This study demonstrates that neural activity in the human brain aligns linearly with the internal contextual embeddings of speech and language within large language models (LLMs) as they process everyday conversations.
Scientists are exploring the capabilities of the DeepSeek-R1 AI model, released by a Chinese firm. This open and cost-effective model performs comparably to industry leaders in solving mathematical and scientific problems. Researchers are leveraging its accessibility to create custom models for specific disciplines, although it still struggles with some tasks.
Sakana AI introduces The AI Scientist, a system enabling foundation models like LLMs to perform scientific research independently, automating the entire research lifecycle.
The article discusses how machine learning is being used to calculate the macroscopic world that would emerge from string theory, a theory that posits the existence of tiny, invisible extra dimensions. These calculations have been difficult due to the enormous number of possibilities, but recent advances in artificial intelligence have made it possible to approximate the shapes of the Calabi-Yau manifolds, the objects that resemble loofahs and host quantum fields in string theory. The calculations have been able to reproduce the number of particles in the standard model, but not their specific masses or interactions. The long-term goal is to use these calculations to predict new physical phenomena beyond the standard model. The article also mentions that some physicists are skeptical of the usefulness of string theory and the role that machine learning will play in it.
