Artificial Intelligence, Real Opportunities

July 28, 2016 | By: Carolyn Goard

How to capitalize on Artificial Intelligence and Machine Learning investments

By Boris Wertz
Founding Partner, Version One Ventures

There’s no denying there’s been an explosion in machine learning (ML) and artificial intelligence (AI) activity. Whether it’s Apple’s Siri or Amazon’s Alexa, some level of artificial intelligence has become commonplace in daily life.

This outbreak of innovation is the result of a few things. Chips have been getting progressively faster and cheaper (Moore’s law) for the past five decades. It’s now cost-effective to put a computer in virtually anything. With smartphones, wearables, tablets, drones, kiosks, IoT, etc., computing is taking place, non-stop, all around us. It’s cheaper than ever to gather data.

There are sensors in your phone and smartwatch; sensors on industrial equipment in manufacturing plants; on warehouse shelves in distribution centres and your refrigerator at home. Drones can cheaply gather large amounts of data. All of this means there’s widespread availability of large data sets. AI systems get better as more data is collected, so cheaper data gathering will lead to better, smarter and more useful AI products.

As an investor, what’s really exciting about AI/ML companies is the potential for strong data network effects. The more data an ML platform gets, the better its predictive power and user experience. This means that if a company can build up a proprietary data set, it’s very hard for a competing platform to replicate the experience.

At Version One, we’re always talking to technology start-ups that leverage AI/ML. And, we’ve developed several AI/ML investment themes that we’re actively interested in right now:

Autonomous vehicles and drones

Recent advances in computer vision and AI have accelerated the development of autonomous vehicles and drones. This spring, General Motors acquired Cruise Automation Inc. — a Silicon Valley company that develops autonomous-vehicle technology — to speed up its efforts to develop self-driving cars. But there is much more potential in this space beyond automobiles. For example, we’ve invested in Vertical AI; they’re using computer vision-guided robotics to turn drones into aerial filming tools.

Commoditized robots

Amidst all the advancements in robotics, there are many applications that are still conducted manually, or rely on very expensive machinery. A lot of current industrial and research robots are still in the mainframe age; they’re expensive and, therefore, only available to a few large institutions. Start-ups such as OpenTrons are democratizing these tools. OpenTrons offers a $3,000 robot for life science applications that’s controlled by a web browser and doesn’t require complex coding on the backend. In other words, they’re making robots available to more organizations and for more applications.

Automating enterprise processes

Virtually every single function in an enterprise can be reinvented by AI. There are opportunities to build highly specialized AI tools for specific vertical and horizontal applications — such as customer service and enterprise knowledge.

Data analysis

Today’s drones and sensors are charting new territory and capturing data that was never before possible. Data is more granular and captured at a greater frequency. For example, drones with cameras perform routine inspections on crops or oil-and-gas assets. Sensors continually monitor the status of production line machinery. And, fixed cameras are used for security applications.

But while hardware is producing more data than ever, businesses need new storage, analytics and search tools in order to make sense of all this new data. Data on its own isn’t very useful; that’s why we’re looking for start-ups who can build the right analysis tools for this deluge of data.

Going Forward

Building a successful ML/AI start-up is hard, but we see a very bright future. If you’re interested in seeing the full breadth of innovation happening today, Shivon Zilis mapped out the entire machine intelligence ecosystem at the end of 2015. As artificial intelligence continues its trajectory into the mainstream, consumers and enterprises will demand more intelligent automation and we’ll be looking for those companies who can turn data into magic.


*Boris Wertz is the founding partner of Version One Ventures, an early-stage venture firm based in Vancouver and Silicon Valley. Read Boris’ recent CVCA blog ‘The View from Here: Best Practices to thrive in Canada’s current & future VC environment’.