Investing in Artificial Intelligence
Venture Capitalists are always looking for the next big thing, the next big industry or company to disrupt the current state or things. So, naturally you would expect investors to look at artificial intelligence (AI) companies as the big sector. However, what happens when AI is seen not as a sector but as something that will be embedded in everything that we do and be a part of every company similar to how electricity or the internet have become the standard and expected everywhere. How do investors wrap their head around that?
Cognilytica recently interviewed John Frankel, founding partner at ff Venture Capital, on the AI Today podcast to get his thoughts on investing in AI. Below is an excerpt from the interview. You can check out the full podcast, and a full transcript, on the Cognilytica site.
AI Today: Can you give us a quick recap and highlights of some of the things that you talked about at the recent NYC Future Labs Summit particularly around AI and investing.
John Frankel: I think the first thing to set in frame is really: why is AI different? We can talk about where AI is now but I think a lot of commentators have addressed that. We think AI is different and isn’t just a sector. And if you go back 20-25 years ago, we had this thing called the Internet and cloud computing and it’s had a massive impact and it wasn’t just the sector. It was a sort of architectural change in the way things were done. And then 10 years ago, mobile came along, and initially we talked about companies being mobile — start-ups were ‘mobile first’. You know, all built around SoLoMo, social location, mobile — but these days we don’t use those terms, it’s just embedded in everything. And today when we look at AI, we don’t see AI as the sector, we see it as something that will be embedded in everything that we do and every company in the same way — in the way that electricity today is embedded in everything that companies do. And then for AI in particular, because you have companies such as retail, financial services, advertising, media fashion companies — all of which are being disrupted by AI start-ups and based in New York — there’s a lot of the main specific talent that is sitting right next to this. And that we think is just a great place to grow AI companies. We have a number that are growing very strongly in New York and there are new ones being founded everyday.
AI Today: New York has a lot of investment, a lot of VCs, and a lot of start-up activity going on. It’s a pretty thriving area. ff Venture Capital also invest heavily in Artificial Intelligence companies. Can you tell us where you feel the current state of the AI market is, as an investor?
John Frankel: I’ll give you a little framework here; as I said before, AI’s been on the cusp of mainstream for about 50 years, and there’s been AI winters along the way and we’re now in the middle of an AI summer. And we do run the risk that there is too much hype in the space and that expectations run ahead. An example of that, I think, is autonomous vehicles, where if you read the press it feels like in 2021, maybe 2025, you or I could go to a local dealer and buy a level five autonomous vehicle. One that may or may not have a steering wheel, but doesn’t need one. And when I speak to leaders in the field, some say ‘maybe, but there’s a lot to be invented’ and others will say ‘maybe by 2040 you’ll have that’. Now what you’ll probably see is in constrained environments, ring-fenced environments, on a rideshare basis you’ll start to see autonomous vehicles as early as next year. And then over time, the ring-fencing will get wider. But individuals owning autonomous vehicle is way off for a number of reasons, including political, societal and economic reasons, which I won’t go into now. But the hype is very high. And people have to change their behavior. If you’re in San Francisco, no one jaywalks; if you’re in New York and it’s 4:30 on a weekday, the density of people walking on the street and on the sidewalk are about the same. And I think in New York, if they’ll see an autonomous vehicle coming towards them, they will just stand in its way. So I think there’s a lot that needs to be worked out. I can use that as an example: when I look at it, the first wave of AI recently we saw, were engineering people going after almost research projects that may or may not end up being businesses. And we saw the large tech companies buy these teams in as aquihires and elsewise, to build out that very deep talented pool for the consumer facing products. And we’re seeing the benefit of that today and products you buy from Google and Apple and Amazon and the like.
The second wave that we saw was horizontal ones, where they said: we’re going take a problem like image recognition, and we’re going to be the place you go for that (or voice recognition or the like). And some of those tech stacks were again bought or developed within these large technology companies. And because a lot of the people who work there still have a foot within research, there’s been a bias for them to open source the solutions and open up the APIs. And so a lot of those horizontal solutions today can be replicated at a fraction of the cost they took to build, because a lot of the technology which was very difficult and unknown then, has become very facile and known.
The third wave — which is the wave we’re really investing around — are companies that are enterprise- as opposed to consumer-focused, and going after specific vertical problems, using a combination of technology and data to build deep network effects. Which allows them to build some barriers to entry around what they’re doing, and doing it in a way that is relatively careful and efficient. I don’t think the lean start-up methodology works well, as a rule, with AI. There’s just too much data processing and customer acquisition that needs to be had to build these barriers. But I don’t think you need a 40 million dollar check just to get into the business either. And so we’re seeing some really interesting companies around the space.
Artificial Intelligence and the ideas around it have been around for decades, but we are finally (hopefully) in a technological position to see our ideas come to light. Will AI become something so common place and intertwined into every day business that people couldn’t imagine a world without it (could you imagine a world without electricity?!)? For companies looking for funding and firms looking to invest, there needs to be shift in thinking from the traditional way we build and evaluate startups. AI is not a sector, but rather a technology embedded in businesses. Embrace that and let’s see just how far AI can take us!
The Cognilytica Take
We’d love to hear your thoughts on this podcast and this subject in general so join the discussion on our Facebook Group AI Today (https://www.facebook.com/groups/aitoday/) or follow us at Cognilyitca.
