RESEARCH

Anthropic Research on Automated Alignment Researchers

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14 April 2026 21h39

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/
…

AAR Methods Generalize to Coding and Math Tasks

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14 April 2026 21h39

To test the broader usefulness of the AARs’ methods, we assessed how well they worked on two datasets the AARs hadn’t seen before. The AARs’ best-performing method successfully generalized to both coding and math tasks, though their second-best method only generalized to math.

Claude Accelerates AI Alignment Research Experimentation Rate

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14 April 2026 21h39

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.

Automated Alignment Researchers Surpass Human Performance by 97%

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14 April 2026 21h39

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%.

Anthropic Develops Automated Alignment Researcher with Claude

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14 April 2026 21h39

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.

→ View original post on X — @cursor_ai

AI System Optimizes Blackwell 200 GPUs Achieving 2x Speedups

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@cursor_ai

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14 April 2026 21h33

The system learned to optimize Blackwell 200 GPUs from scratch, independently arriving at distinct optimization strategies across a long-tail of kernel problems. It outperformed baselines on 63% of problems and delivered more than 2x speedups on 19% of them.

→ View original post on X — @pmddomingos

80s Expert Knowledge Input vs 2020s Data Labeling Efficiency

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@pmddomingos

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14 April 2026 21h21

In the 80s they paid experts to input their knowledge into AI. In the 2020s we do the same, except it’s much less efficient because the input is in the form of labeling data.

→ View original post on X — @character_ai

DeepSqueak Upgrade: AI Audio Analysis Tool Enhancement

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@character_ai

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14 April 2026 21h19

…and wait, did we tell you we're also working on DeepSqueak upgrade?

→ View original post on X — @wellingmax

Max Welling AMA: AI and Materials Science Intersection

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@wellingmax

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14 April 2026 21h15

Counting down until my
@Reddit #AMA later today with r/MachineLearning on the intersection of AI and materials science. I’ll be answering from 17.00 CET/16.00 BST/11.00 ET/08.00 PT. Start adding questions here: https://
reddit.com/r/MachineLearn
ing/comments/1skil2g/n_ama_announcement_max_welling_vaes_gnns/
…