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Comment by ramoz | Hacker News Reader

Their goal is to always drive enterprise business towards consumption.

With AI they need to desperately steer the narrative away from API based services (OpenAI).

By training LLMs, they build sales artifacts (stories, references, even accelerators with LLMs themselves) to paint the pictures needed to convince their enterprise customer market that Databricks is the platform for enterprise AI. Their blog details how the entire end to end process was done on the platform.

In other words, Databricks spent millions as an aid in influencing their customers to do the same (on Databricks).

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Thanks! Why do they not focus on hosting other open models then? I suspect other models will soon catch up with their advantages in faster inference and better benchmark results. That said, maybe the advantage is aligned interests: they want customers to use their platforms, so they can keep their models open. In contrast, Mistral removed their commitment to open source as they found a potential path to profitability.

Commoditize your complements:

https://gwern.net/complement

If Databricks makes their money off model serving and doesn't care whose model you use, they are incentivized to help the open models be competitive with the closed models they can't serve.

At this point it's a cliché to share this article, as much as I love gwern lol.

There is always the lucky 10k.

Today I was one

For that reference in particular, feels like you should really share the link as well:

https://xkcd.com/1053/

Demonstrating you can do it yourself shows a level of investment and commitment to AI in your platform that integrating LLAMA does not.

And from a corporate perspective, it means that you have in-house capability to work at the cutting-edge of AI to be prepared for whatever comes next.

> Demonstrating you can do it yourself shows a level of investment and commitment to AI in your platform that integrating LLAMA does not.

I buy this argument. It looks that's not what AWS does, though, yet they don't have problem attracting LLM users. Maybe AWS already got enough reputation?

It's easier because 70% of the market already has an AWS account and a sizeable budget allocated to it. The technical team is literally one click away from any AWS service.

I may be misunderstanding, but doesn't Amazon have it's own models in the form of Amazon Titan[0]? I know they aren't competitive in terms of output quality but surely in terms of cost there can be some use cases for them.

[0] https://aws.amazon.com/bedrock/titan/

Mistral did what many startups are doing now, leveraging open-source to get traction and then doing a rug-pull. Hell, I've seen many startups be open-source, get contributions, get free press, get into YC and before you know it, the repo is gone.

Well Databricks is a big company with real cash flow, and Mistral is a startup so there is a kinda big difference here.

They do have a solid focus on doing so, it’s just not exclusive.

https://www.databricks.com/product/machine-learning/large-la...

> Why do they not focus on hosting other open models then?

They do host other open models as well (pay-per-token).

https://docs.databricks.com/en/machine-learning/foundation-m...

Do they use spark for the training?

Mosaic AI Training (https://www.databricks.com/product/machine-learning/mosaic-a...) as it's mentioned in the announcement blog (https://www.databricks.com/blog/announcing-dbrx-new-standard... - it's a bit less technical)

Thanks. Is this open source - i.e. can it be used on my own cluster outside of databricks?

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