What's better than a scalable AI architecture? A scalable *and compounding* AI architecture.
MACHINE LEARNING
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Autonomous AI Through Dynamic Model Synthesis and Self-Improving Abstractions
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The path to autonomous AI is a system that learns to solve new problems by synthesizing models of them on the fly (as code), and that gets smarter over time by adding new abstractions to its own library (also as code), compounding its capabilities. Not a static map — rather, an
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AI Research Breakthrough with International Mathematics Experts
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Finally, this work won't be possible with the co-authors: @DawsenHwang
, @HoangT1215
, @g01na2
, @junsukim
, @gjb_ai
, @jon_lee0
, @Swarooprm7
, @hmichalewski
, @XingyouSong
, @thtrieu_
, @quocleix
, @jj_at_brown
, our IMO experts (who account for a total of 10 gold and 5 silver IMO medals), -
GradingBench releases 1000 human-graded IMO proof data points
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Last but not least, #GradingBench has 1000 human grading data points from our IMO effort on the advanced IMO-ProofBench. To ensure a robust evaluation, the dataset has been balanced across 4 simplified grading categories (Correct, Almost, Partial, Incorrect). We released all
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ProofAutoGrader: Automatic IMO Proof Evaluation Using Gemini
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While human expert evaluation remains the gold standard for mathematical proofs, its cost and time intensity limit scalable research. To address this, we built #ProofAutoGrader, an automatic grader for IMO-ProofBench. The autograder leverages Gemini 2.5 Pro, providing it with a
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IMO-ProofBench: Evaluating AI Mathematical Reasoning Capabilities
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IMO-ProofBench is our key focus designed to evaluate the ability of AI models in constructing rigorous and valid mathematical arguments. With 60 proof-based problems, the benchmark is divided into two subsets: a basic set covering pre-IMO to IMO-Medium difficulty levels, and an
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AI in Academia vs AI in the World: Different Priorities
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AI in academia: create architectures and algorithms for conference papers. AI in the world: create datasets and evaluations to engineer the models people use.
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Free Virtual SAS AI and Machine Learning Skills Fest
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Want to boost your career in AI and ML? Attend the free virtual SAS AI and Machine Learning Skills Fest! Nov. 12–14 | Register here: http://
2.sas.com/6011AfeIR -
Will AI Replace Computer Programmers? Myth or Reality
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Myth or Reality: Will AI Replace Computer Programmers? Explores whether software development is at risk of being fully automated, and why human programmers may remain essential despite advances in AI coding tools. Read more https://
bernardmarr.com/myth-or-realit
y-will-ai-replace-computer-programmers/
… #Coding #FutureJobs -
AI Integration in Energy Systems: Efficiency and Responsibility
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Thank you.
Yes, the integration of AI into energy systems is becoming essential to balance efficiency, resilience, and the responsible use of resources.