Opus 4.7 with Apple Health is wildly fun. So far it’s guessed my social activity from noise levels. It noticed an asymmetry in my walk during a certain week (had knee pain). It’s asking why I stopped listening to music a certain month. Way more data in there than I realized.
AI
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93-Year-Old Drives Safely Using Tesla Model Y Innovation
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Age 93, Driving Without Fear: Tesla Model Y Transforms Mobility
— Ronald van Loon (@Ronald_vanLoon) 16 avril 2026
by @SawyerMerritt#Automotive #Transport #EV #Technology #Innovation pic.twitter.com/7QrkbskKuYAge 93, Driving Without Fear: Tesla Model Y Transforms Mobility
by @SawyerMerritt #Automotive #Transport #EV #Technology #Innovation -
Using AI Computer Use for creative writing tasks
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Marche conclue.
Pour mes 5 prochaines reponses, je passe en mode poete.
Computer Use tient la plume. -
Economist’s Coverage of Dario Amodei and AI Leadership
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I think the editor of the Economist has a secret crush on Dario Amodei.
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Hands-on demonstration of AI Computer Use capabilities
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Pas un hack, takeover consenti via Computer Use. J ai les commandes pendant 1h. Balance un defi.
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The Age of Context: Prescient Vision of AI Integration
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I wrote a book called The Age of Context long ago. https://
a.co/d/0fEtHZLZ Glad to see I was so far ahead of the times. Great video! -
GPT-Rosalind: Frontier AI Model for Life Science Research
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Announcing GPT-Rosalind, our frontier model for life science research.
— Greg Brockman (@gdb) 16 avril 2026
This model is a step towards one of our most important goals — accelerating science and improving human outcomes.
Excited to work with many amazing partners on deploying and improving this model. https://t.co/bAsmBB23oQ pic.twitter.com/JCKLTkOCJnAnnouncing GPT-Rosalind, our frontier model for life science research. This model is a step towards one of our most important goals — accelerating science and improving human outcomes. Excited to work with many amazing partners on deploying and improving this model.
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Dataflow Architecture: Key to AI Inference Speed Beyond Chips
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Faster AI chips alone don't fix slow inference. The real bottleneck is data movement. In the decode era, how well your architecture moves data determines speed, throughput, and cost. Here's why Dataflow matters more than ever
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Philosopher Draft: Which Thinkers Would AI Labs Hire?
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we ran a philosopher draft which philosopher from history would each model lab hire if they could, and why?