Is a 92% “honest”* AI really good enough? Or a disaster waiting to happen? —-
*”honest” is itself a misleading anthropomorphization of the kind Anthropic loves to promote. “Accurate” would be more accurate.
RESEARCH
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Is 92% Accurate AI Good Enough or Disaster?
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Benchmarking quantization levels with TurboQuant for best context fit
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Tried more quants (4-bit, 5-bit) on upstream llama.cpp Next up is benchmarking TurboQuant for the same quants The goal is finding the best quant that fits with the highest context in q8_0/turbo3 asymmetric
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Knowledge Graphs Transform Modern AI Applications
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Documents into Knowledge: Graphs in Modern AI https://
youtu.be/yyuVR-ML9X8 At the first World's Fair, @emileifrem
, CEO of @Neo4j
, gave one of the most well received @aiDotEngineer talks of all time. He's back now with the 2 year update — now that Context Graphs are cool again, -
Codex benchmarks models and finds optimal inference engine for your hardware
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The best use of Codex is to make it benchmark models for your hardware and fine you the best inference engine for your hardware stack and model of choice as up-to-date as of April 18, 2026
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Who Trains Llama 70B Today Insufficient Workload
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who trains llama 70B these days though. too much of a toy workload
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AI researchers debunked: when genius claims meet reality
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Every time people start thinking AI researchers are a bunch of geniuses an antidote pops up. https://t.co/NCr63cIhKS
— Pedro Domingos (@pmddomingos) 18 avril 2026Every time people start thinking AI researchers are a bunch of geniuses an antidote pops up.
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Blood Test Predicts Alzheimer’s Disease Up to 25 Years in Advance
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There is a sort of file drawer bias: AI benchmarks that don’t meaningfully benchmark performance are dropped, but mostly because they are either 0 or 100. The whole point of benchmarks is to measure something about AI performance. Verisimilitude is a different matter, though.
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Evidence for Mammograms and New Papers Beyond Current Research
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Having done a lot of work on measuring performance, I don’t think this is very common. There are very few tasks that AI can do where there is not an upward trajectory. You can find tasks that no AI can do, or where there is saturation, but otherwise you get improvement over time.
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AI Benefits Breast Cancer Screening: New Reports and Editorial
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This is far from an exhaustive list – look at my past tweets to find dozens more academics doing interesting work on the topic
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Iteration speed beats thinking quality for progress
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The quality of your thinking is a multiplier for the amount of progress you make at each iteration. But the dominant factor behind success is simply your iteration speed. Try more things and you win.