This came during the "Artificial Intelligence Science: Is Artificial Intelligence Capable of Discovery?" forum, which was held as part of the World Summit of Scientists , which kicked off on Sunday in conjunction with the World Government Summit .
The forum was attended by Professor Tony Fan-Cheung Chan, former President of King Abdullah University of Science and Technology; Professor Yuri Nesterov, 2023 World Association of Computer Science Laureates Award winner, Research Professor at Corvinus University Budapest; Professor Omar Yaghi, 2025 Nobel Laureate in Chemistry, Professor of Chemistry at the University of California, Berkeley; Professor Jack Dongarra, 2021 Turing Award winner, Professor Emeritus at the University of Tennessee, Newxville; Professor Robert Tarjan, 1986 Alan Turing Award winner, Distinguished Professor of Computer Science at Princeton University; and Professor Arieh Warshel, 2013 Nobel Laureate in Chemistry and Distinguished Professor of Chemistry at the University of Southern California.
The participants stressed that artificial intelligence is a powerful tool to support scientific research , such as accelerating high-performance computing, discovering new models in chemistry, and simulating complex processes, but it remains limited in its ability to independently develop groundbreaking ideas or theories.
They pointed to the challenges related to the accuracy of information produced by artificial intelligence and its high energy consumption compared to the human brain.
They emphasized that artificial intelligence can be an effective assistant in scientific discoveries and solving complex problems, but it still depends on human expertise to guide it towards real innovation and achieving major discoveries.
In his opening remarks, Professor Tony Van stressed that artificial intelligence has a growing ability to support discovery and innovation, noting that the Nobel Prize in Chemistry was recently awarded to scientists who developed the artificial intelligence tool “Alpha Fold,” which works to predict protein structures, thus contributing to opening new horizons in scientific research and accelerating the discovery of drugs and treatments that will transform human lives.
He explained that artificial intelligence-based technologies have become an essential element of modern scientific research in multiple fields in our current era, especially in the context of the advanced integration of physics, mathematics, computer science, and neuroscience.
Tony added that it does not go so far as to replace scientists who change scientific concepts, citing the question of whether artificial intelligence could discover the general theory of relativity or quantum mechanics on its own.
In a keynote address, Professor Jack Dongarra explained the relationship between high-performance computing and artificial intelligence, saying, "My work in developing algorithms and software is based on theory and experimentation. Today we see that artificial intelligence is enhancing computing very rapidly. In weather forecasting modeling, artificial intelligence can provide 10-day forecasts in seconds instead of hours, and with higher accuracy than traditional numerical methods.
In a keynote address, Professor Robert Tarjan presented his critical view on what he called the "hallucination" of artificial intelligence tools, explaining that these systems may produce inaccurate or unreliable information. He added: "The organizers at one event prepared a resume for me using ChatGPT , and gave me two awards that I never received. He asked: Can artificial intelligence explore problems on its own? Can it invent general relativity or quantum mechanics on its own? I think these questions are still up for debate," as reported by the Emirates News Agency (WAM).
In the same context, Professor Arieh Warshel presented his experiences in integrating physics simulation with artificial intelligence in a keynote address during the forum, noting that he had tried in his field to study the relationship between physics- based simulation and artificial intelligence by studying the design of enzymes through simulation, but he did not get good enough results.
He noted that, out of desperation, he turned to artificial intelligence, using "maximum entropy," and was surprised by what he called "a clear achievement of artificial intelligence" that helped him find an amazing correlation with the catalytic efficiency of enzymes, and enabled him to predict an enzyme faster than natural evolution had done. He said that in other cases, such as studying heart disease, traditional physical methods were more successful than relying on artificial intelligence.
For his part, Professor Yuri Nesterov, in a keynote address, stressed the need to create a "virtual reality" for artificial intelligence, saying: "We are at the beginning of the process of learning how to do this efficiently. Artificial intelligence needs two things: the first is virtual reality, which is a huge database, and the second is an AI unit capable of making decisions. Humans get the surrounding reality for free, but artificial intelligence is very expensive. I believe that artificial intelligence has great creative power; it can discover new connections and structures, but its conclusions only relate to the (model) of the thing and not the real thing itself. If the model is correct, the result is logical, otherwise it is nonsense."
Professor Omar Yaghi gave a practical presentation on "Artificial Intelligence Chemistry," describing it as "amazing." He said that artificial intelligence was able to form new chemical structures and molecules, resulting in the development of water harvesting technologies from the air.
Yaghi continued, "This took me 35 years to come up with, which makes the speed of artificial intelligence in accelerating the discovery exciting for me."
In a related context, Professor Tony Fan-Cheung Chan moderated a panel discussion that discussed the role of artificial intelligence in scientific discovery .
Dr. Jayant Haristha, a senior professor of computer science and automation at the Indian Institute of Science, emphasized during the session that artificial intelligence can uncover a hidden relationship between "graph theory" and "machine learning," but the original ideas in each field are human-made.
Dr. Amir Goharshadi, a 2025 European Research Council grant recipient and associate professor of computer science at Oxford University, pointed out that what caught his attention was the question of the fundamental limits of what artificial intelligence or machine learning can accomplish. He explained that there are problems that are not algorithmically solvable, and therefore AI systems will not be able to solve them. He said: “We often see people on the X platform showing a picture or video and asking: Is this real or fake? Often, an intelligent system gives them inaccurate answers, which illustrates a possible limit to the capabilities of artificial intelligence.”
Dr. Hisham Omran, winner of the 2023 UNESCO-Fozan International Prize for Artificial Intelligence to Promote Young Scientists in Science, Technology, Engineering and Mathematics and Associate Professor of Electronics and Communications Engineering at Ain Shams University in Egypt, said: “We all agree that artificial intelligence is a powerful tool that has changed most aspects of our lives, and it serves as an effective assistant to scientists, but we must distinguish between ordinary science and revolutionary science,” noting that artificial intelligence is able to solve puzzles within the prevailing framework, but it is unable to think outside of this framework.
Imran concluded by saying that "artificial intelligence systems face enormous challenges in consuming electricity , to the point of putting pressure on power grids, and therefore comparing artificial intelligence to the human brain remains an unfair comparison due to this huge difference in energy efficiency."
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