The effort default change from high to medium that Anthropic confirmed is real and measurable. A 15-point accuracy drop in days on a specific benchmark needs a citation.
RESEARCH
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Anthropic Shifts from Agents to Skills for AI Models
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the creators of agent skills at Anthropic explained why they stopped building agents.
— m0h (@exploraX_) 13 avril 2026
and started building skills instead, showing just how powerful agentic skills can be
the article below shares 20 powerful skills you can pair with any AI model.
enjoy! https://t.co/Nk8xL5oHjY pic.twitter.com/dVoYsM069Ithe creators of agent skills at Anthropic explained why they stopped building agents. and started building skills instead, showing just how powerful agentic skills can be the article below shares 20 powerful skills you can pair with any AI model. enjoy! m0h (@exploraX_) x.com/i/article/203923778765… — https://nitter.net/exploraX_/status/2039269234253934811#m
→ View original post on X — @scobleizer, 2026-04-13 06:35 UTC
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AI System Failures: Why Prevention Matters More Than Recovery
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A blank screen after 45 minutes has zero recovery rate. A mediocre behavioral answer still passes. That asymmetry is the whole reason to take this seriously now.
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AMD Telemetry Dataset Reveals Anthropic Changes Confirmation
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An AMD director with 7,000 sessions of telemetry is not vibes. That's a dataset and Anthropic admitting to the changes after the data dropped is the confirmation that matters.
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TactileAloha: Giving Robots the Sense of Touch
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TactileAloha: Empowering #Robots with the Sense of Touch
— Ronald van Loon (@Ronald_vanLoon) 13 avril 2026
by @IntEngineering
#Robotics #ArtificialIntelligence #MachineLearning #EmergingTech #Innovation pic.twitter.com/SA7jbU2fVqTactileAloha: Empowering #Robots with the Sense of Touch
by @IntEngineering #Robotics #ArtificialIntelligence #MachineLearning #EmergingTech #Innovation -
LLMs Fairness and Consistency in AI Model Evaluation
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Are LLMs truly fair and consistent when judging other AI models? A collaborative team from Peking University, NUS, Institute of Science Tokyo, Nanjing University, Carnegie Mellon, Westlake, and Southeast University has the answer! They introduce TrustJudge, a probabilistic
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Mouse-Inspired Robot Learns Brain-Based Place Recognition
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How a Mouse-Inspired Robot Learns to Recognize Places Like a Brain
— Ronald van Loon (@Ronald_vanLoon) 13 avril 2026
by @lukas_m_ziegler
#Robotics #Engineering #ArtificialIntelligence #Innovation #Technology pic.twitter.com/EPjRBzZMwnHow a Mouse-Inspired Robot Learns to Recognize Places Like a Brain
by @lukas_m_ziegler #Robotics #Engineering #ArtificialIntelligence #Innovation #Technology -
Can Codes and Symbols Emerge in Neural Networks?
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Can codes and symbols emerge in a single neural network? Thinking from the "Neural Computers" paper @rmaruy
rmaruy.hatenablog.com/entry/… [Translated from EN to English] -
Context length benchmarks up to 180k tokens
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Ran some benchmarks on different context lengths all the way to 180k Findings below
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Ways to Train Large Language Models Effectively
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Ways to Train an #LLM
by @goyalshaliniuk #GenAI #ArtificialIntelligence #MachineLearning #ML