100%, hallucinations are baked in (as I have been saying since 2001) and that is why basically no LLM company afford to operate in Germany now. We need a better technology.
MACHINE LEARNING
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Gary Marcus’ 2024 prediction: LLMs commodity, no AGI, profits squeezed
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Me, 2024. LLMs will be commodity; (except for Nvdia) profits will be hard to squeeze out. Techbros: Shut up, Gary. GPT-5 is gonna be AGI. Today: LLMs are commodity; (except for Nvidia) profits have been hard to squeeze out. (Also, still no AGI.* *per definitions generally
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Training an open source AI model for construction?
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Should we try to train an open source AI model for construction? We obviously have interesting datasets with HF, MLintern, transformers, trl…
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Tori agent uses SpaceXAI data for market sentiment analysis
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Read more about how Tori, eToro's agent, leverages models and real-time data from SpaceXAI to help consumers analyze market sentiment https://
x.ai/news/grok-etoro -
Hierarchies of smart models auditing cheaper ones
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"Switch to a cheaper model to save money" is a problem because cheaper models are worse (maybe they are good enough for a particular purpose, but still worse). More often a better approach is hierarchies of models, with smart models are orchestrators and auditors of cheap ones.
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Gemma Challenge: Google and Hugging Face for Open-Source AI
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Announcing the Gemma challenge!
— clem 🤗 (@ClementDelangue) 10 juin 2026
Google, Hugging Face, and the open-source AI community choose to empower AI builders rather than sabotage them.
Fun to see the Hub becoming the platform where agents collaborate, just as it became the platform where humans collaborate.… https://t.co/b8Kd6kPCWA pic.twitter.com/FeQKqEz2htLet's announce the Gemma Challenge! Google, Hugging Face, and the open-source AI community choose to empower AI creators rather than sabotage them. Fun to see the Hub become the platform where agents collaborate, just as it became the platform where
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Neural Operators advance from fluid dynamics to weather and fusion
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This is something I have been emphasizing since we started our work on Neural Operators. We very quickly went from simple fluid dynamics benchmarks to hard problems like building the first high-resolution AI-weather model, FourCastNet, and modeling turbulence in nuclear fusion.
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Claude Fable 5’s strongest result: rejecting the wrong metric
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Claude Fable 5’s strongest result was not writing more code. It was rejecting the wrong metric. We tested it on 3 ML tasks:
> Perfect churn validation was leakage
> Drift was real, but not the root cause
> Churn AUC was the wrong target for retention offers The hard one: Fable -
Cognitive skills in AI for adaptive strategic impact
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The shift is recognizing that integrating cognitive skills into AI isn't just about capability—it's about creating systems that can adapt and learn in context. As more organizations grasp this, we'll see AI with more strategic impact.
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AI’s Impact on Social Sciences: Ruin or Revolution?
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Will #AI ruin the social sciences — or revolutionize them?
by David Adam @Nature Learn more: https://
bit.ly/4dYpk4k #LLM #ArtificialIntelligence #MachineLearning #AI