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“The result of this is the model’s not just going to be better than a physicist. It’s going to be better than a superposition of somebody who’s at the top in physics, computer science and data science.”

That’s how Jonathan Siddharth, CEO of Turing AI, describes the shift happening in advanced AI model training. Instead of relying on low-cost clickworkers, companies like Scale AI, Toloka, and Turing are now turning to highly skilled experts in fields like physics, biology, software engineering, and finance. The goal is to create complex, domain-specific tasks that mirror real human thought processes - whether that means writing code, validating physical theories, or analyzing simulations. These specialized datasets are then used to train the new reasoning models at major companies like OpenAI.

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Nvidia announced at the RISC-V Summit China that it will open up its CUDA platform to support RISC-V processors. For the first time, CUDA will extend beyond x86 and Arm to include an open instruction set architecture. According to Nvidia, RISC-V CPUs can now serve as the central processing component in CUDA systems, including Jetson modules and specialized edge devices. The company showcased a reference architecture pairing RISC-V CPUs for operating system and logic tasks with Nvidia GPUs for compute workloads and DPUs for networking. This move could help expand CUDA's reach in markets like China.

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Netflix used generative AI to produce a VFX scene in its Argentinian series “El Eternauta,” co-CEO Ted Sarandos said during the company’s earnings call. The AI-assisted sequence was finished ten times faster than traditional methods and would have been too expensive to make otherwise, Sarandos said. Like every CEO, he claimed AI is meant to support creatives, not replace them. The scene also used virtual production tools.

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