half the joke is that ChatGPT made it
RESEARCH
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Gemini Pro 3.1 Capabilities vs. App Interface: A Curious Discrepancy
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Alex Karp now sounding like @garymarcus.
— Gary Marcus (@GaryMarcus) 5 mai 2026
Sooner or later, everyone figures it out. https://t.co/6OqhRN46bmAlex Karp now sounding like @garymarcus
. Sooner or later, everyone figures it out. -
Scholars Across Disciplines Researching AI and Work
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no, LeCun consistently steals and some of us keep pointing it out.
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AI Diagnosis: Experimental Success vs. Real-World Challenges
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1. LLMs don’t work on their own; they need neurosymbolic harnesses, which is more or less what I send all along.
2. Hundreds of times I have said that LLMs are unreliable and that is the problem, not their power per se. But I guess you can’t or won’t read. So blocked. -
Elsevier SVP on the Right AI Tool for Researchers
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What does ‘the right AI tool’ for researchers look like? Maxim Khan, SVP for Academic and Government Solutions, Elsevier, answers the question. https://
bit.ly/4n7oxSR #AI #Research #Researchers -
New Book: Agentic Architectural Patterns for Multi-Agent Systems, GenAI, RAG, and LLMOps
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5- release from @PacktDataML at http://
amzn.to/3MaHy8T "Agentic Architectural Patterns for Building Multi-Agent Systems: Proven design patterns and practices for GenAI, agents, RAG, LLMOps, and enterprise-scale AI systems" Contents:
GenAI in the Enterprise: Landscape, -
Funding R&D for AI Model Benchmarking
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It would also be useful for funding R&D into benchmarking models, which is currently mostly done by the labs themselves right now.
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NIST Public AI Ability Tests as Independent Evaluator
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In addition to the CAISI evaluation, it would be useful if NIST conducted public tests of AI abilities as an independent evaluator – though those obviously should not be pre-release tests & can be done when models are public. Independent testing is important & getting expensive.
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New Microsoft Research Paper on Long-Horizon Agent Generalization
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NEW paper from Microsoft Research. Nice study on long-horizon agent generalization. (bookmark it) The team runs a study where the only variable is task horizon length. They use the same decision rules, reasoning structure but different sequence length to the goal. The main
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SubQ vs Opus 4.6: massive context, cheaper, faster, threatens Claude
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Si los números de SubQ son reales, Claude tiene un problema serio.
— Nico (@nicos_ai) 5 mai 2026
SubQ vs Opus 4.6:
→ 12M tokens de contexto (Claude se rompe pasados los 200k)
→ 10 veces más barato
→ 52 veces más rápido que FlashAttention
Si esto es así, van a dejar a Claude obsoleto.
Tocará probarlo en… https://t.co/s7QbxAWn1RIf SubQ's numbers are real, Claude has a serious problem.
SubQ vs Opus 4.6:
→ 12M context tokens (Claude breaks beyond 200k)
→ 10x cheaper
→ 52x faster than FlashAttention
If this is the case, they will make Claude obsolete.
Will have to test it on