NeMo Megatron is an end-to-end containerized framework that delivers high training efficiency across thousands of GPUs and makes it practical for enterprises to build and deploy large-scale models. It provides capabilities to curate training data, train large-scale models up to trillions of parameters, customize using prompt learning techniques, and deploy using NVIDIA Triton Inference Server to run large-scale models on multiple GPUs and nodes.
NeMo LLM Service includes the Megatron 530B model for quick experimentation with one of the world’s most powerful language models, and helps customers come up to speed quickly with a pre-trained model as a starting point.So, let’s get back to Leslie. How do you prevent an LLM from making stupid mistakes? Well, you can focus the AI on what problems you want it to solve.
What’s more, GPT-SW3 requires one-tenth the data, slashing the need for tens of thousands of hand-labeled records. That opens the door for users to fine-tune a model with the relatively small, industry-specific datasets they have at hand.... [+]NeMo is yet another example of NVIDIA’s software that turns silicon into solutions. It can help customers adopt the power of LLMs, at significantly reduced cost and risk.
I’ve often been asked about the durability of NVIDIA’s CUDA software moat that protects the company from incursions of the startups. The answer is that the question is wrong. It’s not just CUDA, as we have often said before. It is the entire NVIDIA stack of some 14 specific AI frameworks and all the underlying software that competitors will have to replicate. I don’t think they can or will, at least not in the foreseeable future.
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