At Version One, we take a thematic approach to investing and are very focused on start-ups with strong network effects, like marketplaces and social platforms. This year, we’ve been writing about the power of Artificial Intelligence and Machine Learning, and the potential for strong data network effects to emerge with these companies – particularly when start-ups can build proprietary data sets.

Here are some of the AI and machine learning investment themes that we are actively interested in right now (and have already made a few investments):  

Autonomous vehicles and drones

Recent advances in computer vision and AI have been accelerating the development of autonomous vehicles and drones. Everybody has probably heard about Cruise and GM by now, but there is much more potential in this space. We’ve invested in Vertical AI; they’re using computer vision guided robotics to turn drones into aerial filming tools.

Commoditized robots with command line in the cloud

Amidst all the advancements in robotics, there are many applications that are still conducted manually, or rely on very expensive machinery. Startups like OpenTrons are democratizing these tools. For example, OpenTrons offers a $3000 robot for life science applications that’s controlled by a web browser and doesn’t require complex coding on the backend. There is a strong opportunity here to move many current industrial and research robots from the mainframe age to the Cloud/PC age.

Automating enterprise processes

Every single function in the enterprise can be reinvented by AI. We are looking at highly vertical applications, and have already made investments (yet to be announced) in the customer service and enterprise knowledge space.

Data analysis layer for large verticals

Drones and commoditized sensors are making data capture cheaper and better. And as a result, data analysis is more powerful and important than ever before. In some cases, drones/sensors are charting new territory and capturing data that was never before possible. In other cases, data is more granular or captured at greater frequency.

For example, drones with cameras can perform routine inspections on crops or oil and gas assets. Sensors can continually monitor the status of production line machinery (think Industrial IoT). And, fixed cameras are used for security applications. In every case, there’s a strong need to add the right data storage/analytics/search layer to help businesses get the most value from all this new data.

We’ll be making some investment announcements later this year regarding machine learning and AI-driven start-ups. And, we’re always looking for start-ups who are doing great things (or have the potential to do great things) in these areas.