The Godfather of AI, Geoffrey Hinton, has won the 2024 Nobel Prize in Physics. Obviously, the tech world is abuzz with discussions about the AI professor known for his work in deep learning, and his work in physics. However, moving on from the massive win for Hinton and the AI/ML ecosystem, we see this also as a new beginning for the future of AI and its investments.
Hinton achieved the award for developing the ‘Boltzmann machine’, a neural network model inspired by statistical physics. This model allows neural networks to self-learn patterns from data by modelling systems with interacting nodes, mimicking how the brain processes and categorises information.
Apart from this, David Baker, an American biochemist and computational biologist, and Demis Hassabis and John M Jumper, two Google DeepMind scientists, have been awarded the Nobel Prize in Chemistry 2024 by The Royal Swedish Academy of Sciences.
Baker received the award for ‘computational protein design’ and the other two shared jointly by Hassabis and Jumper for ‘protein structure prediction.’ The latter two have successfully utilised AI to predict the structure of almost all known proteins. In 2020, Hassabis and Jumper presented an AI model called AlphaFold2.
These awards, when considered for the healthcare industry, are revolutionary in showcasing the impact that AI can have on the medical field.
When someone asked ChatGPT if Hinton would ever be able to land a Nobel Prize in Physics, it replied that it is not possible at all since physics is not the same as AI. But it has been proven completely wrong.
Traditionally, the Nobel Prize in Physics has been reserved for discoveries that illuminate the physical world. Hinton’s win, however, highlights how deeply AI is now intertwined with our understanding of the universe and how neural networks—rooted in concepts borrowed from statistical mechanics—are driving forward both scientific inquiry and technological progress.
“AI is truly mainstream,” commented Debarghya Deedy Das, acknowledging that the person who wrote seminal computer science papers for ML, has won the Nobel Prize for Physics.
Meanwhile, Hinton was “flabbergasted” about being awarded the prize. “I’m in a cheap hotel in California which doesn’t have a good internet or phone connection. I was going to have an MRI scan today but I’ll have to cancel that,” Hinton told the press conference.
What Does It Mean for India?
Vishnu Vardhan, the founder of SML and creator of Hanooman AI, told AIM that the Physics Nobel for an AI scientist is coming of age for AI. “Today, AI is no longer an unknown black box but a mainstream science which is proven at the fundamental level. This is huge as AI will now be used with a lot more confidence as it is recognised as fundamental science than just another computer algorithm.”
Vardhan added that this will pave the way for India to use AI to solve many of its unique challenges from agricultural production and access to education and universal healthcare. “This will also bring in a lot more research funding and collaboration at the global level. A great day for the AI community to be recognised as mainstream science,” he added.
Subbarao Kambhampati sounded worried about the plight of the “desi CS folk”. Now, with this Nobel Prize, they will have to deal with Nobel expectations as well. “Bitiya, tu bhi paa sakte ho, na? Kuch zor se kaam karo…” he posted on X.
“This Nobel prize is a beacon of inspiration for everyone in the field of AI,” Ankush Sabharwal, CEO of CoRover, told AIM. “Their efforts have opened the door for AI systems that help people make judgments more quickly and accurately. To ensure that these technologies are really human-centric, it is more important than ever to develop AI that understands human emotions and behaviour,” he added.
The Risk Factor
Hinton has been very vocal about the dangers of AI. He compares the potential risks of AI to the creation of the atomic bomb during World War II, emphasising the dangers of profit-driven AI development that could result in AI-generated content surpassing human-produced content and jeopardising our survival.
After winning the award, Hinton also said that he is proud that Ilya Sutskever, one of Hinton’s students, fired Sam Altman from OpenAI as Altman is not concerned about AI safety at all. Because of this, some people have even claimed that Hinton got the award mostly because he has been siding with the people who promote ‘AI doomerism‘.
On the other hand, some even call it the promotion of ethical AI, as Hinton proposes a slow and responsible approach to building AI. “A large language model has a trillion weights. You have 100 trillion weights. Even if you use 10% of that, you have 10 trillion weights,” said Hinton. He adds that an LLM in its trillion weights knows thousands of times more than we do.
“It’s got much more knowledge and that’s partly because it has seen much more data,” he explained in his lecture at Oxford University, saying that it might also be because it has much better learning algorithms, something humans will never be able to achieve. “You have got crazily more parameters than you have got experiences. Our brain is optimised for not having many experiences.”
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