Yes; I think the main reason that LLMs are so far behind our performance relative to the amount of data they get is that they don't regularize and integrate enough
RESEARCH
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Kurzweil’s AGI predictions mixed with flawed connectome immortality
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Kurzweil mixed bold but solid predictions (given enough compute, a neocognitron like architecture can achieve AGI before 2030) with dogshit (digitizing the connectome is a near term way to human immortality). But both looked like the same kind of scifi to non experts.
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LLMs’ text input narrows world model compared to human perception
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That's technically correct but also misleading. Our world model is a shadow of our perception, and the sheer amount of text going into LLMs is constraining this shadow more than the perceptual patterns a human brain can encounter in a lifetime of experience.
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AGI and ASI timeline forecast considered too aggressive
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AGI in 27 and then ASI in 28 is too aggressive forecast. Albeit AGI is getting closer
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Deep Learning imitates AI by mining human output for intelligence
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Technically we are not in an AI age, but in a Deep Learning age. Deep Learning is deep faking AI, (mostly) by imitating the patterns of human thought. That does not mean that Deep Learning is limited, but it is wasteful to dig through mountains of our output to find intelligence
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AI finds errors and updates grad school paper with new data
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The interaction between AI & past scholarly work is going to get weird. Here I gave GPT-5.5 Pro a copy of my first published paper from grad school & asked it to find errors and update it. It found new data, analyzed it, created reproducible files, extended the key argument…
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T-Rex introduces basis hand motions for tactile learning
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T-Rex introduces a new set of basis hand motions to learn tactile responses:
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Generative media break visual Turing test: hope for truce
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Sigh. Unfortunately, it will only get worse as generative media shatter the visual Turing test. I hope that internal quarrels between traditional and neural computer graphics will cease.
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DeepMind and Google AI merger leads to unhappy researchers leaving
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Merging DeepMind and Google AI was a double-edged sword. It helped Google catch up, but it made a lot of researchers unhappy – and they're leaving.
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Comparison of LLM, RAG, AIAgent, and MCP
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#LLM vs. RAG vs. #AIAgent vs. MCP
by @Python_Dv #GenerativeAI #ArtificialIntelligence #MachineLearning #ML