Continuous learning

Continuous learning in the federal learning context

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Continuous learning in the federal learning context

Federated Learning is a process where distributed devices, each with its own store with local collection data, can contribute to Global Machine Learning Model without transmitting the data itself. Keeping local data reduces Federated Learning both network traffic and protects data protection. Continuous learning is the process of constantly updating a model when new data … Read more

Updating large language models by direct editing of networking

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Updating large language models by direct editing of networking

One of the major attractions of large language models (LLMS) is that they encoding information about the real world. But the world is constantly changing, and an LLMS information is only as frown the data it was trained on. Training an LLM can take months even when the task is parallelized across 1,000 servers, so … Read more