In this episode, the DAS crew discussed installing and running large language models (LLMs) locally on personal computers and in business settings.
They covered the benefits of running LLMs locally, including privacy, control over the model, and offline usage. The discussion touched on various open source models like Meta's LLaMA and Mistral.
The hosts talked through the system requirements to run LLMs locally, with powerful GPUs and ample RAM needed for larger models. They mentioned options like using cloud services to run models while still retaining control.
There was debate around use cases, with most hosts currently not seeing a need for local LLMs. However, they acknowledged niche business needs around privacy and intranet search.
The takeaway was that capabilities are rapidly improving, so following LLMs is important even if not deploying now.
Key topics:

Benefits of local LLM installation
Popular open source language models
System requirements and costs
Use cases like privacy, offline usage, intranets
Capabilities improving quickly even if no use case now

Overall, the episode provided an introductory overview of considerations around running LLMs locally. It highlighted how hardware constraints are being overcome to make local models more accessible.

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