Is your startup an AI company? — A practical guide for CEOs

In case you’ve been hanging out with the technology groundhog in its cave: we’re in the midst of an AI spring. The past two years have seen a resurgence in excitement around our ability to model human-like intelligence in computer algorithms. This excitement has a number of catalysts, not least of which is the enabled application of deep neural networks to a multitude of fields by the advancement of Moore’s law.

For the average person, the AI spring is a period of unbridled excitement: your iPhone will transcribe your voicemails so you don’t have to lift the phone to your ear, Facebook will translate the posts of the friends you made during that one summer in college in Puerto Rico, and your Alexa can tell you interesting trivia about Star Wars.

But the life of a startup CEO is not so simple. You see, our founders have been presented with a serious conundrum.

Are they building AI companies or are they not?

Even a year ago, this question wouldn’t have been that hard. The answer was just “no”. No quibbling about the demarcation between cool algorithm and expert system. No scoffing at the classification of linear regression or basic probabilistic classifiers. Just no.

But these pedantries now matter. “AI company” is no longer a red badge of courage to be worn by those pining for a lost era of 80s optimism. That term now means money. You see, AI companies don’t play by the same rules as the pedestrian startups toiling away on the mortal plane. They don’t generate revenue. They get scooped up by Google, Facebook, and Apple for $5M+ per employee before ever releasing a product.

To understand the implication here… imagine you’re a well-to-do technologist getting by on your $50K-$150K/year paycheck. Shouldn’t be that hard for most of us. Now imagine that you could call up 3 of your buddies, incorporate in Delaware, then collect a cool $20M from Google in exchange for a contract to continue to work at Google for a year. Compelling enough reason to think about the “AI company” epithet?

The hypothetical is obviously tongue-in-cheek, but this is a very real conundrum for hundreds of founders out there today. There’s no clear definition of artificial intelligence in general, so of course there’s no definition of what constitutes an “AI company”. All the founders know is that if they do it right, they can take that expertise straight to the bank.

So how do you know?

Without further ado, I present to you my official criteria for when and why you should call your company an AI company:

1. You have a working deep neural network of any kind in your product release.
2. You have fewer than 10 engineers and at least 1–2 of them have an MS or PhD in CS, specializing in machine learning.
3. You have more than 10 engineers and >25% of them are working with some type of machine learning more complex than polynomial regression or naive Bayes classifiers.
4. You have a proprietary semantic graph.
5. You have an expert system complex enough that it feels like AI.

I feel bad about #5. It’s the only criterion that you can’t objectively assess. But I refuse to adhere to the “ML is the only AI that matters” mantra. So if you’re not sure if you qualify under #5, shoot a link to your pitch deck to me on Twitter and I’ll play referee.

Why is this list necessary?

I’m glad you asked. You see, the myriad riches and fame that await “AI companies” are so tempting that many of our entrepreneur brethren have decided to self-identify as such without just cause. It’s gotten bad enough that the pendulum is beginning to swing the other way: my fellow investors are beginning to dislike it when they’re pitched by an AI company. Their frustration with the duplicity has simply become too much for them to bear.

So as a bonus, here is the mirror list — the criteria that are insufficient to justify calling yourself an AI company:

1. You registered a .ai domain name.
2. You made an algorithm.
3. You have machine learning on your product roadmap.
4. You know what a neural network is.
5. You built a chat bot.

And that’s it!

If you disagree with any of my criteria, keep it to yourself. If you want to thank me for my wisdom, please reach out on Twitter to share your praise!