Tootfinder

Sources: Alibaba is set to lead a $300M round in AI model testing startup UniPat AI at a $2.5B valuation; UniPat founder Li Kuan worked at Alibaba's Tongyi Lab (Bloomberg)
https://www.bloomberg.com/news/articles/2026-09-10…

Hey, #Utah. How's about a new, government-funded cult, as a treat?
"These group exercises and private corrections resemble tactics used in Synanon, a notorious and controversial drug treatment program seen as one of the first versions of a therapeutic community model. The Other Side Academy leaders don’t claim a tie to that program. But Delancey Street Foundation — where several ear…

Reconstruction Bias in Timepix4 Subpixel Centroiding for Electron Imaging
Nina Dimova, Richard Plackett, Daniela Bortoletto
https://arxiv.org/abs/2608.21072 https://arxiv.org/pdf/2608.21072 https://arxiv.org/html/2608.21072
arXiv:2608.21072v1 Announce Type: new
Abstract: Subpixel centroiding is widely used to improve the spatial resolution of hybrid pixel detectors for electron imaging by estimating the true interaction position within an entry pixel. Existing centroiding strategies are typically optimised using localisation accuracy. However, observations show that improved localisation does not necessarily translate into improved modulation transfer function (MTF) or reliable virtual-pixel rebinning. This work proposes a unified interpretation of these observations based on the ambiguity of the centroid reconstruction problem. We show that observable-based centroid estimators solve an intrinsically non-unique inverse problem using deterministic reconstruction rules, which can introduce entry-phase-dependent reconstruction bias that governs the spatial distribution of reconstructed subpixel coordinates. This framework explains why localisation accuracy alone is insufficient to predict imaging performance and identifies approximate intra-pixel translational symmetry as a prerequisite for faithful virtual-pixel imaging. The proposed interpretation is evaluated using simulated 200 keV and 300 keV electron data together with measured 200 keV data acquired with a Timepix4 detector. Comparisons of charge-weighted, timing-based, and morphology-dependent centroiding strategies demonstrate that estimators with similar localisation performance can exhibit markedly different MTFs and rebinned flat-field behaviour. The results suggest that future centroid optimisation should consider subpixel phase bias and rebinnability alongside localisation accuracy.
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In an interview, Tim Cook says Apple price hikes are "unavoidable" to offset surging memory and storage chip costs, and "the situation has become unsustainable" (Rolfe Winkler/Wall Street Journal)
https://www.wsj.com/tech/apple-price…