GlyphNet’s own results support this: their best CNN (VGG16 fine-tuned on rendered glyphs) achieved 63-67% accuracy on domain-level binary classification. Learned features do not dramatically outperform structural similarity for glyph comparison, and they introduce model versioning concerns and training corpus dependencies. For a dataset intended to feed into security policy, determinism and auditability matter more than marginal accuracy gains.
This article originally appeared on Engadget at https://www.engadget.com/home/ambient-dreamie-bedside-companion-review-the-best-sleep-ive-had-in-years-184019430.html?src=rss
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Source: Computational Materials Science, Volume 266
All of these changes came in the wake of layoffs, big-name flops, more layoffs, studio closures, even more layoffs, strikes and (yep) layoffs again. Earlier this month, Ubisoft even fired an employee who criticized the company’s return-to-office mandate.
Read the full story at The Verge.