A weird part of working at Anthropic: getting a few of these each day
RESEARCH
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Growing Up in the 90s: Neural Nets, Scaling Laws, and Artificial Consciousness
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My ideal timeline: Growing up in the 90s, discovering neural nets, scaling laws, and building an artificial consciousness.pic.twitter.com/FQMunONGm3
— hardmaru (@hardmaru) 29 mars 2026My ideal timeline: Growing up in the 90s, discovering neural nets, scaling laws, and building an artificial consciousness.
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Three-month-old Anthropic model achieves SOTA on code maintainability
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~3mo old model is still SOTA and was +8% vs 5.3-codex on maintainability total anthropic victory Gabe Orlanski (@GOrlanski) We found that agents generate progressively worse code with each iteration. Real developers do not. SlopCodeBench is the only eval that faithfully measures quality degradation on iterative, long-horizon coding tasks. arxiv.org/abs/2603.24755 scbench.ai 🧵 — https://nitter.net/GOrlanski/status/2037560777356238881#m
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Querying 3 Billion Vectors in AI and Machine Learning
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Querying 3 billion vectors buff.ly/WBC83jD #AI #MachineLearning #DeepLearning #LLMs #DataScience
→ View original post on X — @miketamir, 2026-03-29 00:05 UTC
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AI Researchers Debate LLM Capabilities: Correlation vs. Causation
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if you’re using Ollama switch to llama.cpp if you’re using OpenClaw switch to Hermes these are basics at this point
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Vizier-style Bayesian search outperforms alternative hyperparameter optimization
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As it turns out, it's empirically much less efficient than Vizier-style Bayesian hyperparameter search
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Origami-Inspired Robot Crawls Across Complex Terrain
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Origami-Inspired #Robot Crawls Across Complex Terrain Without Legs
— Ronald van Loon (@Ronald_vanLoon) 28 mars 2026
by @tweetciiiim#AI #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/hJ57BomxFHOrigami-Inspired #Robot Crawls Across Complex Terrain Without Legs
by @tweetciiiim #AI #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology -
Exploring Interesting Approaches to Infinite Memory and Context in AI
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r/hardwareswap subreddit snd discord server
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Self-Distillation Degrades LLM Reasoning Capabilities
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"Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?" Self-distillation can make LLMs look smarter by producing shorter, more confident reasoning traces, but in math it often takes out the model's uncertainty and self-correction signals. This can
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New AI Paper Reveals Surprising and Persistent Phenomenon
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New AI paper from us this week. When my student first showed me his initial findings, I really didn't know what to make of them. I felt that this was an interesting but curious loophole phenomenon that would shortly be closed. I was very wrong. arxiv.org/abs/2603.21687 [Translated from EN to English]
→ View original post on X — @debashis_dutta, 2026-03-28 20:41 UTC