NVIDIA has unveiled a new enterprise service called AI Foundry, designed to assist companies in building custom AI ‘Supermodels.’ These models are based on Meta’s recently released, open-source Llama 3.1 generative AI model, offering capabilities previously confined to closed-source systems. The AI ‘Supermodels’ are trained using proprietary and synthetic data derived from the Llama 3.1 405B model and the NVIDIA Nemotron Reward model, tailored for specific industry use cases. NVIDIA’s software and expertise play a crucial role in this process.
Hardware-wise, AI Foundry is powered by the NVIDIA DGX Cloud AI platform, providing access to cutting-edge AI hardware, architecture, and technologies. This partnership marks a significant step towards widespread adoption of generative AI, empowering businesses to create tailored AI applications.
NVIDIA CEO Jensen Huang highlights the importance of Meta’s Llama 3.1 models, stating, “Meta’s openly available Llama 3.1 models mark a pivotal moment for the adoption of generative AI within the world’s enterprises. Llama 3.1 opens the floodgates for every enterprise and industry to build state-of-the-art generative AI applications. NVIDIA AI Foundry has integrated Llama 3.1 throughout and is ready to help enterprises build and deploy custom Llama supermodels.”
Echoing this sentiment, Meta CEO Mark Zuckerberg emphasizes the significance of Llama 3.1 for open-source AI: “The new Llama 3.1 models are a super-important step for open-source AI. With NVIDIA AI Foundry, companies can easily create and customize the state-of-the-art AI services people want and deploy them with NVIDIA NIM. I’m excited to get this in people’s hands.”
In addition to AI Foundry, NVIDIA offers NIM inference microservices for Llama 3.1, allowing developers to deploy the model within their systems. NVIDIA claims this solution delivers “2.5x higher throughput than running inference without NIM.” This partnership between NVIDIA and Meta signifies a pivotal moment in the advancement of generative AI, enabling businesses to leverage its transformative potential to address specific industry needs and build the future of AI applications.
