Prediction is not bounded by the intelligence of the process that produces the thing to predict. Eg, somewhere on the Internet are tuples in that order.
RESEARCH
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Gary Marcus Five Critical Points for Elon Musk
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sketched here: https://
garymarcus.substack.com/p/dear-elon-mu
sk-here-are-five-things
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Evolution’s Optimization Process and Reality’s Infinite Degrees of Freedom
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Evolution's outer optimization process was aimed at "inclusive genetic fitness", a simple concept that humans never even formed except by postmortem reconstruction millions of years later. There's vastly more degrees of freedom in "where to steer reality" than "predicting
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Humans Make Mistakes Too: LLMs vs Human Error Discussion
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“but humans make mistakes, too” is so common a reply, I have written a discussion comparing humans and LLMs:
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Human Cognitive Errors vs LLM Hallucinations Explained
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So many people are confused about the relation between human cognitive errors and LLM hallucinations that I wrote this short explainer: Humans say things that aren't true for many different reasons
• Sometimes they lie
• Sometimes they misremember things
• Sometimes they fail -
Multimodal World Models: The Future of Grounded AI Systems
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How to attain Multimodal World Models is a great open question in AI. The solutions will likely lead to more grounded models that interact better with people and make better physics predictions. Hopefully, they will enable scientific generalisation, but this too I feel is an open
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State Space Models Survey: Analysis and Applications
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10/ A Survey on State Space Models – a survey paper on state space models (SSMs) with experimental comparison and analysis; it reviews current SSMs, improvements compared to alternatives, challenges, and their applications.
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LLM In-Context Recall Depends on Prompt Formulation
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9/ LLM In-Context Recall is Prompt Dependent – finds that a model's recall performance is significantly affected by small changes in the prompt; the interplay between prompt content and training data can degrade the response quality.
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RAG Reduces Hallucination in LLM Structured Outputs
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7/ Reducing Hallucination in Structured Outputs via RAG – shows that RAG can enable deploying powerful LLM-powered systems in limited-resource settings while mitigating issues like hallucination and increasing the reliability of outputs.
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State-Space Models Express Power Limited to TC0 Complexity
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6/ The Illusion of State in State-Space Models – investigates the expressive power of state space models (SSMs) and reveals that it is limited similar to transformers in that SSMs cannot express computation outside the complexity class 𝖳𝖢^0…