Researchers at the Massachusetts Institute of Technology (MIT) created the AI Physicist system, which is capable of generating theories about physical laws in fictional universes. This will allow AI to extrapolate its knowledge and predict the future.
Artificial intelligence is not yet able to recognize objects or situations, discarding irrelevant details. In other words, it does not know how to focus on a particular object. The reason is that AI at the current level of development is unable to determine what is necessary. For example, if you show it many photos of cats, where they will be in different environments, the system will not be able to identify them because of this difference.
MIT used a different approach. Researchers Tailin Wu and Max Tegmark have programmed four strategies in the machine learning algorithm that scientists use to generate theories about complex observations. They also added a method of small models. These models describe a certain subset of objects, and then a larger “theory of everything” is formed from them.
These are the techniques: divide and conquer (generation of multiple theories, each of which explains part of the overall picture), Occam's razor (using the simplest theory as much as possible without involving third-party entities), unification (combining theories) and lifelong learning (trying to apply theories to solve future problems). AI introduced a series of progressively more complex virtual environments with unusual and strange physical laws. The task of the machine was to predict the behavior of objects in these environments.
In order for the AI to determine how objects will move in two dimensions in these environments, it had to create his own physical theories. AI Physicist, as reported, was able to predict the behavior of the ball in an environment with different physical phenomena in more than 90% of cases, which is much higher than that of traditional machine learning systems.
It is assumed that in the future, AIs will be able to independently set tasks and conduct experiments, even in virtual space. This will allow scientists to better understand complex systems, as well as use artificial intelligence to predict climate change, the economy, and other systems with large amounts of data. As for science, such systems will surely find application in astronomy, physics, chemistry, and so on.