GLM 5.1 took a 3rd spot on LM Code Arena, surpassing Claude Sonnet 4.6 and GPT-5.4. It has never been like that before
RESEARCH
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LLM Simulation Path Outperforms Neuroscience Adjacent Philosophy
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These neuroscience adjacent ideas are exotic armchair philosophy when the LLM simulation path will work really well and so much faster and it's not even remotely a contest.
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Brain Upload via LLM Simulators: Near-term Tractable Alternative
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Yes it's the tractable form of brain upload. There's a ton of scifi on brain uploads that requires way too exotic tech (scanning and simulating brains etc), when we're about to get a lossy and approximate version of that *a lot* sooner via LLM simulators. You can easily imagine a
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Top 9 Algorithms Powering Modern World Technology
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Top 9 #Algorithms that Power the Modern World
by @Python_Dv #AI #DataStructures #ArtificialIntelligence -
PhD Defense on Reasoning Machines and Next Professional Chapter
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In 2023, I paused my PhD to join @OpenAI to build the world’s first reasoning machine — OpenAI o1. Earlier this year, I defended my PhD thesis “Building a Reasoning Machine” advised by @Yoshua_Bengio at @Mila_Quebec 🎓 🎉 Much has changed since Yoshua and I first discussed reasoning in 2022, but the main themes aged well: – Adding structures to computation unlocks strong reasoning capabilities; – Data & sample efficiency will become the bottleneck to useful intelligence; – Retaining Bayesian uncertainty is key to reliable and safe AI systems. You can read the introduction of my thesis here: edwardjhu.com/thesis/ My next professional chapter (TBA) will be on bridging frontier intelligence with real economic impact, a theme dear to my heart after working closely with @drwconvexity and @suna_said in the last year 🚀
→ View original post on X — @ceobillionaire, 2026-04-10 15:08 UTC
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New research framework proposes training tools instead of retraining AI agents
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Stop retraining your AI agents. Train their tools instead. Most AI agents look great in demos. Then they break in production. A new paper from Stanford and Harvard explains why. It introduces a framework that changes how we think about building agents. The core finding: when
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Understanding Composite AI: The Future of Intelligence Systems
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What Is Composite AI?
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @lexfridman @sama @kaifulee @ID_AA_Carmack @karpathy @2morrowknight @ylecun -
Meta to Release Muse Spark API Soon
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Meta is planning to release Muse Spark on the APIs soon. Would be curious also to play with Meta’s 9B model if it will ever come out. Soon
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BLIP-2: Connecting Vision and Language Models Efficiently
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BLIP-2: Bridging Vision and Language Without Full Retraining
— Satya Mallick (@LearnOpenCV) 10 avril 2026
In this episode of Artificial Intelligence: Papers and Concepts, we explore BLIP-2, a powerful vision–language model that connects pretrained image encoders with large language models without requiring expensive… pic.twitter.com/EnefAwliTzBLIP-2: Bridging Vision and Language Without Full Retraining In this episode of Artificial Intelligence: Papers and Concepts, we explore BLIP-2, a powerful vision–language model that connects pretrained image encoders with large language models without requiring expensive
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Exponential Quantum Advantage in Processing Massive Classical Data
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Exponential quantum advantage in processing massive classical data Zhao et al. : https://
arxiv.org/abs/2604.07639 #ArtificialIntelligence