METR's evals are honestly the best public signal we have for actual capability gain right now, glad they're getting more airtime.
MACHINE LEARNING
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AI Often Judged on Outdated Models, Skewing Research Results
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This points to a broader issue where AI is often being judged based on extremely outdated models. Any time someone sends me a study showing AI failing at something, the first thing I do is look at the models they used… more often than not, they’re extremely outdated. We need
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Level Up Data and AI Skills at DataAISummit 2026
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Level up your data + AI skills at #DataAISummit!
— Databricks (@databricks) 27 avril 2026
Explore 800+ sessions across topics like AI agents, Lakebase, democratizing BI, app development, and more. You can also take onsite certification exams at 50% off to validate your expertise.
Spots are limited. Secure your… pic.twitter.com/cyXw0sPSYOLevel up your data + AI skills at #DataAISummit! Explore 800+ sessions across topics like AI agents, Lakebase, democratizing BI, app development, and more. You can also take onsite certification exams at 50% off to validate your expertise. Spots are limited. Secure your
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Bullshit Benchmark: Evaluating AI Model Reliability
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GitHub: https://
github.com/petergpt/bulls
hit-benchmark
… DataViewer: https://
petergpt.github.io/bullshit-bench
mark/viewer/index.v2.html
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AI Models Learn Self-Improvement Without External Rewards
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Can an AI teach itself to reason better without any outside reward? Researchers from CUHK, Shenzhen, SJTU, and CUHK present SePT. They let a language model generate its own reasoning examples by using "low-temperature" (more focused) responses, then train on that new data in a
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Abstract Chain-of-Thought: Efficient Latent Reasoning Without Words
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"Thinking Without Words: Efficient Latent Reasoning with Abstract Chain-of-Thought" Do reasoning models really need to think in words? This paper replaces long verbal CoT with a short learned sequence of abstract tokens that acts like a latent scratchpad. Warmed up from
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Scientific Theory of Deep Learning Emerges
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“There Will Be a Scientific Theory of Deep Learning” This paper argues that a real scientific theory of deep learning is beginning to emerge. Not a theory that tracks every neuron individually, but a physics-like theory of learning itself. One that aims to characterize how
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Overcoming Barriers to AI Adoption in Financial Services
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Moving Past Roadblocks To Unlock Artificial Intelligence in Financial Services
#AI #AIio #AIInnovation #ML #DataScience #Futureofwork @timnitgebru @oriolvinyalsml @ceobillionaire @soumithchintala @waitin4agi_ @sallyeaves @bernardmarr -
Research on Prompt Compression Using Draft Models Accepted to ICLR
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Another research accepted to ICLR 2026 We explored a new way to shrink long prompts using smaller draft models from different model families, no retraining needed. Faster time to first token, with performance holding strong. Take a look @UrmishThakker
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Agentic World Modeling: Foundations, Capabilities, Laws
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Agentic World Modeling Foundations, Capabilities, Laws, and Beyond paper: https://
huggingface.co/papers/2604.22
748
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