OPENAI : A mention of a new Ultrafast mode appeared for some time on the Codex GitHub repository. > "The fastest available responses for latency-sensitive work." Seems like it was unintended push
RESEARCH
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Deconstructing Geoffrey Hinton’s Perspective on AI
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you are lost, brother, read this: https://
open.substack.com/pub/garymarcus
/p/deconstructing-geoffrey-hintons-weakest?r=8tdk6&utm_medium=ios
… and also this: -
Deconstructing Geoffrey Hinton’s Views on AI
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the details of what he said and why it was wrong are here: https://
open.substack.com/pub/garymarcus
/p/deconstructing-geoffrey-hintons-weakest?r=8tdk6&utm_medium=ios
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GPT Image 2 Sets New Performance Record on Image Arena
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GPT Image 2 just dethroned Nano Banana 2 on Image Arena — by the biggest gap in leaderboard history (+242 Elo points) Here's how the two best AI image generators stack up: GPT Image 2
→ ~99.2% text rendering accuracy
→ #1 across every Arena category
→ $0.211 per -
Accepted papers for COLT 2026 announced
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Accepted papers for #COLT2026: https://
learningtheory.org/colt2026/accep
ted.html
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Optimizing AI models for creativity to overcome lack of variation
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The inability of AI models to produce creative variation is a huge gap. The fact that they generate similar ideas limits their ability to do science & the same-y writing limits their usefulness in many other applications This paper showed you can optimize models for creativity
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Enterprise roadmap vs Labs’ rapid AGI scaling vision
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Enterprises are going to actually want a coherent roadmap for the development of tools like Codex and Cowork, so they can plan and train and scale their use. This conflicts with the Labs’ vision where these tools rapidly scale exponentially in ability as models approach AGI.
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Why Do Large Neural Networks Work?
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Researchers have just explained why massive neural networks work so effectively. Deep networks possess enough capacity to memorize completely random noise. Yet, they still excel at making accurate predictions on unseen data. A new paper finally sheds light on this phenomenon. The empirical Neural Tangent Kernel (NTK) subtly divides the output.
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Technical Requirements for Evaluating AI Model Architecture
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Thanks, but there are no open weights yet, right? Asking because it would be impossible to cover architecture details without open weights and/or a detailed technical report
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MACE-Dance: Motion-Appearance Experts for Music-Driven Dance
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MACE-Dance Motion-Appearance Cascaded Experts for Music-Driven Dance Generation