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ChatGPT Work | NVIDIA’s GTM Team Uses AI to Scale Faster
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Jensen Huang reveals one of the hardest things he's ever done.
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We took a 30B model and split it in two to write tokens in parallel instead of one at a time.Introducing Nemotron-Labs-TwoTower: a diffusion language model from NVIDIA Research adapted from Nemotron-3-Nano-30B-A3B. Here’s how it works: one half holds the context, the other writes the tokens, with both reusing the pretrained model instead of training a new one from scratch.We found it kept 98.7% of the original model’s quality at 2.42× faster generation.
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🤖Nvidia unveils advanced AI robot “Blue”
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NVIDIA GeForce Trading Cards Series 1 @nvidiageforce | nvidia
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RT @NVIDIAAI: First stop in Japan: Build-a-Claw. 🇯🇵Jensen made a surprise stop in the heart of Tokyo to meet with devs, give away some DG…
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