Ever since october 2022, the world is mesmerized by the seemingly unlimited ability and potential of Large Language Models. But what happens if you don't have the resources or rights to host it, and you can't risk sending away your data for potential redustribution to third parties? What if superfluous data access trigger more inaccuracy and hallucinations than helpfulness? Or what if you just don't want to use ALL of your resources on training local language models?

Discover how using a Small Language Model can actually work to your favour, using less local resources, provide better accuracy with a more narrow context, and not sending away a single byte.

Duration: normal, including live demo
Audience: DevOps, AIOps, Ops mgmnt, sovereignty, airgapped, open source, cloud native, non-proprietary.