A mental model for working with coding agents is that they're blind squirrels running into a maze and bumping into walls. You must place the walls (verifiable constraints) strategically so that they end up in the general region you want them in.
LLMS
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AI agents approaching autonomous full analyses
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Cada vez queda menos para que los agentes de IA hagan análisis completos solos
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Addressing out-of-distribution detection in LLMs
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Why don’t LLM’s just tell you when you are asking a question / doing something that is out of distribution?
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ChatCPR AI Outperforms 911 Dispatchers in Simulation Study
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Now there's a ChatCPR that outperforms 911 dispatchers in simulation testing @JAMAInternalMed https://
jamanetwork.com/journals/jamai
nternalmedicine/fullarticle/2848650
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Models show consistent theory-of-mind failures
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Its a consistent theory-of-mind failure in models that are otherwise suprisingly good at theory-of-mind
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MiniMax Releases M2.7 Open-Weight LLM with Self-Evolution Capabilities
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💡 @MiniMax_AI M2.7 is an open-weight LLM built for serious dev work.
— SambaNova (@SambaNovaAI) 18 mai 2026
It’s the first in MiniMax’s M-series to “self-evolve” via its own training + eval loop (agent harness optimization). Designed for complex coding, multi-agent systems, and pro-grade workflows.
Learn more:… pic.twitter.com/BZJp8zgCLg@MiniMax_AI M2.7 is an open-weight LLM built for serious dev work. It’s the first in MiniMax’s M-series to “self-evolve” via its own training + eval loop (agent harness optimization). Designed for complex coding, multi-agent systems, and pro-grade workflows. Learn more:
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LLMs leaking irrelevant conversation history in outputs
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One thing to watch for with Claude & GPT is that the models expose too much irrelevant history in their outputs. Slides are given footers saying things like "Better, more targeted version" if you asked for a better version, documents make references to how they are improved, etc
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Blind ambition of AI agents can cause digital disasters
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Blind ambition: #AIAgents can turn tasks into #Digital disasters
by David Danelski, University of California @TechXplore_com Learn more: https://
bit.ly/4935nbf #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
Analyzing LLM tokenization and cognitive competence
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Ils peuvent faire des jeux de mots: "penser" au niveau du token n'empêche pas de maîtriser un ensemble plus large, tout comme écrire lettre par lettre ne vous empêcherait pas d'écrire tout un livre. Le problème est davantage un problème de compétences mais la compétence des LLM
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Discussion on Neuro-Symbolic AI and LLM Integration in Autonomous Systems
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you need both for optimal function; that’s the claim i have been making for 30 years. neuro+symbolic. as a point of fact though, most of waymo’s LLM stuff at least as of last summer was still experimental. i am not actually sure how much lift they are getting from LLMs in