Gurman: as part of Vision Pro cuts, Apple is largely shutting down a team focused on gaming and reducing the size of a unit producing immersive video content (Chance Miller/9to5Mac)
https://9to5mac.com/2026/08/21/apple-lays-off-200-people-across-vis…
🇺🇦 #NowPlaying on KEXP's #SeekAndDestroy
Agriculture:
🎵 Bodhidharma
#Agriculture
https://agriculturemusic.bandcamp.com/track/bodhidharma
https://open.spotify.com/track/1NoYnWzMQ1mY67jo7gDakq
AI advice suppresses people’s willingness to say “I don’t know”, even when the advice is wrong and accuracy is incentivized.
https://arxiv.org/abs/2607.13562v1
Google rolls out an embeddable "Preferred Sources" button, natural language Discover controls, and custom audio briefings in the Google News app on Android (Matt G. Southern/Search Engine Journal)
https://www.searchenginejournal.com/google
Orientation Reading by Production Vision-Language Models on Optotype Charts: A Controlled Multi-Model Evaluation Across Reasoning Modes, Prompts, and Access Modalities
Shahryar Wasif, Avneek Sandhu, Bin Hu
https://arxiv.org/abs/2607.16595 https://arxiv.org/pdf/2607.16595 https://arxiv.org/html/2607.16595
arXiv:2607.16595v1 Announce Type: new
Abstract: OBJECTIVES: Vision-language models are increasingly used to interpret medical and everyday images through consumer chat interfaces, yet their ability to read orientation - the single perceptual operation tested by the tumbling-E acuity optotype - is poorly characterized on the surfaces through which they are actually used. METHODS: We evaluated four production vision-language models (referred to as Claude, GPT, GROK, and Gemini) through their consumer chat interfaces on a locked set of seven optotype charts: four uniform tumbling-E charts (one per cardinal orientation), two mixed-orientation tumbling-E charts, and one Snellen letter chart as a specificity control. Each model was run in two reasoning modes (Fast and Thinking) under two prompt variants (with and without an explicit orientation-decoding rule) by up to three operators. The corpus comprised 920 scoreable trials and 50,420 glyph judgements. The primary outcome was glyph-level accuracy against the chart's designed orientation, summarized with Wilson 95% confidence intervals. RESULTS: Accuracy ranged from 43.0% to 97.0% across models on identical charts, and the strongest model depended on reasoning mode (GPT 97.0% in Fast mode; GROK 96.6% in Thinking mode). Errors were not random but collapsed onto a model-specific attractor direction. Models were 96-100% internally self-consistent yet ranged widely in accuracy, dissociating reliability from validity. An answer-key-free ensemble-consensus estimate tracked accuracy closely (r = 0.998). For one model, consumer-interface accuracy fell 25-27 points below programmatic access, almost entirely on a single orientation. CONCLUSIONS: A single accuracy figure conceals clinically relevant, orientation-specific failure modes; vision-language models should be evaluated along multiple axes and on the deployment surface before image-interpretation outputs are trusted.
toXiv_bot_toot
Just on the way to bed and to the South East on the horizon is a spectacular thunder storm. I checked my lightning app and I can see it a huge storm stretching from Amiens to Lille in France - 140 miles away across the Channel!
#weather #lightning
Google rolls out an embeddable "Preferred Sources" button, natural language Discover controls, and custom audio briefings in the Google News app on Android (Matt G. Southern/Search Engine Journal)
https://www.searchenginejournal.com/google
Blackstone agrees to invest an undisclosed sum in South Korea-based Futronic, which makes actuators used in industrial robots, sources say at a ~$675M valuation (Manuel Baigorri/Bloomberg)
https://www.bloomberg.com/news/articles/20