The contributions made by two pioneers in the world of AI were acknowledged at this year’s Nobel Prize Awards.
Geoffrey Hinton and John Hopfield were rewarded for setting the groundwork of Large Language Models and Generative AI. They were also hailed for their massive contributions in this domain, linked to the world of physics.
Arising from the University of Toronto, Geoffrey Hinton was given the award for all his work in the field of backpropagation. Today, he’s known as the godfather of AI and also made the news last year for his great contributions.
Many call him the godfather of AI who used to work for Google in the past. He quit in 2023 as he felt he couldn’t speak more openly against the risks that AI comes with. This is the technology that he spent a lot of time making.
Backpropagation is a technique that dates back to the 80s and is a concept that allows algorithms to learn. You can think of it like a three-step process comprising of noticing errors, figuring out reasons why, and improving. In the end, thousands of pictures are under review and this robot gets better at finding the correct answer. So this is how a computer learns.
On the other hand, the other big winner at this year’s event was John Hopfield who came up with the concept of associative memory. He came up with computer memory that is similar to the human mind. It’s quite like linking the dots of information.
The reason why this concept is so famous has to do with how it can withstand unclear information. So the perfect example is trying to decipher noise in a crowded room full of people. Hopfield tried to ensure computers could recall data in a way that human minds could. So he designed software that could recognize patterns and fill in algorithms.
Both these mega contributions have given rise to the world of AI as can see it today. The honor came with a mega $1M cheque. The award is a prestigious honor that includes accomplishments related to the world of science, health, literature, economics, physics, and peace.
Image: Nobel Prize / Niklas Elmehed
Read next: Researchers Identify Key Thinking Patterns Behind Excessive Social Media Usage
Geoffrey Hinton and John Hopfield were rewarded for setting the groundwork of Large Language Models and Generative AI. They were also hailed for their massive contributions in this domain, linked to the world of physics.
Arising from the University of Toronto, Geoffrey Hinton was given the award for all his work in the field of backpropagation. Today, he’s known as the godfather of AI and also made the news last year for his great contributions.
Many call him the godfather of AI who used to work for Google in the past. He quit in 2023 as he felt he couldn’t speak more openly against the risks that AI comes with. This is the technology that he spent a lot of time making.
Backpropagation is a technique that dates back to the 80s and is a concept that allows algorithms to learn. You can think of it like a three-step process comprising of noticing errors, figuring out reasons why, and improving. In the end, thousands of pictures are under review and this robot gets better at finding the correct answer. So this is how a computer learns.
On the other hand, the other big winner at this year’s event was John Hopfield who came up with the concept of associative memory. He came up with computer memory that is similar to the human mind. It’s quite like linking the dots of information.
The reason why this concept is so famous has to do with how it can withstand unclear information. So the perfect example is trying to decipher noise in a crowded room full of people. Hopfield tried to ensure computers could recall data in a way that human minds could. So he designed software that could recognize patterns and fill in algorithms.
Both these mega contributions have given rise to the world of AI as can see it today. The honor came with a mega $1M cheque. The award is a prestigious honor that includes accomplishments related to the world of science, health, literature, economics, physics, and peace.
Read next: Researchers Identify Key Thinking Patterns Behind Excessive Social Media Usage
