My skepticism about scaling deep learning is shared by many old fashioned AI people, but it’s likely wrong. Perhaps there is a master algorithm hidden in the training data? Perhaps we can distill it? And if not, there are many ways in which a dumb AI can learn to improve itself.
AGI
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LLMs as Brute Force Path to AGI: Small vs Planetary Systems
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If LLMs turn out to be the brute force path to AGI, I expect we can create small (<<H100) AGI engines that derive most of what they need on the fly, and make use of interchangeable knowledge bases. But why use small special purpose systems when you can have a planetary mind?
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Big Data Approach to AGI: Memorization vs. Curious Learning
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My bias against the big data approach to AGI is fueled by how I observe my own learning. I always try to avoid memorization and focus on re-deriving, using, improving and integrating what I read. Memorizers do worse than curious explorers and experimenters.
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Deep Learning Insufficient for AGI: Meta-Behaviors and Epistemology
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I still suffer from the intuition that deep learning is the wrong approach. General intelligence cannot consist in learning to imitate all human behavior; there must be a small set of meta behaviors that lead to discovering epistemology, empirical learning, analytic thought.
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Statistical Text Models and AGI: Semantics Extraction Beyond Imitation
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I glimpsed during my work in Ian Witten‘s lab in the 1990ies that one can extract arbitrary semantics from pure statistical text models. I just never considered this to be very interesting, because I thought AGI would result from intelligent self improvement, not mere imitation.
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AI Models Evolving Beyond Memorization Through Reasoning
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I expected AI would become smarter than us before it knew very much. Current frontier models are idiot savant AI: less intelligent than competent humans, but they memorized basically everything. The models are now improving through reasoning, reinforcement learning and tool use.
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Rocket: Prompt-to-Product Engine Generates Deployable App in 6 Minutes
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Rocket is a prompt-to-product engine that doesn’t just generate code – it reasons through your idea like a dev team would. In 6 minutes, I had: Homepage
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West Must Out-Accelerate China in AI to Preserve Freedom
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If the CCP wins at AI, they own the future.
— Nathan Lands (@NathanLands) 12 juin 2025
They rewrite history and freedom becomes a thing of the past. Civil liberties, what's that?
The West and it's Allies must out-accelerate them in AI, energy, infrastructure, and space.
Nothing else matters. Period https://t.co/wlGeeSwPFdIf the CCP wins at AI, they own the future. They rewrite history and freedom becomes a thing of the past. Civil liberties, what's that? The West and it's Allies must out-accelerate them in AI, energy, infrastructure, and space. Nothing else matters. Period
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Parshin Shojaee discusses illusion of thinking on alphaXiv
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@ParshinShojaee is on alphaXiv to answer questions on The Illusion of Thinking! Join the discussion here: https://
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Pre-o1 Era: Reflecting on AI Model Evolution
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yep theres a lot to think about here. this was the pre-o1 era ofc