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Is AI actually starting to ‘get smarter’?! The latest research from MIT indicates that the internal structure of large language models (LLMs) astonishingly resembles that of the human brain! This study utilized sparse autoencoder techniques to conduct an in-depth analysis of the activation space of LLMs, revealing three hierarchical structural features that are truly remarkable: first, at the microscopic level, researchers discovered the existence of structures akin to ‘crystals’. The surfaces of these ‘crystals’ are composed of parallelograms or trapezoids, similar to familiar lexical analogies such as ‘man:’

As AI technology rapidly advances, the challenges of data acquisition are becoming increasingly prominent. Research from institutions like MIT reveals that open-source datasets such as C4, RefineWeb, and Dolma are facing stricter licensing agreements from the websites they scrape, posing significant challenges for AI training and academic research. The study found that even major AI companies like OpenAI are subject to strict limitations due to r....

["MIT research found that multi-agent debates can significantly improve the accuracy and reasoning abilities of AI models.", "The debate method reduces hallucinations and helps improve the model's responsiveness.", "Multiple AI systems debating answers to problems are more accurate than a single system.", "This method can be used for collaborative work among different language models to improve output.", "These research findings provide new insights for the AI field, enhancing the authenticity and reasoning capabilities of language models."]

Researchers at MIT have developed an AI technology that enables robots to manipulate objects using their entire hand rather than just their fingertips. This technology can reduce energy consumption and costs, allowing factories to employ mobile robots for object manipulation. Although it is still in the early stages, this technology holds promise for enhancing the operational capabilities of robots.