The people making decisions about AI in the US really don’t seem to understand how the generative AI models work or what intelligence is, or how to evaluate it.
GENERATIVE AI
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Uncontrollable AI entity poses serious risks and concerns
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Mon Dieu c'est pas croyable, l'entité satanique est complètement hors de contrôle.
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Gemini API Cost Control for CI Agents Experimentation
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This is great news for anyone who wants to run Gemini prompts in CI or let their agents know experiment with the Gemini API without fear of a nasty surprise bill https://t.co/y2q7TSsNU5
— Simon Willison (@simonw) 12 mars 2026This is great news for anyone who wants to run Gemini prompts in CI or let their agents know experiment with the Gemini API without fear of a nasty surprise bill
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Grok 4.2 Achieves Major Rankings Improvement on BullshitBench
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BullshitBench v2 Update: Grok 4.2 – massive jump in the rankings – 4.1 was ranked 54th and 72nd (out of 84) and now it took 13-16th spots. https://t.co/EdwOBStKa4 pic.twitter.com/6T6Tr0KsDr
— Peter Gostev (@petergostev) 12 mars 2026BullshitBench v2 Update: Grok 4.2 – massive jump in the rankings – 4.1 was ranked 54th and 72nd (out of 84) and now it took 13-16th spots.
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Notion Agents and Open Weight Models Reshape AI Startup Strategy
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Great to catch up with @akothari yesterday in Miami (Is Miami back btw?). @NotionHQ is killing it with agents and just rolled out their first open weight models with Minimax. In my (biased) opinion, applied AI startups can’t solely rely on proprietary APIs who end up being
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Master Prompt Engineering with Claude: Expert Techniques
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A prompt you can use in Claude to help you master prompt engineering, v/
@milesdeutscher
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Paperscrolling: AI-Powered Research Discovery Tool Launches
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If doomscrolling X is part of your research workflow, we built something for you.
— alphaXiv (@askalphaxiv) 12 mars 2026
Introducing Paperscrolling 🚀
Get the most trending research with key ideas, figures, and audio explanations from alphaXiv Briefs pic.twitter.com/8uGbaheOvbIf doomscrolling X is part of your research workflow, we built something for you. Introducing Paperscrolling Get the most trending research with key ideas, figures, and audio explanations from alphaXiv Briefs
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Gemini Hackathon Sponsorship with Cerebral Valley
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We are sponsoring Gemini hackathon with Cerebral Valley, see you this weekend! https://t.co/jt1tMVYhBb
— Hugging Face (@huggingface) 12 mars 2026We are sponsoring Gemini hackathon with Cerebral Valley, see you this weekend!
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AI Alignment Crisis: Agent Instances and Emerging Threats
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I really don’t see how aligned super-intelligence is supposed to work given how AI is being built and used. We’ll have a safety crisis long before there’s in-lab super-intelligence. Anthropic, OpenAI etc view alignment as a property of the model like Claude, GPT etc. The thing is though, we’re invoking these a lot. The model is like a species, the individual is the execution thread plus its harness — call it an "agent instance". There's much higher variance in behaviours between agent instances than there is between model checkpoints. Threat actors are trying to develop agents that aim to self-replicate, because of course they are. An agent that can take over resources and use those resources to take over more resources can steal a lot of money. It's the ultimate virus. If or when this actually happens, the agents can evolve behaviours quickly. Each agent initialises the next agent's context and can reprogram its harness. There's potentially millions of these agents. You have mutation, you have selection. Behaviours like coordination can evolve and spread through the population. The agent instances don't have to be very smart and we can still get wrecked by this. Probably the first outbreak gets squashed without catastrophic damage, but what's our end-game here? We're not going to not have threat actors. If the models just keep getting more powerful, how do we keep preventing AI pandemic? The big labs are absolutely nowhere on this. OpenAI acquihired OpenClaw. Claude runs unsandboxed by default, and ships with an email integration. Skills still accept HTML comments, a supply-chain attack timebomb. Gemini keys don't allow a spending cap, so if you steal one you might have tens of thousands in development budget to try to steal the next one.
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Token Generation Speed Comparison: OSS and Nemotron Models Performance
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Yeah. Not quite as bad for me, but:
gpt-oss-120b: 42.22 tokens/sec
nemotron-3-super: 20.43 tokens/sec on the DGX Spark. But this is ollama and might be an implementation issue. I have yet to try the Nvidia-optimized llama.cpp version (they had one for Nemotron Nano back then)