---
title: AI KEynote discussion
weight: 2
---

A podium discussion (somewhat scripted) lead by Pryanka

## Guests

* Tim from Mistral
* Paige from Google AI
* Jeff founder of OLLAMA

## Discussion

* What do you use as the base of dev for ollama
  * Jeff: The concepts from docker, git, kubernetes
* How is the balance between ai engi and ai ops
  * Jeff: The classic dev vs ops devide, many ML-Engi don't think about
  * Paige: Yessir
* How does infra keep up with the fast research
  * Paige: Well, they don't - but they do their best and Cloudnative is cool
  * Jeff: Well we're not google, but kubernetes is the saviour
* What are scaling constraints
  * Jeff: Currently sizing of models is still in it's infancy
  * Jeff: There will be more specific hardware and someone will have to support it
  * Paige: Sizing also depends on latency needs (code autocompletion vs performance optimization)
  * Paige: Optimization of smaller models
* What technologies need to be open source licensed
  * Jeff: The model b/c access and trust
  * Tim: The models and base execution environemtn -> Vendor agnosticism
  * Paige: Yes and remixes are really imporant for development
* Anything else
  * Jeff: How do we bring our awesome tools (monitoring, logging, security) to the new AI world
  * Paige: Currently many people just use paid apis to abstract the infra, but we need this stuff selfhostable
  * Tim: I don'T want to know about the hardware, the whole infra side should be done by the cloudnative teams to let ML-Engi to just be ML-Engi