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Malone leaves OpenAI: infrastructure wing changes leadership again
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Malone leaves OpenAI: infrastructure wing changes leadership again

Chris Malone, who oversaw data centers at OpenAI, is no longer with the company — his departure fits into a string of losses among top management that has exceeded a dozen names over the year. Formally, no reasons are given, but it was precisely in this area that a management reshuffle took place shortly before his departure: the division was moved out from under Greg Brockman's direct oversight and handed to Vice President Sachin Katti.

14 September 2026
Liquid AI open-sourced Pipette: how to benchmark on-device inference end to end — from quantization to hardware
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Liquid AI open-sourced Pipette: how to benchmark on-device inference end to end — from quantization to hardware

Liquid AI, together with Artificial Analysis, has released Pipette, an open platform where the unit of measurement is not the model itself but the entire deployed configuration: weights, quantization scheme, runtime, and the specific device. The starting set includes over a thousand such combinations, more than thirty models, and the first benchmarks on smartphones and laptops with Apple Silicon.

14 September 2026
Spiking network decides where to look: membrane potential becomes a confidence indicator in 3D point cloud parsing
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Spiking network decides where to look: membrane potential becomes a confidence indicator in 3D point cloud parsing

The authors of arXiv:2608.19232 propose rethinking point cloud recognition as a sequence of decisions: the accumulated charge of LIF neurons serves as a running class estimate, hints at which fragment to inspect next, and allows early exit from computation. The method adds about 2% parameters to the backbone and transfers to dense prediction, though in accuracy on ModelNet it falls slightly behind a heavier spiking competitor.

14 September 2026
TimeRoute: Personalized Modality Selection and Diffusion Against Outdated Signals in Recommendations
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TimeRoute: Personalized Modality Selection and Diffusion Against Outdated Signals in Recommendations

Researchers from the University of Amsterdam have proposed a diffusion-based recommender that tunes the proportions of text, images, and audio for each user, taking into account how quickly these signals lose relevance. Separate long-term and short-term denoising streams filter out outdated modal connections before they enter the propagation graph.

14 September 2026

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