to businesses and end-users to further build on this foundation and create game-changing innovations in various human-centric areas in 2023 and beyond.”

Highlighting technologies like quantum computing, artificial intelligence, smart robots, metaverse and Web 3.0, he said, “These technologies are going to be key to further boosting our innovation quotient ever further.”

Hasit Trivedi, CTO, digital technologies & global head, Tech Mahindra, recently said that the company is heavily investing in the AI sector and is focusing on autonomous driving as well. Earlier this year Tech Mahindra picked up 80% stake in Geomatic.AI to build on AI capabilities.

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India’s communications solutions provider Bharti Airtel (Airtel) and digital transformation and consulting company Tech Mahindra announced a strategic partnership to deploy 5G for enterprise solutions at Mahindra’s Chakan manufacturing facility, making it India’s first 5G-enabled auto manufacturing unit.

Chakan’s network connectivity has enhanced owing to the “5G for Business” solution, resulting in faster software flashing speeds, a crucial step for all vehicle dispatches. Managers can now conduct numerous software flashing sessions concurrently because of the high speeds and extremely low latency, which shortens the turnaround time for an activity. Now that the computerised vision-based inspection is entirely automated, the quality of the paint has improved. As part of its #5GforBusiness offerings, Airtel has been testing use cases and spectrum delivery at several sites with a variety of partners.

Together with Tech Mahindra’s industry expertise, Airtel’s integrated connectivity portfolio of #5GforBusiness offers customers specialised services, tried-and-true system integration skills, and 5G enterprise solutions like Factory. Enterprise customers will profit from NXT’s domain knowledge in planning, designing, installing, and managing private wireless networks for businesses. It will hasten the adoption of game-changing network technologies like 5G in India. This collaboration is in line with Tech Mahindra’s NXT.NOWTM framework, which focuses on investing in cutting-edge technologies and solutions that enable digital transformation and satisfy the changing needs of the consumer while simultaneously aspiring to improve the ‘Human Centric Experience’.

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After Pune and Bengaluru, T-Systems, one of the leading European IT service providers, plans to add Nagpur to its list of delivery centres. These centres are aimed at providing intelligent digital solutions and efficient cloud services to T-Systems’ global customers. 

The new centre is established in partnership with Tech Mahindra, and will open employment opportunities for 6,000 people across various departments including sales, marketing, technical roles, and others, over the period of 24 months. To meet the needs, Tech Mahindra will enable the building up of a dedicated workforce delivering cutting-edge technological solutions in digital and cloud spaces. 

T-Systems attributes Tech Mahindra’s access to market, talent from Tier II cities, and competitive pricing as primary reasons for this partnership. 

CP Gurnani, CEO of Tech Mahindra, said that Nagpur can be the next digital hub for leading innovation because of several factors, like ease of doing business, availability of manpower, and accessibility to infrastructure. He also added that its partnership with T-Systems will enable employment opportunities for local talent to work and collaborate with a global team. 

The move further supports the notion that post-pandemic, IT companies are not just restricting themselves to Tier-I cities anymore, but are expanding their presence and workforce to Tier-II and Tier-III cities. With growing attrition, IT companies are looking to harness the entry-level talent pool available in smaller cities.  

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AI is all-pervasive. Infused into every aspect of any business, it can transform business models and the processes that define it, the applications that deliver it, and the infrastructure that supports it.

Hasit Trivedi, CTO Digital Technologies & Global Head – AI at Tech Mahindra, believes that in recent years, AI has become one of the most potent tools in tech history to bring machines and humankind together.

In this exclusive interview with Analytics India Magazine, Hasit Trivedi discusses how Tech Mahindra is helping their customers leverage AI/ML, AI regulation and also how the IT giant is leveraging AI for humanitarian causes.

AIM: Tell us a bit about the work that Tech Mahindra has been doing in terms of AI.

Hasit: At Tech Mahindra, we have a suite of Artificial Intelligence (AI) solutions, TechM amplifAI^0->∞ , that is helping us democratise and scale the deployment of AI technology for enterprises globally. 

Our labs across geographies serve as innovation hubs wherein several exciting projects run in different areas of AI and integrate cutting-edge technologies to build numerous solutions for various industries. For example, we implemented a deep learning-based model for a telco company to predict if a truck roll is required for a customer ticket. The ML model could predict with 70% accuracy if truck rolls are required for customer tickets. In 25% of the truck rolls to fix issues at customer locations, no fault was found, subsequently resulting in substantial revenue savings.

AI has helped us remain committed to ensuring the well-being of our employees, customers, and partner ecosystem. We have multiple programmes across the organisation that have active deliveries based on AI and Advanced Analytics for specific use cases like order fallout, fault prediction, pole detection, and asset maintenance using computer vision-based solutions. 

We also work with hyper scalers for their product maintenance, helping them with AI Crowdsourcing, and more. Similarly, our AI NLP-based chatbot is implemented for many clients. We have built an AR/VR-based training module for our employees, and we are continuing work on product development involving technologies like AI and AR/VR. Another project we are currently working on includes Autonomous Driving for Indian road conditions based on Vision AI. 

AI is a lucrative investment sector for us as it guarantees improved business outcomes, resilience, customer satisfaction and retention, along with enhanced operational efficiencies.

AIM: Tell us a bit about TechM amplifAI^0->∞ . What are the problems it solves? 

Hasit: TechM amplifAI^0->∞  is a suite of AI offerings and solutions to democratise and scale the deployment of AI in a responsible manner. We have different AI solutions and capabilities like Chatbot Analytics, Complaint Analytics, Call Data Analytics, Demand Forecasting Workbench, Intelligent Automation, AI Store, AI Maturity Assessment Utility, ITSM Problem Analytics, Alert Noise Management, DB Anomaly Detection, Provisioning Commerce, AI & Automation CoE, AI Discovery, Enterprise AI/Democratisation of AI, MLOps, Document AI, Computer Vision, Edge AI, and more. 

Through these offerings and solutions, we help enterprises amplify human potential and solve complex problems to future-proof business operations. The most salient feature of TechM amplifAI^0->∞  is that its AI solutions can eliminate existing bottlenecks by offering tailor-made services and automating processes to increase the throughput and profitability of enterprises. 

We believe in the strategy of aspiring for Zero to Infinity. AI can offer a distinctive competitive edge and defence in a highly disruptive environment for ZeroOps. It can help businesses with InfinityOps to solve complex problems and create disruptive capabilities with AI-driven insights, action, and agility. 

Our approach to customer lifecycle and enterprise AI is structured and caters to any stage of the AI & Data Science lifecycle. We help clients in their enterprise AI journey through our end-to-end implementation and consultation offering that caters to a customisable AI journey for clients. For example, AI improved data accuracy by 90% and reduced 60% human effort for an insurance claims company; a leading US-based telecom company enabled AI/ML to optimise prices and discounts and better serve its customers. 

AIM: Can you shed some light on the AI strategies implemented by Tech Mahindra in creating a sustainable advantage for enterprises? 

Hasit: To harness this capability fully of AI, Tech Mahindra’s design thinking-led approach and frameworks help identify AI opportunities in organisations. Further, our experts determine the right AI strategy and chalk out the sustainable growth roadmap for organisations. Competencies are augmented as we drive digital transformation globally. In tandem with this, Tech Mahindra actively promotes the DigitALL philosophy for comprehensive business transformation. 

Tech Mahindra has invested heavily in innovations, building IPs and AI solutions, and acquiring products that could enable next-generation AI solutions for our clients. Besides, we have platform-centric solutions, our in-house or partners’ platforms. These platforms could cater to a point solution for an industry problem or enable development solutions for a broad spectrum of data science problems. 

We have a structured approach towards enabling talent, reskilling, and refactoring them across the enterprise, thereby democratising AI. We have a team of domain consultants who specialise in industry verticals like banking, financial services, insurance, supply chain, manufacturing, health care, life sciences, telecom, retail, consumer goods, and more. This makes it easy to create value propositions, define the role, and prioritise the use cases and areas to solve the business problem.

AIM: Can you elaborate on some of the challenges prevailing in the industry?

Hasit: AI and ML solutions are transforming several operational, functional, and strategic landscapes across industries. In the enterprise context, AI systems have the potential to improve productivity and open up new avenues of revenue by building insights from data that define business and customer interaction patterns. On the flip side, perceived unfair treatment by the AI model can lead to trust issues, brand value erosion, and missed business opportunities—all directly impacting the top line. This is where AI ethics and fairness become important. 

Users’ ethics and integrity issues have become a significant concern with advanced AI solutions. These solutions cannot always be neutral, and sometimes AI judgments are intangible to humans; sometimes, they ignore data accuracy and give ambiguous results. 

TechM amplifAI^0->∞  is robust in ensuring no bias, and we have defined the correct principles and transparent governance structures that build trust in AI amongst all stakeholders. We ensure that the risk control policies are in place for efficient monitoring and reporting.

Another challenge that many organisations face is the proper infrastructure support that AI requires, leading to high implementation costs. In some cases, poor IT infrastructure prevents organisations from implementing AI solutions. Our AIOps services have empowered us and our customers to leverage AI to improve IT and Network operations. Machine Learning Operations (MLOps) is critical in delivering high-performance production of AI/ML models at speed and scale, standardising and streamlining ML lifecycle management. Combining practices and processes helps organisations make seamless and efficient development, deployment, scaling, and maintenance of AI/ML models. 

Besides, finding the right talent for using AI is a daunting task for enterprises. There is a huge demand for AI professionals in India, and upskilling and reskilling professionals is the way to address this demand.

AIM: Is Tech Mahindra leveraging AI for any humanitarian causes?

Hasit: At Tech Mahindra, we firmly believe that technology is the thread using which we can mend the present to create a more inclusive and sustainable society for the future. Technology today defines new realities for people from different socio-economic backgrounds and cultures by bringing them all on the same pedestal. 

We leveraged AI to research potential therapeutic drugs for the treatment of COVID-19. In this application, we used AI to identify helpful information regarding hospital beds, oxygen, and more, from social media to help people in need. Our Whatsapp-based SOS Seva helped save lives, reaching at least 125,000 associates and partners.

Further, we designed an app to help farmers access important agriculture-related information and insights from government agencies like IMD, ISRO, Ministries of Govt. and Water (built with the Principal Scientific Advisor to Govt. of India’s office). 

We have also leveraged Vision AI to identify pests based on an incoming photograph from a farm and provided information to the farmers on how to address the pest sustainably. We are working closely with PJTSAU (Telangana Agricultural University) for this initiative and contribute to India’s pest repository.

AIM: What are your views on AI ethics? Do you think the Indian government needs to have strong AI regulations in place?

Hasit: An ethical approach to AI is an absolute imperative. Knowing that an AI system will do whatever it is assigned to without considering its effects or legality, we must have strict regulations to prevent AI from generating adverse outcomes. Fortunately, governments, organisations, and institutions are categorising and identifying safe ways to deploy AI into their daily operations and secure sustainable growth. 

The growth of AI startups and career opportunities has resulted in AI gaining massive traction, all for the right reasons. The employment market will constantly evolve, with several jobs getting automated while new ones getting created; however, aspirants will have to acquire new skills, including AI operational prowess, to remain relevant in the future job market. Again, interpreting the future, society at large will have to broadly embrace ethics and humanism concerning the progress of AI.

Undoubtedly, AI is already shaping global competitiveness, promising a strategic advantage to early adopters. With other mega-economies having joined the race to adopt AI safely and ethically, it is time for our government to employ AI-specific policies to gain the most out of it. The Government of India has already embarked on the AI technology revolution. With a few more policies strengthening the governance of its deployment, India will seamlessly harness its enormous digital capital through AI-driven development.

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