MIT researchers have developed a new method to help artificial intelligence (AI) systems conduct complex reasoning tasks in three areas including coding, strategic planning and robotics.
Large language models (LLMs), which include ChatGPT and Claude 3 Opus, process and generate text based on human input, known as “prompts.” These technologies have improved greatly in the last 18 months, but are constrained by their inability to understand context as well as humans or perform well in reasoning tasks, the researchers said.
But MIT scientists now claim to have cracked this problem by creating “a treasure trove” of natural language “abstractions” that could lead to more powerful AI models. Abstractions turn complex subjects into high-level characterizations and omit non-important information — which could help chatbots reason, learn, perceive, and represent knowledge just like humans.
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