And, yes, our experiments used a mix of GPT-4 & GPT-4o (publishing takes awhile). I think we would see much larger results with more recent models, let alone recent agentic tools.
AI
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Technical challenges in stateful AI agents and memory management
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yeah they do cool stuff around memory. starting to think stateful goes beyond that to tracking changes in the agents capability, etc which I’m not sure if many memory tools do
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LLM traces masquent un planificateur myope
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“Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning” Reasoning models can write traces that look like real tree search, but this paper shows their decisions are mostly driven by shallow one-step evaluation. They extract search trees from LLM CoT in
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Architectural challenges in building AI agent loops
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agree. kinda feels like we’re tacking on memory, tools, traces, logs into agent loops but there should be an elegant way to combine them, also relying on crons or heartbeat loops also feels hack
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Complexity of state tracking in AI agents
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one thing that makes agents more complex is that they generally add capability over time which should also be tracked as part of the state
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AI and connectivity reshaping live sports experiences
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Live sports are quietly becoming one of the best examples of how AI and advanced connectivity are reshaping real-world experiences. At the PGA Championship, technologies behind the scenes are helping power faster broadcasts, smoother operations, and more interactive fan
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Critical Perspective on GPT Development and AI Capabilities
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What I am about to describe ain’t AGI; it’s a sign of a trillion dollar trainwreck. If I had told you in 2022 that the 2026 version of GPT (which by the way would only be GPT 5.5 and not GPT-6 or 7 like many people fantasized about) would still have strange quirks like inserting
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China’s fully automated AI port moves cargo without humans
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Fully #Automated: China’s #AI-Powered Port Moves Cargo Without Humans
— Ronald van Loon (@Ronald_vanLoon) 17 mai 2026
by @_fluxfeeds#ArtificialIntelligence #MachineLearning #ML #MI pic.twitter.com/pNEu6UX9EnFully #Automated: China’s #AI-Powered Port Moves Cargo Without Humans
by @_fluxfeeds #ArtificialIntelligence #MachineLearning #ML #MI -
Skill0: RL recipe for skill internalization by Meituan team
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That's so cool! The same team at @Meituan_LongCat wrote Skill0, where they propose an RL recipe for skill internalization.
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Seeking elegant primitives for implementing stateful AI agents
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stateful agents, decision traces, context graphs… talked about a lot, but has anyone seen an elegant primitive around how to actually implement?