“I am going to Goa for a vacation, show me what I can wear,” we asked, and within seconds, this new tool called–MyFashionGPT was able to fetch results on shorts, t-shirts, sunglasses, hats and sunscreen.
The brainchild of Myntra. This new tool enables users to search using natural language, alongside giving relevant suggestions based on customer queries. “This is a first-of-its-kind solution in e-commerce in India and possibly globally,” avered Myntra’s chief technology and product officer, Raghu Krishnananda, in an exclusive interaction with AIM.
He said that they used ChatGPT for query understanding and then leveraged its own search infrastructure to fetch relevant and related products from its catalogue and show them as collections. It is working on more features that use generative AI, and will get launched in the near future on the platform.
Tech Stack
Myntra has been using both proprietary and open-source algorithms based on user cases. Krishnanda believes that open-source algorithms provide a quicker path to market. “When proprietary data is involved, using a hosted model would be the right approach where we train the open source models on Myntra-specific knowledge such as the product taxonomy.” The company has also developed its own AI models and combined multiple models to solve for specific use cases, especially in image science applications.
Myntra is currently leveraging AzureAI services that give access to OpenAI models such as ChatGPT3.5, Dall-E, etc. “We are looking at privately hosted models as well as managed service models based on the use cases, and we will continue to have partnerships that serve this need.”
Myntra’s latest tool MyFashionGPT, is integrated with ChatGPT3.5. “For text-related generative AI, we use ChatGPT3.5 and for image-related generative AI, we use Stable Diffusion-based models in conjunction with other internally developed models.” A number of other AI-based solutions in Myntra (non-generative AI) such as MyStylist have been developed in-house.
Myntra’s Generative AI Prowess
Synonymous with fashion and lifestyle, Myntra have been aggressively pushing through to bring generative AI onto their platform with the big picture of enhancing customer experience. “We have been using AI for more than five years now and see huge benefits. In that sense Myntra is an AI-first company,” said Krishnananda.
Myntra’s adoption of AI-based solutions has not only helped customers but also sellers. “AI-based solutions such as trend identification, demand prediction, and others are helping sellers bring the right merchandise and assortment and stay ahead of the trend,” said Krishnananda. Furthermore, its inventory and route optimisation algorithms have helped improve logistics.
While Myntra may have carved an AI niche in the fashion segment, other e-commerce players have also dived into the generative AI wave with a number of use cases (see below).
Source: Paxcom Report
Tech giant Amazon, who have already been implementing generative AI solutions on AWS and other services, are also working on bringing the same to its e-commerce vertical. The company is testing AI-generated customer review highlights that will present concise summaries of written reviews to aid a shopper in making quick purchasing decisions.
To cater to small-scale sellers, last week Amazon launched its virtual assistant ‘सहAI’ (sahai). The AI tool will help sellers list their products online, analyse sales trends and thereby assist with improving sales.
Challenges Galore
Training and inference for very large proprietary generative AI models is a challenge for any company, and it is easier said than done. “We are working to take ‘smaller’ open-source models and fine tune them on our own data,” said Krishnananda, emphasising the safety and cost benefits of training the model, without revealing the names of the smaller models (namely, Llama, Vicuna, etc.) being used.
Confident Myntra believes that it faces fewer challenges when it comes to adopting generative AI in their workflow. Krishnananda also spoke about how they are bringing adoption not just on the platform front, but also within teams. “The tech team is taking measures to democratise the use of Generative AI by providing internal APIs that the broader tech team can play with, as well as organise tech talks and knowledge sharing sessions,” he concluded, saying that they are building in-house frameworks for low cost fine-tuning and inference using GPUs.
