'Godfather of AI' notches Nobel win

The Nobel Prize in Physics goes to John Hopfield at Princeton and Geoffrey Hinton at the University of Toronto for their work on artificial neural networks. Their inspiration initially came from the desire to understand how the brain works. Hinton has been sharing fears about AI’s future development. Ok, let’s step back and look at the big picture. Reminding everyone that historically humans have not been good at predicting the implications of technologies. Don’t get me wrong, I believe our concerns are valid. But, we are not helpless, we have successfully put controls around the development of certain technologies and continue to innovate. We don’t need to stop. I believe the mystique around the development of AGI has been leveraged to get our attention. We are in control here, not the machines. Arthur C. Clarke once wrote that “any sufficiently advanced technology is indistinguishable from magic,” and we are having another moment of that with large language models and generative AI. A big debate is going on online about why they received the Nobel Prize in Physics. Is Neural Networks Physics? Something to think about #artificialintelligence #technology #innovation

The most interesting thing in tech: today the Nobel Prize in physics was awarded to two pioneers of AI, Geoffrey Hinton and John Hopfield. Hinton's work is more well-known, so I want to talk about one interesting element of Hopfield's work that was cited by the committee: the idea of associative memory, and the way that our brains take specific inputs and them to a web of related thoughts, images, and emotions. Imagine, for example, a smell that brings you right back to your childhood kitchen and lets you imagine and see everything in it. This is an idea that Hopfield worked to model with physics and that has since become an important part of modern AI.

What Nobel Prize for Physics- it’s awarded to the “Godfather of AI” together with another pioneer for their work on machine learning. American Professor John Hopfield, 91, is a professor at Princeton University in the US, and Prof Hinton, 76, is a professor at University of Toronto in Canada. Machine learning is key to artificial intelligence as it develops how a computer can train itself to generate information. Professor Hinton wasn’t ignoring potential risks of AI - eg he raised concerns about AI becoming too powerful or displacing jobs https://lnkd.in/eueFa56m #AI #machinelearning #NobelPrize

Congratulations to Canada’s very own Dr. Geoffrey E. Hinton — one of the “Godfathers of AI” — on winning the 2024 Nobel Prize in Physics. Geoffrey, we’re glad to have a mind like yours developing safe and responsible AI for the world.

We just witnessed history. An AI pioneer just won the Nobel Prize in Physics. Geoffrey Hinton, the "Godfather of AI," and John Hopfield received the Nobel Prize in Physics for their groundbreaking work on artificial neural networks. This isn't just a win for two brilliant minds. It's a shift in how we view technology's place in the world. Think about it: - A computer scientist winning in Physics - AI being recognized alongside quantum mechanics and relativity - Software officially joining the ranks of "hard science" This validation isn't just for Hinton and Hopfield. It's for every coder, every startup founder, every tech visionary who's been told their work isn't "real science." But here's the thing: as monumental as this is, it also made me question something: Why isn't there a Nobel Prize category specifically for Technology Innovation? Software and AI are reshaping everything from healthcare to climate science. They're solving problems and creating opportunities on a scale that rivals traditional scientific breakthroughs. Imagine a Nobel that celebrates: - Breakthroughs in quantum computing - Innovations in renewable energy tech - Advancements in biotech and personalized medicine A dedicated category that recognized these achievements would also inspire the next generation of tech innovators. As we celebrate Hinton and Hopfield, let's also push for greater recognition of tech's transformative power. The pioneers building our digital future deserve to stand alongside those revolutionizing physics, chemistry, and medicine. So you think it's time for a Nobel Prize in Technology Innovation? #AI #technology #nobelprize Emma W. Thorne , https://lnkd.in/eNmgirSv

“This years prize is about machines that learn” Congratulations to Prof. Hopfield and Prof. Hinton - and to the many, many researchers and scientists working to advance the field of AI every day. Building AI responsibly, with care for ethics and the environment is a core responsibility. The Nobel committee’s recognition of the importance of the field underscores this responsibility. If you’re working to enhance models or improve how to use them efficiently - you’re all a part of the next revolution. Sometimes it’s important to step back and see that we’re a part of something much, much bigger than us. #NobelPrize

This morning, Geoffrey Hinton was honored with a Nobel Prize for his exceptional contributions to AI for his pioneering work in neural nets, deep learning, and back propagation. Often called the father of AI, without his groundbreaking research, platforms like OpenAI and technologies like ChatGPT wouldn't exist today. In 2017, I had the privilege of meeting Geoff during a visit to the Toronto/Kitchener area, organized by Google. Alongside Ben Fowler (then leading Data Science at CarePredict, Inc.) it was truly inspiring to witness Geoff's insights firsthand. This experience served as an early validation of our innovative work in elder care with deep learning AI and led to us deploying our deep learning models to predict declines in health starting in 2017. Here's a throwback to a memorable lunch with Geoff in Toronto, where Ben (orange shirt) and I had the opportunity to engage with one of the most influential figures in the field.

When I was a young student learning about neural networks and backpropagation, I often thought that if there were a Nobel Prize category for Computer Science, Geoffrey Hinton would surely win it due to his groundbreaking contributions. And now, here it is! ?? This may spark some debate among physicists. However, considering the disruptions of AI and its impact on our lives, doesn't he deserve this recognition? The beauty of this achievement lies in the collaborative spirit of science. Hinton's work builds upon the foundations laid by physicists like John Hopfield, highlighting how interdisciplinary collaboration drives innovation. This Nobel Prize not only celebrates individual brilliance but also emphasizes the power of shared knowledge and collective advancement.

A physics nobel prize for a computer scientist - Geoffrey Hinton - is a remarkable moment. It's like Dylan getting the nobel prize for literature. If you still doubt if AI will impact life sciences research, I don't even know what to say to you. Biology has been dogma for too long. Data and AI will change that. We will be less reliant on individual genius and more on data driven guesses. Note, less reliant - domain heavy knowledge will always play a part. The best biologists and disease-experts will still be extremely valuable. What will change is that the idea that whatever we know of biology is in a book or paper will no longer be true. Papers are interpretations of data. Nuanced interpretations by experts who know the subject well. But they are not statements of truth. They are informed opinions. AI will enable asking questions that weren't always possible. It will speed up processes that have been too slow for too long. This is a watershed moment. Congratulations to the AI community!

Yesterday was a wonderful day, my favorite molecule to which I have been dedicating a great part of my professional life, RNA, was given value again ?? . Researchers Victor Ambros and Gary Ruvkun were awarded for their contribution to the discovery of miRNAs and their regulatory role in RNA. Today starts the day with a second piece of news that makes this week special: the Nobel Prize in Physics 2024 is awarded to John Hopfield and Geoffrey Hinton for the work on artificial intelligence (IA) that has been the basis for the development of ML and neural networks, my second favorite thing. ?? This work is the basis for many predictive models that live with all of us in our lives, but are a paradigm shift in many fields such as the pharmaceutical industry. ?ML, AI has come to change the status quo in this field. Helping professionals to make their processes more efficient and productive, to infer new information, explore new paths, offer new alternatives to reduce time for patients, and try to improve the characteristics of these drugs by incorporating features in predictive models that make them better and better, quickly and without spending years of research and money, something quite common in the pharmaceutical industry. Using technology to get novel drugs to the patient faster and better each time is a challenge and a responsibility. Relying on technology to walk this path is a help and an exciting challenge that can only be used to make things better. Ultimately working to improve people's lives. I am pleased about these two Nobel Prizes and grateful to have the possibility,?in my daily life,?to work with both technologies. siRNAs, miRNAs and AI ?? . At SYLENTIS today we are celebrating that these technologies are taking center stage in our daily lives, and we rely on them to try to make things better every day. Thanks to the laureates for their work for their contribution to the world and for giving us tools to other people to try to make this world a little better with small contributions. ??