NVIDIA unveils AI Foundations, its customizable Gen-AI cloud service | Engadget

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NVIDIA unveils AI Foundations, its customizable Gen-AI cloud service | Engadget
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NVIDIA unveils AI Foundations, its customizable Gen-AI cloud service

. NVIDIA announced such a system Tuesday built on the NeMo cloud service: a series of responsibly sourced text-to-image and text-to-video models,"trained on Getty Images' fully licensed assets," Tuesday’s press release read."BioNeMo, uses the same technical underpinnings as NeMo itself, but is geared entirely towards drug and molecule discovery.

"BioNeMo is dramatically accelerating our approach to biologics discovery," Peter Grandsard, executive director of Biologics Therapeutic Discovery at Amgen said in a statement."With it, we can pre-train large language models for molecular biology on Amgen’s proprietary data, enabling us to explore and develop therapeutic proteins for the next generation of medicine that will help patients.

Six models will be available at launch including DeepMind’s AlphaFold2, Meta AI’s ESM2 and ESMFold predictive models ProtGPT-2, DiffDock and MoFlow. According to the companies, incorporating AI-based predictive models helped reduce the time to train “five custom models for molecule screening and optimization” using Amgen’s proprietary data on antibodies from the usual three months down to fourNVIDIA announced a similar partnership with Shutterstock as well.

“Our generative 3D partnership with NVIDIA will power the next generation of 3D contributor tools, greatly reducing the time it takes to create beautifully textured and structured 3D models,” Shutterstock CEO Paul Hennessy, said in the release. “This first of its kind partnership furthers our strategy of leveraging Shutterstock’s massive pool of metadata to bring new products, tools, and content to market.

NVIDIA is also partnering with Adobe as part of the latter’s Content Authenticity Initiative, which seeks to enhance transparency and accountability within the generative AI training process. The CAI’s proposals include a “do not train” list, similar to robot.txt but for images and multimodal content, and persistent origination tags that will detail whether a piece is AI generated and from where.

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