you may just be possessed by brainworms, you know
@plinz
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Neutrality Positioned Outside Center: Systemic Implications
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Neutrality is often not in the center but outside
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Grok’s Epistemological Challenges: Wikipedia Bias and First Principles
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Grok is using sources like Wikipedia, which are not always neutral (Wikipedia articles often get captured by activists when it comes to contested topics). First principles reasoning and sound epistemology are hard to achieve for now
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LLMs Are Context Sensitive Not Averaging Mechanisms
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LLMs are not averaging, they are context sensitive. All ideas that are sufficiently represented in the training data can be reproduced equally well, regardless of their relative prevalence.
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AI Political Neutrality: Examining Bias in Machine Learning Models
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If you believe that AI models cannot be politically neutral, the problem might be that you don't yet know how to be politically neutral yourself
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Brilliant Minds Across Different Universes Episodes
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Yes, they are successive episodes with some of the smartest people imaginable, each of them living in a different universe
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LLMs Tax Returns vs ASI Development Priorities
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Dwarkesh asking Sholto whether LLMs can do tax returns in the next couple of years and essentially getting nah we are too busy polishing the ASI
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Dwarkesh podcast guests debate divergent AI singularity and job market scenarios
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I love how Dwarkesh‘s guests alternatingly construct detailed scenarios of futures where singularities manifest in 2 or 30 years, followed by a world in which openAI does not interfere with the job market of tax attorneys unless Anthropic releases irresponsible improvements
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Formal Arguments Required for Large Model Limitation Claims
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I think that strong claims about the limits of large end-to-end trained models require a formal argument or decisive empirical support, because they go beyond what is scientifically known
