Joanne Chen, general partner at Foundation Capital, breaks AI startups into three buckets: intelligent automation for workflow tasks, machine-learning infrastructure for data and model building, and AI-enabled cybersecurity against deepfakes and poisoning attacks. The categories shape where the firm invests.
One thing I noticed is that there are so many new AI companies around, particularly generative AI companies. Do you have a sense of how you might go about categorizing them? Are there some important areas that are developing?
Sure. So from our standpoint, we've been investing kind of in applied AI for the last almost 15 years now. There's three areas that we typically look at broadly. One is the application of AI. So what we call intelligent automation.
Meaning.
Automation of workflows, tasks, decision making. Think of AI applied to marketing or sales, or to an industry like legal or logistics. That's one big bucket. Or fintech, that's one big bucket. The second is machine learning infrastructure, which is all the tooling and all the infrastructure necessary in order for companies to capture data, clean data, process data, and use that to leverage machine learning and AI. And I think the third bucket, which I think is super interesting that we are spending a lot of time in, is looking at cybersecurity. Because as the tools get more powerful, as AI gets more powerful, tools that are misused are similarly are getting more powerful. And therefore, how do you counteract things like fake content that's easier to generate and less costly to generate today? How do you counteract. Hackers are now trying to do model poisoning or data poisoning and a whole bunch of other, you know, how are you defending against phishing attacks that are now sounding more realistic? Right? You get an email saying, please click this link and etc. So those are. There's another really big bucket that.
