Kol Tregaskes

@koltregaskes
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AI Art Creator 🎨 | AI Video Producer 🎬🤖 | AI Music Composer 🎵 | Tech & Science News Curator🔬 | Movie & Sci-fi Enthusiast 🍿 | Geek at Heart 🤓 | #AI #Tech
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After the Sora news the news on the Disney deal cancellation was inevitable.
https://x.com/DiscussingFilm/status/2036546800069353689?s=20
DiscussingFilm (@DiscussingFilm) on X

Disney has cancelled their deal with OpenAI. They planned to invest $1 billion into the company and let Sora have access to AI generate videos of characters from Disney, Marvel, Pixar and Star Wars. (Source: https://t.co/9q8u5VtqZE)

X (formerly Twitter)
More news on the Sora closure and the new LLM.
https://x.com/kimmonismus/status/2036549192592531960?s=20
Chubby♨️ (@kimmonismus) on X

OpenAI's Sora team is now working on world-models - they prioritize longer-term world simulation research especially as it pertains to robotics. tl;dr what we know so far: - Sora has been cancelled because they needed the compute for their new LLM - they renamed product

X (formerly Twitter)

Sora's closure announced in a confusing edited message. More details on the app and API to follow. Further news suggests they will focus on world models instead and use the released compute for a new "very, very strong" model that "accelerates the economy" coming very soon. Disney cancels deal with OpenAI.

https://x.com/soraofficialapp/status/2036546752535470382?s=20

- Scientists lack a semi-formal language to capture the intuitive heuristics narratives and plausibility judgments they use daily beyond pure logical proofs in systems like Lean.
- Serendipity unplanned interactions and a certain level of distraction remain essential for creativity even as AI automates routine tasks and over-optimisation risks reducing it.

The full episode is available on the usual platforms.

https://x.com/dwarkesh_sp/status/2035446346803777728?s=20

Dwarkesh Patel (@dwarkesh_sp) on X

Terence Tao spent a year at the Institute for Advanced Study - no teaching, no random events of committees, just unlimited time to think. But after a few months, he ran out of ideas. Terence thinks that mathematicians and scientists need a certain level of randomness and

X (formerly Twitter)
- AI now enriches Tao's papers with far more charts code numerical examples and literature searches making secondary tasks up to five times faster while the deepest deductive core work still happens with pen and paper.
- Human-AI hybrid teams are expected to dominate mathematical discovery for years to come as each supplies complementary strengths of breadth and depth.
- Tao distinguishes artificial cleverness where AI excels at jumping over low walls or solving easy untried problems from true intelligence which builds cumulatively on partial progress through interactive adaptation.
- AI rapidly solved around 50 previously untouched Erdős problems but progress stalled when three teams applied frontier models to the remaining harder challenges.
- AI has made generating thousands of hypotheses almost free but the real bottleneck is now verification evaluation and separating valuable ideas from massive volumes of slop.
- Small datasets can produce spurious patterns such as Bode's law which seemed to predict missing planets until Neptune's discovery showed it was a numerical coincidence.
- Copernicus's simpler heliocentric model with circular orbits actually predicted planetary positions less accurately than Ptolemy's refined geocentric system which had centuries of tweaks.
- Correct theories can initially make worse predictions and survive only through hard-to-articulate human judgment and heuristics that may take decades or centuries to verify.

Terence Tao joins Dwarkesh Patel to explain how Kepler discovered the laws of planetary motion after 20 years of testing random theories and what this reveals about AI progress in science.

- Kepler behaved like a high-temperature LLM generating countless random relationships and geometric ideas over two decades before using Tycho Brahe's precise naked-eye data to derive his three famous laws of ellipses equal areas and the period-distance relation.

Roche has purchased 2,176 Nvidia Blackwell GPUs to launch a new AI factory, taking its total to over 3,500 GPUs - the largest announced in the pharmaceutical industry - to accelerate drug discovery, development, manufacture and commercialisation.

The infrastructure deploys across the US and Europe under a collaboration with Nvidia that started in 2023. Roche aims to shorten the typical $1 billion, 10-year drug development process with AI embedded everywhere.

https://x.com/Forbes/status/2035959759552254159