TIME magazine created a euphoria of sorts in the tech world by dedicating its latest issue to the 100 most influential personalities in the field of artificial intelligence. While AI stalwarts like OpenAI chief Sam Altman, DeepMind cofounder Demis Hassabis, xAI’s Elon Musk, Nvidia’s Jensen Huang and Hugging Face’s Clément Delangue were duly credited for their noteworthy contributions, the extensive TIME100 AI list compilation that meticulously hand-picked experts from different fields of AI including research, ethics, and innovation seems to have missed out some well-deserving individuals in AI.
Let’s take a look at some of these AI heavyweights who didn’t make the cut for TIME.
When it comes to giving back to the open-source community, Andrej Karpathy, the computer vision genius, is the first name that pops into everyone’s mind. Back in January, he released NanoGPT, a fast repository for training and tuning medium-sized GPTs, building upon his earlier work with miniGPT for GPT language models. His latest contribution is Baby Llama, which he made by tuning NanoGPT to use Meta’s Llama 2 architecture instead of GPT-2.
The former AI director at Tesla came to fame for his immense contribution to Optimus, Tesla’s groundbreaking humanoid robot. Karpathy also played a pivotal role as the head of Tesla Autopilot’s computer vision team. He is also known for his comprehensive educational resources, coding tutorials on YouTube and more.
Mira Murati
OpenAI has been the most influential name in AI since the team released ChatGPT in December 2022. This is evident as all the co-founders, namely Greg Brockman, Ilya Sutsvekar and Sam Altman are rightly placed on the list. Along with that we also have Jan Leike (superalignment co-lead) and Anna Makanju (vice president of global affairs). However, Mira Murati, the CTO of OpenAI was conspicuously missing from the list. Since her appointment in 2018 as the VP of applied AI and partnerships to eventually becoming the CTO in 2019, Murati has spearheaded the making and release of notable generative AI models like DALL.E-2, GPT-3, GPT-3.5, GPT-4 and more.
Murati, 35, completed her mechanical engineering from Dartmouth College, interned at Goldman Sachs, and has rich experience of working in engineering roles at Zodiac Aerospace and Tesla for ‘Model X’. She later became VP of product and engineering at Leap Motion, a company specialising in hand motion-controlled technology for PCs and Macs, where she oversaw the launch of hand-tracking software for VR.
Jakub Pachocki
Talking about OpenAI, another name that has surprisingly not made it to the list is Jakub Pachocki, principal of research, who joined the company in 2017. He is the brain behind the much-celebrated GPT-4. According to Altman, “We wouldn’t be here without him”. He has garnered immense recognition for his technical vision and leadership, emphasising his pivotal role in GPT-4’s development. Pachocki got into AI when AlphaGo came out, and he saw that deep learning could push computers further. He played a big part in OpenAI’s development of a bot for Dota 2, where it trained by playing itself until reaching a pro level.
David Silver
Google DeepMind is often referred to as the champion of reinforcement learning and that is because of their principal research scientist David Silver who missed the well-deserving spot on the list. He is also a professor at the University of London. His research primarily revolves around the development of AI agents through RL techniques. He co-led the project that integrated deep learning and RL to achieve proficiency in playing Atari games directly from pixel data, and spearheaded the AlphaGo initiative, making it the first time for a program to defeat a top professional player in the complex abstract strategy game of Go.
Additionally, Silver’s leadership of the AlphaZero project resulted in an AI system autonomously mastering chess, shogi, and Go, surpassing the world’s strongest programs. Most recently, he co-led the AlphaStar project, which achieved grandmaster-level gameplay in StarCraft. His contributions have garnered him prestigious recognition, including the ACM Prize in Computing, the Marvin Minsky Award, Mensa Foundation Prize, and the Royal Academy of Engineering Silver Medal.
Ian Goodfellow
Notably absent in the list is Ian Goodfellow, the renowned creator of Generative Adversarial Nets (GANs), who currently serves as a research scientist at Google DeepMind. GANs were one of the early methods of generating images before diffusion models came in. Currently working as a research scientist at Google DeepMind, Goodfellow is a prominent figure in the AI field. He holds the distinction of being the first author of the textbook “Deep Learning” (2016), co-authored with AI experts Yoshua Bengio and Aaron Courville. The Standford graduate has held significant positions at OpenAI and Apple in the past.
At Google DeepMind, Goodfellow collaborates with Oriol Vinyals, a principal research scientist, with whom he has partnered on various research projects including one concerning the TensorFlow interface while both were at Google. Again in 2015, they worked together on research related to neural network optimisation problems.
Ashish Vaswani
It’s pretty safe to say that BIT Mesra graduate Ashish Vaswani played a significant role in the success of companies like OpenAI, which are renowned for their cutting-edge NLP models. ChatGPT would not have come into existence if it weren’t for his contributions. Vaswani is one of the key contributors to the Transformer model, which eliminates the need for sequential processing in tasks involving sequences, relying solely on self-attention mechanisms. This model has greatly influenced the development of many other cutting-edge NLP models, such as BERT, GPT-2, GPT-3, GPT-3.5, and GPT-4.
The Transformer model was introduced in the paper Attention Is All You Need, during his time at Google. He also co-founded and was the chief scientist of Adept AI Labs which works towards useful general intelligence. However, he left the company last year and is working on his new stealth startup. AI enthusiasts are rightly disappointed that he did not make it to the TIME list.
Russlan Salakhutdinov
Often referred to as a hero of deep learning, Canadian AI researcher Ruslan Salakhutdinov specialises in probabilistic graphical models and large-scale optimisation, with Geoff Hinton as his doctoral advisor during PhD. He’s famous for creating Bayesian Program Learning, addressing one-shot learning, which mimics how humans grasp concepts from a single example. He served as a director of ML at Apple for sometime before joining Felix Smart in 2023 as a board director, a company that uses AI to take care for plants and animals. He is also a computer science professor at Carnegie Mellon University and has published over 42 machine learning papers since 2009, backed by funding from Google, Microsoft, and Samsung.
Daphne Koller
Another important AI expert who wasn’t mentioned on the TIME AI list is Israeli-American computer scientist Daphne Koller who is acclaimed for her groundbreaking contributions to machine learning and probabilistic models, as well as their application in the fields of biology and human health. However, she was featured as one of the 100 most influential people by TIME in 2013. But since then, she has made significant contributions in the field. Apart from that, she is also recognised for her efforts in democratising education as she also founded an online learning platform along with Andrew Ng who made it to the list.
Presently, Kaller leads Insitro, a biotech startup focusing on discovering improved medicines through the integration of machine learning and biology at scale. She played a pivotal role in advancing graphical models, focusing on both model structure and parameters, and merging statistical learning with relational modelling languages. Additionally, she developed fundamental techniques for inference and learning in temporal models, with her textbook on Probabilistic Graphical Models co-authored with Nir Friedman serving as a definitive reference in the field. In the realm of life sciences, Koller introduced Module Networks, harnessing modularity in gene regulation to create a powerful gene activity model.
Rana el Kaliouby
TIME magazine overlooked another significant individual, Rana el Kaliouby, the pioneering mind behind Emotion AI, who has fundamentally reshaped our interactions and exchanges within an ever more technology-driven global landscape. Driven by her upbringing in a technologically inclined family and inspired by Rosalind Picard’s book on Affective Computing, she infused AI with emotional intelligence. Through her work at MIT and the founding of Affectiva, she pioneered emotion technology, allowing computers to detect and respond to human emotions through facial expressions. This emotion recognition software holds a multitude of potential uses, spanning diverse fields such as linguistics and video content creation.
Check back with us as we discuss the remaining AI leaders and their contributions in the Part-2 of the story.
