Tootfinder

Riesenrakete Starship: Beim zehnten Testflug läuft wieder alles nach Plan
Nachdem drei Testflüge infolge nicht geglückt waren, ist SpaceX beim zehnten Start der Riesenrakete Starship jetzt wieder alles gelungen, was geplant war.

Kasvipohjaisempi ruokavalio parantaa ruokavalion laatua, mutta tuo myös haasteita https://www.ruokavirasto.fi/teemat/riskinarviointi/riskinarviointiuutisia/aj…

Kasvipohjaisempi ruokavalio parantaa ruokavalion laatua, mutta tuo myös haasteita

Starship: Zehnter Testflug der Riesenrakete kurz vor Start verschoben
Mit dem größten Raketensystem will Elon Musk zum Mars. Neun Tests liefen anders als geplant, nun sollte der zehnte folgen – doch erstmal bleibt sie am Boden.

Video models are zero-shot learners and reasoners
Thadd\"aus Wiedemer, Yuxuan Li, Paul Vicol, Shixiang Shane Gu, Nick Matarese, Kevin Swersky, Been Kim, Priyank Jaini, Robert Geirhos
https://arxiv.org/abs/2509.20328

Video models are zero-shot learners and reasoners
The remarkable zero-shot capabilities of Large Language Models (LLMs) have propelled natural language processing from task-specific models to unified, generalist foundation models. This transformation emerged from simple primitives: large, generative models trained on web-scale data. Curiously, the same primitives apply to today's generative video models. Could video models be on a trajectory towards general-purpose vision understanding, much like LLMs developed general-purpose language underst…

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning
Xuan Zhang, Zhijian Zhou, Weidi Xu, Yanting Miao, Chao Qu, Yuan Qi
https://arxiv.org/abs/2508.16524 https://

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning
Enabling neural networks to learn complex logical constraints and fulfill symbolic reasoning is a critical challenge. Bridging this gap often requires guiding the neural network's output distribution to move closer to the symbolic constraints. While diffusion models have shown remarkable generative capability across various domains, we employ the powerful architecture to perform neuro-symbolic learning and solve logical puzzles. Our diffusion-based pipeline adopts a two-stage training strategy:…

Amazon agrees to pay $2.5B to settle a US FTC case, including a $1B civil penalty and $1.5B in consumer redress; FTC alleged Amazon duped customers into Prime (Rafe Rosner-Uddin/Financial Times)
https://www.ft.com/content/69df3776-3286-40ea-8a9e-8f08a1314aa8

Ich zögere immer noch einen Gaming Rechner für Videobearbeitung mit #DaVinci (Studio V20) für Linux aufzusetzen.
Habt ihr Erfahrung damit? Besser doch Win11?
Und wenn wir schon dabei sind: AMD Ryzen oder Intel Prozessor? GeForce oder Radeon?
Habe mich bei Puget schon eingelesen...

DaVinci Resolve Studio: AMD Ryzen 9000 Series vs Intel Core 14th Gen
AMD's new Ryzen 9000 processors are here, but how do they compare to the previous generation Ryzen 7000 or Intel's Core 14th Gen processors in DaVinci Resolve Studio?

Abschied vom Bluescreen: Windows-Fehlerseite wird noch im Sommer schwarz
Als ein fehlerhaftes CrowdStrike-Update vor einem Jahr Millionen Rechner lahmlegte, gingen die Fotos der Bluescreens um die Welt. Die sollen bald schwarz sein.

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning
Xuan Zhang, Zhijian Zhou, Weidi Xu, Yanting Miao, Chao Qu, Yuan Qi
https://arxiv.org/abs/2508.16524 https://

Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning
Enabling neural networks to learn complex logical constraints and fulfill symbolic reasoning is a critical challenge. Bridging this gap often requires guiding the neural network's output distribution to move closer to the symbolic constraints. While diffusion models have shown remarkable generative capability across various domains, we employ the powerful architecture to perform neuro-symbolic learning and solve logical puzzles. Our diffusion-based pipeline adopts a two-stage training strategy:…