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Tag: Large Language Model Limitations

Apple’s AI Research: Unveiling Limitations and Guiding Responsible AI Implementation in Business

Apple’s AI Research: Unveiling Limitations and Guiding Responsible AI Implementation in Business

Apple’s AI Research: Unveiling Limitations and Guiding Responsible AI Implementation in Business A recent Apple research paper, titled “The Illusion of Thinking,” has ignited a crucial discussion within the AI community regarding the limitations of Large Reasoning Models (LRMs). This study reveals a phenomenon termed “accuracy collapse,” where advanced models like GPT-4, DeepSeek, and Claude Sonnet fail dramatically when confronted with increasingly complex tasks. This finding challenges the prevailing assumption that simply increasing processing power, data volume, or tokens will…

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Apple Researchers Challenge the “Reasoning” Capabilities of Large Language Models

Apple Researchers Challenge the “Reasoning” Capabilities of Large Language Models

Apple Researchers Challenge the “Reasoning” Capabilities of Large Language Models A recent research paper from Apple casts doubt on the widely touted “reasoning” abilities of leading large language models (LLMs). The study, authored by a team of Apple’s machine learning experts including Samy Bengio, Director of Artificial Intelligence and Machine Learning Research, challenges the claims made by companies like OpenAI, Anthropic, and Google regarding the advanced reasoning capabilities of models such as OpenAI’s GPT-3, Anthropic’s Claude 3.7, and Google’s Gemini….

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