AI has no time to replace you. It's busy winning the Nobel Prize - Investment Notes Issue 235

While we were still debating whether AI would replace humans, it has already won a laurels in the highest hall of science - the Nobel Prize.

In the 2024 Nobel Prize in Chemistry, AI emerged as a research method and was directly dedicated to achieving real - world applications. The laureates also included several young AI researchers at the forefront.

In the 2024 Nobel Prize in Physics, AI was the core and research direction. The laureate was also known as the "father of AI". The reason for winning the Physics Prize was more like borrowing physical principles in the exploration of AI.

In the 2025 Nobel Memorial Prize in Economic Sciences, the research results will be combined with AI to help people understand and predict the most important topic in today's human society - the economy in a more efficient way.

In the 2025 Nobel Prize in Physics, the research results will assist the development of AI, directly enhance AI computing power, and make more people's AI dreams come true.

When AI for Science becomes the mainstream, and countries around the world are promoting "Science AI platforms" and striving to involve AI in basic scientific research, comprehensive research such as AI - based material discovery, AI - based drug screening, and AI - based climate simulation will only become more common. There will also be more and more research results, laureates, and award - winning cases related to AI.

Is it a "mistake" of the Nobel Prize?

An AI expert won the Physics Prize

The 2024 Nobel Prizes clearly became a watershed in the AI era. The Physics Prize and the Chemistry Prize were respectively awarded to researchers in the field of artificial intelligence. This indicates that AI has moved from being a tool to science itself.

The Physics Prize was awarded to Hopfield and Hinton, while the Chemistry Prize was awarded to Hassabis and Jumper of DeepMind, and Baker of the University of Washington.

The paths of the two prizes have their own characteristics: The Physics Prize rewarded the establishment of the theoretical foundation of AI, while the Chemistry Prize rewarded the practical application of AI in science.

Let's first look at the Physics Prize. The Hopfield network (a neural network similar to the way the brain remembers) was proposed in 1982 and is one of the earliest artificial neural networks. Its core is "associative memory": given a fuzzy or incomplete input, the network can restore the closest complete pattern.

The reason for winning the Physics Prize is that Hopfield used physical tools to describe the cooperation between neurons and explained how the network self - corrects with "energy minimization". It was this physical analogy that made it possible for the first time to describe the theoretical framework of AI with equations and solve it through optimization.

Usually, the Nobel Prize rewards several outstanding scientists who have struggled in a theoretical context. They receive the honor because their research results are recognized, for example, in theoretical science or real - world applications, and have a huge impact on future generations. In other words, the laureates of the same session are more like multiple fruits on a vine. Hinton, the father of the Boltzmann machine, won the prize together with Hopfield.

Hinton further developed the idea of the Hopfield network and created the Boltzmann machine - a generative AI model capable of independently discovering data features. He used statistical physics methods to train the network, allowing the machine to learn data patterns from given examples, classify, and generate new samples. This is like finding common features such as "ears" and "whiskers" in many cat images and analyzing their relationship with cats. This idea directly gave birth to deep learning and laid the theoretical foundation for later convolutional neural networks and attention mechanisms.

Later, Hinton got another title: the father of deep learning.

When Hopfield and Hinton presented their research results, AI was not even called AI, let alone "deep learning". The Nobel Committee for Physics specifically emphasized that the research of Hopfield and Hinton laid the foundation for modern AI, enabling computers to independently discover data patterns and thus promoting the comprehensive development of AI. This is also the first time that AI research has won the Physics Prize. There has never been an "AI Prize" in history. AI researchers usually receive the Turing Award, the highest international award in the field of computer science.

Now let's look at the 2024 Nobel Prize in Chemistry. Different from the Physics Prize, it rewards the practical application of AI in science. Among the laureates, Baker's work belongs to traditional computational biology, designing proteins through the Rosetta system, while AlphaFold2 by Hassabis and Jumper is a pure AI achievement.

AlphaFold is a well - known name in the AI circle. It solved the protein folding problem that has puzzled scientists for 50 years: predicting the three - dimensional structure of proteins from amino acid sequences. Under traditional experimental methods, this process could take months to years, while AlphaFold2 can complete the prediction in a few minutes with an accuracy close to experimental results.

The Nobel Prize is always awarded for "past achievements". No one can win the prize in the same year they present their results. AlphaFold2 was released in 2020 and won the Nobel Prize in 2024. In the history of the Nobel Prize, it is rare that it only took 4 years from the release of the result to winning the prize, indicating that the result was fully verified. In the first two years after AlphaFold2 appeared, although it shocked the scientific community, it was still questioned. Starting from the third year, its accuracy was verified to be over 90% in thousands of laboratories. Then it began to be heavily relied on in fields such as pharmaceutical R & D and new material design, thus winning the favor of the Nobel Prize.

The 2024 Nobel Prize in Physics and the Nobel Prize in Chemistry both embraced AI, which actually dispelled many people's speculations: People used to think that AI could only be a tool, not a research direction, and could not be truly respected like a "scientist".

The "indirect" connection between the Nobel Prize and AI

The direct connection between the 2024 Nobel Prize in Physics and the Nobel Prize in Chemistry and AI actually caused a lot of controversy. The 2025 Nobel Prizes seemingly did not reward scientists who regarded AI as a research direction or core, but in fact, the Nobel Memorial Prize in Economic Sciences and the Nobel Prize in Physics have also quietly been marked with the imprint of AI.

The 2025 Nobel Memorial Prize in Economic Sciences was awarded to Mokyr, Aghion, and Howitt in recognition of their pioneering research in the theory of innovation - driven economic growth. Their research topic was to reveal how technological innovation promotes economic development, especially within the framework of "creative destruction": Old technologies are replaced by new ones, leading to an increase in productivity.

Mokyr focused on economic history research, while Aghion and Howitt developed theoretical models. However, their research results will directly provide a theoretical basis for AI applications. Even, we can say that their research results are aimed at enabling people to truly master, rather than succumb to, AI. Because the core technology regarded as driving "creative destruction" at present is none other than AI.

Although these scientists are concerned with the human economy, what they actually focus on the most is AI. After winning the prize, laureate Aghion immediately stated that he planned to use part of the prize money for AI research, exploring how AI can accelerate technological innovation and improve productivity, and dealing with employment or monopoly issues that AI may bring, so that people's AI dreams will not turn into nightmares.

The laureates of the 2025 Nobel Prize in Physics, Devoret, Martinis, and Clarke, hope that their results will help people realize the dream of enhancing AI computing power.

At first glance, their award - winning results have nothing to do with AI. Through superconducting circuit experiments, the three scientists proved that even a "macroscopic system" - a circuit composed of a large number of particles and can be held in the hand - can exhibit quantum mechanical effects, such as tunneling and energy quantization.

This breakthrough laid a physical foundation for controllable qubits (the smallest information unit of a quantum computer), and qubits are the core components of a quantum computer. A quantum computer is also a key platform for enhancing AI computing power and can outperform classical computers in specific tasks (i.e., what people call quantum supremacy). In other words, this discovery provides the potential for training large - scale models and solving high - complexity optimization problems.

Ultimately, this research is an important part of the quantum technology ecosystem in the AI era. In fact, human exploration of the microscopic world and pursuit of quantum computing are ultimately aimed at promoting AI.

It can be said that the 2025 Nobel Prizes still reflect the academic community's emphasis on AI. Or, we can think that the presence of AI cannot be ignored. More and more theories, applications, and basic scientific research will form a mutually supportive cycle with it.

The Nobel Prize "transformed" by AI

It can be said that the progress of AI has also enabled the Nobel Prize to achieve "self - breakthrough". Hassabis, the laureate of the 2024 Nobel Prize in Chemistry, is a doctor in neuroscience and AI, and Jumper's research direction is also machine learning/computational biology. They do not have a background in chemistry. Hopfield, the laureate of the Physics Prize, has a background in physics, while Hinton's research direction is AI/neural networks.

Hassabis, Jumper, and Hinton are typical experts in the field of AI, not the titans in the fields of physics and chemistry. Therefore, the Nobel Prize seems to be very "rebellious". Right after the prizes were awarded, there were many doubts on social media around the world:

"The two bigwigs only realized today that what they have been doing all their lives is actually physics."

"If computers can be counted as physics, then there are too many things that can be counted as physics!"

"Originally, the Chemistry Prize was half a Biology Prize (there is no Biology Prize in the Nobel Prizes). Now, is the Physics Prize also going to be split in half by computers?"

These doubts are understandable because AI researchers have their own award, the Turing Award. Moreover, Hinton, the laureate of the 2024 Physics Prize, won the Turing Award in 2019.

Under the influence of AI, the first innovation of the Nobel Prize is "cross - boundary". The second innovation is that the time required for scientists to receive the Nobel Prize from presenting their results has become shorter and shorter.