Databricks spent $10M on new DBRX generative AI model

 If you wanted to raise the profile of your major tech company and had $10 million to spend, how would you spend it? On a Super Bowl ad? An F1 sponsorship?

You could spend it training a generative AI model. While not marketing in the traditional sense, generative models are attention grabbers — and increasingly funnels to vendors’ bread-and-butter products and services.

See Databricks’ DBRX, a new generative AI model announced today akin to OpenAI’s GPT series and Google’s Gemini. Available on GitHub and the AI dev platform Hugging Face for research as well as for commercial use, base (DBRX Base) and fine-tuned (DBRX Instruct) versions of DBRX can be run and tuned on public, custom or otherwise proprietary data.

“DBRX was trained to be useful and provide information on a wide variety of topics,” Naveen Rao, VP of generative AI at Databricks, told TechCrunch in an interview. “DBRX has been optimized and tuned for English language usage, but is capable of conversing and translating into a wide variety of languages, such as French, Spanish and German.”

Databricks describes DBRX as “open source” in a similar vein as “open source” models like Meta’s Llama 2 and AI startup Mistral’s models. (It’s the subject of robust debate as to whether these models truly meet the definition of open source.)

Databricks says that it spent roughly $10 million and two months training DBRX, which it claims (quoting from a press release) “outperform[s] all existing open source models on standard benchmarks.”

But — and here’s the marketing rub — it’s exceptionally hard to use DBRX unless you’re a Databricks customer.