How To Build a Defensible A.I. Startup

Two ways for an AI company to protect itself from competition: (a) depend not just on AI but also deep domain knowledge about a particular field, (b) have a very close relationship with the end users.

However, a key risk with several of these startups is the potential lack of a long-term moat. It is difficult to read too much into it given the stage of these startups and the limited public information available but it’s not difficult to poke holes at their long term defensibility. For example:

• If a startup is built on the premise of taking base L

... See more

Disruption Theory & risk-aversion don’t apply

Incumbents typically cede market space to startups wherever there’s new, unproven technology or a new, unproven market, especially in spaces where they can’t use past data to predict the future. But in AI, they’re rushing to embrace new technology and uncertain markets, spending historic amounts of ... See more

Entrepreneurial Strategy There are four things an entrepreneur needs: a good idea, a good team, a good product, and a good business model. Interviewing customers, assessing the market, building a MVP, and iterating are all tactics. In the long run, how do we dominate a significant market? In the short term, entrepreneurs tend to focus on a large ma... See more

Of course, there are major ethical issues to work out—leaps forward in technology often walk a fine line between deeply-impactful and dystopian. Among the questions we need to figure out:

• Who is responsible for AI’s mistakes?


• Who is the creator of an AI work? Is it the AI? The developers? The person who wrote the prompt? The people whose work was use

... See more

Another issue is low tech defensibility. In the AI world tech defensibility is harder to achieve because new/revolutionary models are being developed mostly in open, academic settings and so are available in open source.