This is publication bias inherited at full scale. Models learned from the sliver of science that worked and almost none of what didn't.
DATA
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Claude’s training data may explain cleaner iOS work
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Could be training data. Whatever Claude saw more of, iOS work seems to land cleaner.
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Post about ideasai.com website generation for satellite AI crop prediction
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Yes, this is http://
ideasai.com mostly 😀 The webite generation: https://
ideasai.com/idea/a-platfor
m-that-uses-satellite-imagery-and-ai-to-predict-cro-48801/build
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AI writes site that curates 40,000 daily posts
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AI wrote every word on my site that reads 40,000 posts a day here on X and picks the best. It's pretty good: https://
alignednews.com/ai While I agree with you, there is some reason to have AI write. I can't read 40,000 posts a day. Can you? -
Benchmark lets AI agents curate own training data without humans
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What if an AI agent could curate its own training data—without human hand-holding? Researchers from Virginia Tech, UIUC, UW-Madison, and UC Berkeley present CURATION-BENCH, a benchmark that gives generalist coding agents command-line access to inspect, implement, test, and
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Researchers propose CODA to keep data on chip longer for AI training
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Can AI training be fixed by keeping data on the chip longer? Researchers from MIT, Princeton, Together AI, and Meta introduce CODA — a new way to rewrite Transformer building blocks as GEMM-plus-epilogue programs. Instead of moving large intermediate tensors back and forth to
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GenAI ROI positive but Bain report opaque on metrics
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There are lots of issues with GenAI implementations but surveys seem to suggest broad positive ROI. Data & stories about AI failures are real and useful but need to be clearer about what they are measuring. The Bain report is super odd & opaque about that. https://
bain.com/insights/your-
ai-budget-is-growing-your-returns-arent-heres-why/
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Prior ML data issues could hinder AI investment, citing fake MIT study
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I actually read this & it is super weird, it appears to be an argument that prior machine learning systems (not generative AI) did not generate savings due to data issues so that will lead to a lack of investment into current AI systems Also it cites the mostly fake “MIT study”
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Step-by-step LLM engineering projects roadmap
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Step-By-Step LLM Engineering Projects Roadmap – Build a tokenizer
– Learn embeddings
– Implement RoPE / ALiBi
– Hand-wire attention
– Build MHA
– Build a Transformer block
– Train a mini-former
– Compare objectives
– Build sampling
– Speculative decoding
– KV cache
– MQA / GQA / -
BS Fuji Prime News: SNS Criticism AI Analysis – Aguko, Minemura, Ishii Discussion
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[BS Fuji Prime News]
AI Analysis of SNS Criticism Against Japan Aguko Tomoko × Minemura Kenji × Ishii Junya Broadcast on 2026/6/3 Front Part: https://
youtu.be/oN543zF6mVU
Back Part: https://
youtu.be/EEx7gkZx0ac