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I could actually see this having niche applications though. Like rendering high-quality graphics or training boutique AI models where having a distributed system of GPUs makes sense. But for the big AI use cases, I can't see how individual miners can compete with hyperscalers like CoreWeave building dedicated AI supercomputers.
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Harnessing GPU Power with CUDA CUDA (Compute Unified Device Architecture) is a parallel computing platform by Nvidia that unleashes the power of GPUs for more than just graphics rendering. Initially developed in 2007, CUDA enables massive parallel p
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ā”ļøUnreal power of new Nvidia GPUs. The RTX 5090 will be 48% more powerful than the RTX 4090 and will have 28 GB of GDDR7 video memory with a 448-bit bus, according to a RedGamingTech insider. But that's not all. Nvidia is working on Titan AI, which
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One of our recent achievements showcases how optimizing code and parallelizing processes can drastically improve machine learning model training times. The Challenge: Long Training Times Our model training process was initially taking 8 hoursāslow
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šš„ Google just made changing clothes obsolete. Welcome to Doppl ā your AI stylist in your pocket. Snap a pic. Upload any outfit you see online. Boom .. itās on you. In seconds. In motion. šāØ Yes, even that Insta look you thought you could never
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"Hello everyone, š¤ I'm working on creating a master course and I'd love to get your feedback. The course topic is 'Creating Successful Online Courses Using AI and Motion Graphics.' I've attached a PDF outline of the course curriculum and I'd appr
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