The new Mistral NeMo AI model from Nvidia and Mistral AI should make it easier for companies to efficiently implement AI across IT environments—even client devices.
The promise of AI in the enterprise is huge—as in, unprecedentedly huge. The speed at which a company can get from concept to value with AI is unmatched. This is why, despite its perceived costs and complexity, AI and especially generative AI are a top priority for virtually every organization.
Mistral NeMo features a 128,000-token context length, which enables a greater level of coherency, contextualization and accuracy. Consider a chatbot that provides online service. The 128,000-token length enables a longer, more complete interaction between customer and company. Or imagine an in-house security application that manages access to application data based on a user's privileged access control.
Mistral NeMo was trained on the Nvidia DGX Cloud AI platform, utilizing Megatron-LM running 3,072 of Nvidia’s H100 80GB Tensor Core GPUs. Megatron-LM, part of the NeMo platform, is an advanced model parallelism technique designed for scaling large language models. It effectively reduces training times by splitting computations across GPUs. In addition to speeding up training times, Megatron-LM trains models for performance, accuracy and scalability.
Nvidia continues to build its AI support with partnerships like the one with Mistral by making AI frictionless for any organization, whether it's a large government agency or a tiny start-up looking to create differentiated solutions. This is demonstrated by what the company has done in terms of enabling the AI ecosystem, from hardware to tools to frameworks to software.
Mistral AI Mistral Nemo AI Generative AI Enterprise AI
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