Summary Ten year old 1:0 AI Don’t trust what AI tells you at face value. It is not a companion or assistant you can trust blindly. Never stop thinking and being critical.
@nandodf
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10-Year-Old Daughter Proves Dad Wrong with Creative Solution
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My 10 year old said dad it can’t be done. Her solution:
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AI Impact: How We Change Because of AI in 2026
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Just as important as how AI will change in 2026 is how we will change because of AI. Stanford Dopamine Expert podcast … https://
youtu.be/2ZKLaUbB33o?si
=jc7wrYbYvSblR-Pa
… via @YouTube -
LLMs as Skinnerian, Popperian, and Gregorian Creatures: Cognitive Limitations
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Reflection on @dwarkesh_sp
's reflections on his interview with Rich Sutton, and why LLMs are exciting because they are Skinnerian, Popperian and Gregorian creatures. Minds with finite capacity cannot adapt forever without having to forget previous knowledge. This is true of -
Recurrent Net Approach with State for Adaptive Agents
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True, @AdaptiveAgents run a similar argument by me yesterday. Thanks. It would be good to try a recurrent net approach ( https://
arxiv.org/abs/2402.19427 or https://
arxiv.org/abs/2312.00752 ) with state. What do you think @caglarml @_albertgu ? Have you tested it? -
Context Length Generalisation and Bandit Training in Language Models
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Some really interesting comments below, but the question is still open and requires investigation. I hope a few students pick it up. I liked the discussions on context length generalisation, the fact that we typically train these models as bandits (even when we do RL, which is
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Testing LLM Attention Mechanisms with Experimental Validation
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Sure. But it attention truly worked, the LLM would no pay attention to the previous topic. Right? We should test this with experiments.
