Good day. Staying on the bleeding edge of artificial intelligence is mandatory these days—even for companies at the forefront of AI. So far this month, two key AI players have turned to venture investing to keep their edge—though in different ways.
Last week, San Francisco-based Databricks, a data-analytics software company riding a surge in growth from AI, launched a startup accelerator for AI pre-seed and seed startups. And earlier this month, cloud computing provider CoreWeave launched a venture arm to invest in AI startups.
Databricks’ initiative, called the AI Accelerator Program, will write checks of up to $250,000, provide mentorship and connect founders with prominent venture firms in its network. Databricks said the accelerator will complement the company’s venture arm, which targets Series A or later startups.
The accelerator has made five deals to date, spanning sectors such as enterprise automation and security.
WSJ Pro spoke with Andrew Ferguson, a vice president at Databricks Ventures, who will oversee the accelerator. The interview has been edited for length and clarity.
WSJ Pro: We’ve seen at least a couple of initiatives just this month by leading AI companies to tap into the nascent startup world. Why are we seeing more of this?
Ferguson: I know the CoreWeave guys pretty well and we traded notes as they were setting up their program. Startups are always going to be pushing the boundaries of what's possible with a platform like ours. For us, this is an ecosystem-focused play. We want to have a thriving ecosystem of AI-native companies that are building their businesses on top of the Databricks platform. That will be great for the startups because they'll have a fantastic data AI platform on the back end.
WSJ Pro: What is Databricks' strategy with the accelerator and how will it work in conjunction with Databricks Ventures?
Ferguson: Early-stage companies are great at providing rapid and honest feedback on our platform. They can use the full capabilities of our platform and provide feedback to us that makes our platform better for our 20,000 enterprise customers. Another strategic benefit is we have a lot of customers who have data in Databricks, and over time, we want to build an ecosystem of AI-first startups that provide more data options to our customers.
WSJ Pro: Can you offer an example of this?
Ferguson: Of the initial companies in the program, a couple are in security. Databricks is often used as a data lake for security companies, and so it’s a win-win if we can provide security-related tools from a startup that a customer can use.
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