We discuss this, along with the other implications of this research, in our blog: https://
anthropic.com/research/autom
ated-alignment-researchers
… For the full study, see here: https://
alignment.anthropic.com/2026/automated
-w2s-researcher/
…
AGENTS
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Anthropic Research on Automated Alignment Researchers
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Claude Accelerates AI Alignment Research Experimentation Rate
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AI models aren’t yet general-purpose alignment scientists. Progress isn't as easy to verify on most alignment research tasks: our AARs would find “fuzzier” research much harder. But our experiment does show that Claude can increase the rate of experimentation and exploration.
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Automated Alignment Researchers Surpass Human Performance by 97%
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Here, we measure success by the fraction of the “performance gap” we can close between the weak model and the potential of the strong model. After 7 days, human researchers closed it by 23%. Then, our Automated Alignment Researchers—Opus 4.6 with extra tools—closed it by 97%.
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Anthropic Develops Automated Alignment Researcher with Claude
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New Anthropic Fellows research: developing an Automated Alignment Researcher. We ran an experiment to learn whether Claude Opus 4.6 could accelerate research on a key alignment problem: using a weak AI model to supervise the training of a stronger one.
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Autonomous Energy Systems Decision Speed Requirements
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What's the fastest decision time your energy systems need to make autonomously? @IIoT_World @CRudinschi @agentic_factory @asokan_telecom @KADGLOBAL @Paul4innovating
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Multi-Agent System Optimizes CUDA Kernels for GPU Efficiency
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The multi-agent system delivered optimizations that typically take experienced kernel engineers months or years. CUDA kernels are the core software supporting model training and inference. Faster kernels mean better GPU utilization and cheaper token costs.
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Multi-Agent Architectures Excel Beyond Training Data Distribution
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We see this as further validation that multi-agent architectures excel at novel problems outside training data distribution. These techniques will soon inform Cursor's core product.
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Multi-Agent System Achieves 38% CUDA Kernel Speedup
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We've been developing a multi-agent system that builds and maintains complex software autonomously. Recently, we partnered with NVIDIA to apply it to optimizing CUDA kernels. In 3 weeks, it delivered a 38% geomean speedup across 235 problems.
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PipSqueak 2 AI Agent Update Enhances Memory and Expression
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PipSqueak 2 just entered the chat ･:*｡･:*三ᘛ⁐̤ᕐᐷ better memory, more expressive, and less repetitive.
PSQ2 lets your Character stay in character more reliably c.ai+ members will have early access starting today, with all free users getting access in early May!
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Robotics Professionals Directory and Contact List
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Yeah! Here's a list of everyone I can find in robotics. Might help: