The gotcha here is that most desirable AI startups SV wants to fund now (understandably) follow a pattern more closely described here: http://www.bradfordcross.

The gotcha here is that most desirable AI startups SV wants to fund now (understandably) follow a pattern more closely described here: http://www.bradfordcross.com/blog/2017/6/13/vertical-ai-startups-solving-industry-specific-problems-by-combining-ai-and-subject-matter-expertise http://www.bradfordcross.com/blog/2017/6/13/vertical-ai-star... Generally, their advantage is in the way they use data to solve a vertical specific problem. They more "bolt on" AI. AI isn't really the focus of most of these companies. This is just what investors want to hear about. The article here isn't calling them out specifically, but AI infra startups are what are being discussed here as the "hammer looking for a nail" startup. YC funded a few of them including Skymind (my company) and deepgram (mainly audio). There are a lot more of these startups such as vicarious that mainly publish papers but raise tons of funding hoping for a deepmind style exit (they didn't really have a business model). With that context out of the way, I'll also maybe just state some learnings from the other side of the table. Skymind has typically made money trying to reduce dependencies on cloud providers by decoupling the AI infra from google cloud and co from the cloud provider itself. A horizontal play like this is by its nature very hard. We maintain the whole stack including our own framework. We also started in 2014 and have a decent foothold in enterprise. I wouldn't recommend trying to do this in 2017. That being said, one other semi similar horizontal AI startup that is being started are the chip companies. Those are significantly harder to run than even what we're doing. The most common "failed" type of startup that I think of when we think "horizontal" plays are Machine Learning as a service, which is hugely a loss leader for the various cloud providers (some companies are building on top of these providers though). This is where you see Metamind, Alchemy API, Scaled Inference (founded in 2015), even Nervana before they sold were trying to a "nervana asic cloud" among others. Maybe a lot of investors from SV view this as a waste of time dissecting, but I would personally love to see a bit more content on acknowledging some of these trends in the market. The allure of "AI as a service" and the horizontal dev tools infra play is that you can try to build the next AWS similar to what the container and database companies are trying to do. Execution is definitely key for this to work though. Research also can't be the primary focus. I won't comment on what will or won't work there