2023
Kevin Scott said he had been experimenting with Databricks' 12-billion-parameter Dolly 2.0 model, which runs on a single machine.
“I was just playing around yesterday with, uh, that 12 billion parameter, uh, Dolly 2.0 model from Databricks”
Topic
Databricks
18 facts from 11 episodes, in date order. These are what speakers said on the shows, each linked to the moment it was said. They aren't independently verified.
2025
Reganti says a paper from UC Berkeley and Databricks researchers found about 74 to 75 percent of enterprises surveyed named reliability as their biggest problem, which made them hesitant to deploy AI products to users.
“about seventy four, seventy five of the enterprises that they had spoken to. Um, their biggest problem was reliability, and that's also why they weren't, uh, comfortable, um, deploying products to their end users”
2026
Todd McKinnon said Palantir, Snowflake and Databricks let companies pull data into one warehouse rather than connecting AI agents to many separate systems.
“Cause what they allow companies to do is instead of having to actually connect their agentic enterprise to all these separate systems, they pull it into one data warehouse.”
Undated
Aidan Gomez cited Databricks and Snowflake as independent database companies that succeeded without belonging to a big cloud provider.
“fantastic companies like Databricks and Snowflake, which are independent”
Undated
Some Airtable customers pull data from Snowflake or Databricks into Airtable to build operational workflows.
“now we have a lot of customers who are pulling in data from, for instance, Snowflake or Databricks into Airtable”
Undated
Ramaswamy says the three hyperscale cloud providers would like to own the data space, but Snowflake and Databricks exist as independent successes.
“The three hyperscalers would love to just own the data space like they own any other space, but yet there's Snowflake, there's Databricks”
Undated
Ramaswamy says Snowflake's relationship with Microsoft was initially mediocre because Microsoft had a first-party relationship with Databricks and was conflicted about its Fabric product.
“Among the earliest places where, uh, this went to work was in our relationship with Microsoft, which was okay, but not that great.”
Undated
Ali Ghodsi said Royal Bank of Canada built agents with Databricks that begin working as soon as an earnings report is released.
“Royal Bank of Canada, uh, built agents with us that basically take as soon as an earnings report comes out.”
Undated
Ghodsi said Databricks customer Merck created a model called Teddy, which stands for transformer enabled drug discovery.
“customer Merck, uh, that in the life science space created a model called Teddy. Teddy stands for transformer enabled drug discovery.”
Undated
Ghodsi said Databricks' early attempts to automate software engineering failed because of how people were organized, not because of the AI.
“initial attempts at automate, a lot of the software engineering at Databricks kind of failed. Even there's nothing wrong with the AI, the problem is the humans and how we were organized.”
Undated
Ghodsi said Databricks' finance team moved from Excel to Python and machine-learning forecasting models built first by an external data science team.
“finance have kind of moved from Excel to Python, uh, largely at Databricks”
Undated
Databricks acquired MosaicML roughly two years before the interview, according to host Nathan.
“Databricks acquired this company called Mosaic ML not too long ago, maybe two years ago now”
Undated
Nathan says Databricks CEO Ali Ghodsi told him the continued pre-training product was discontinued and Mosaic became an in-house research unit.
“and he said, we killed that product, so they basically turned Mosaic into a in-house research unit.”
Undated
Tim Crawford said data used by AI agents may sit in systems of record outside central repositories such as Snowflake or Databricks, each with its own governance.
“that data may not exist within a central repository like your Snowflake repository or Databricks or whatnot.”
Undated
Samaya AI recently announced new investment from Nvidia's venture arm NVentures and from Databricks Ventures.
“you also announced recently a new investment from N Ventures, that's Nvidia's, uh, venture arm, as well as Data Bricks Ventures.”
Undated
Chris Slovak says that about two to three years before the recording, many companies bought modern data warehouses such as Databricks or Snowflake.
“two, three years ago, everybody purchased a modern data warehouse, whether it's a Databricks or a Snowflake.”
Undated
Slovak says many companies are still in migration cycles of about two years to move data into centralized platforms.
“many, many companies are like, still like smack dab in these two year long cycles to migrate and import.”
Undated
Slovak says a retailer's program to move its data into Databricks and run a report would likely still be about twelve months away.
“But that program is probably still twelve months out.”
Episodes
- 16 Feb 2026CIO Agenda 2026: The Enterprise AI Promise | CXOTalk #90955m
- 30 Mar 2026Okta's CEO is betting big on AI agent identity1h 13m
- 10 Jun 2024AI will make money sooner than you think, says Cohere CEO Aidan Gomez1h 15m
- 1 Apr 2026How AI is reshaping Wall Street37m
- 6 Nov 2025Meet Snowflake Intelligence: A Personalized Enterprise Intelligence Agent with Sridhar Ramaswamy42m
- 24 May 2023Going Full Send on AI, and the (Positive) Impact of AI on Jobs, with Kevin Scott, CTO of Microsoft54m
- 23 Dec 2025AI Enterprise - Databricks & Glean | BG2 Guest Interview45m
- 11 Jan 2026Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google, and Amazon1h 26m
- 12 Sep 2024From No-Code to AI-Powered Apps with Airtable’s Howie Liu1h 12m
- 13 Aug 2026The Predictive Model Reshaping Retail Operations at Scale - with Chris Slovak of Unframe37m
- 14 Jan 2026Snowflake VP of AI Baris Gultekin on Bringing AI to Data, Agent Design, Text-2-SQL, RAG & More1h 36m