Researchers at OpenAI rival AnthropicAI are delving into the inner workings of their large language models (LLMs) to demystify the 'black box' nature of AI systems. This initiative, part of their Claude-3 research, aims to enhance the understanding of generative AI, potentially changing how these systems are perceived and utilized. By uncovering clues about the internal mechanics of LLMs, AnthropicAI hopes to prevent misuse and reduce potential threats. The research has revealed that turning certain features on and off can significantly alter the behavior of AI systems, providing insights into bias, safety, and autonomy concerns.
🚀 Accelerate! Check out @AnthropicAI's insane Claude-3 research; unlocking the inner workings of LLMs, offering potential solutions to bias, safety, and autonomy concerns. Mind-blowing stuff from @nlw https://t.co/nFuWJDRTnB
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AI’s Black Boxes Just Got a Little Less Mysterious🤯⚠️ -Researchers at @AnthropicAI uncover clues about the inner workings of LLMs -This can help prevent misuse & reduce potential threats -Found turning certain features on/off can change how AI systems behave #GenAI #Anthropic https://t.co/sJT8yqGfhQ
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Researchers at OpenAI rival @AnthropicAI are peering inside the black box of their model. It could change how we understand generative AI. Click to read: https://t.co/sFLPxu57Te
today in AI: 1/ Mapping the mind of a LLM You know how AI models are often seen as a black box? Well, @AnthropicAI does this crazy thing of looking inside them to understand what makes them tick