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HanaBothWays t1_jbjtj4n wrote

It’s a race to develop better Large Language Model tech, but if you are in a sector that deals with sensitive data and these tools pose a risk of inadvertently disclosing that data (because the tools send everything back to “the mothership” for analysis), being an early adopter is maybe not such a good idea.

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NoSaltNoSkillz t1_jbkm19o wrote

If you localize the instance within the company, or more specifically, within the teams with access to that data already, and run different instances for those outside of that group, its less of a problem. The model being local, and only allowing input local should limit the risks, although if it is still scrapping current data, who knows, could be a risk poin

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HanaBothWays t1_jbko8au wrote

Yes, but to ensure you have a model that’s behaving in that way, with standardized controls, you need to first established what those standardized controls are and then figure out some kind of auditing and certification framework for saying “this version of the tool works that way and is safe to use in an environment with sensitive information/regulated data.”

These organizations shouldn’t be trying to roll their own secure instance of ChatGPT (they wouldn’t even know where to start) and I bet they don’t want to.

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