[gaius]

Faced with the impossibility of determining whether a technology is intelligent or not—since we don’t know what intelligence is—Silicon Valley’s funders are left instead to judge the merit of a new idea in AI according to the perceived intelligence of its developers. What did they study? Where did they go to school? These are the questions that matter

This is a perfect summary of the VC situation today. Too much money chasing no-one knows what exactly, but they're sure they'll know it when they see it.

[graycat]

From all I've been able to see, that statement

"... judge the merit of a new idea in AI according to the perceived intelligence of its developers."

about information technology VCs and AI is just totally wrong: I don't believe VCs do that. Why? Generally, from 50,000 feet up, it's too far from the norms of the accounting, banking, and investing communities respected by the limited partners of the VCs. Uh, the limited partners (LPs) are where the VCs get nearly all the money they invest, and the limited partners are conservative people, managers of pension funds, university endowments, etc. Not only do the VCs not do that, the LPs won't let the VCs do that!

Instead, about the shortest believable view I can see is, VCs look for traction that is significant and growing rapidly in a market large enough to permit a company worth $1+ billion in a few years.

The VCs view of traction is a weakening of the usual measures the accounting, banking, and investing communities use and respect of audited revenue and earnings.

So, sure, the best form of traction will be earnings, then next best, revenue, next best lots of interested customers, e.g., advertisers willing to pay for eyeballs, then last best, just lots of eyeballs. In these norms, intelligence, brilliance, AI, technology, etc. are mostly publicity points, window dressing, the wrapping paper on a birthday gift, and with a dime won't cover a 10 cent cup of coffee.

In a sense, the VCs have a good point, more from insight into humans and the real world than anything in a pitch deck: (1) With technology, it's too easy to push totally meaningless, useless BS. (2) Carefully studying core, deep, difficult technology is just too darned difficult to be practical for the VCs.

Or the investors believe in a Markov assumption: The future of the business and the technology from the past are conditionally independent given the current traction, its rate of growth, and the size of the market. To be clear, this Markov assumption does not say that the technology and the future of the company are independent.

The stories in the OP about the company Predata, to abbreviate "predictions from data", are good: The company was floundering around with guesses about what would work, e.g., for predicting terrorist attacks, that were like something from smoking funny stuff.

But here is one big place the VCs and technology are going wrong: We do have some terrific examples of how to do well. The examples are from the past 70+ years of the unique world class, all-time, unchallenged grand champion of using advanced, even original, technology for important practical results -- the US DoD.

A grand example is GPS. GPS was by the USAF, but it was a refinement of an earlier system by the US Navy, for navigation for the missile firing submarines and started at the Johns Hopkins University Applied Physics Laboratory JHU/APL. At one time I worked in the group that did the original work and heard the stories. A key point: The original proposal was by some physicists and almost just on the back of an envelope. Soon the project was approved and pushed forward with a lot of effort. Then, presto, bingo, it all worked just as predicted on the back of the envelope. E.g., a test receiver on the roof navigated its position within one foot, plenty accurate enough for the US Navy.

So, net, for project selection and funding, here is the shocking, surprising, point that the VCs miss: Really, given the back of the envelope work, the rest was relatively routine and low risk.

And the past 70+ years of the US DoD is awash in comparable examples.

In blunt terms, the US DoD has a fantastically high batting average on far out projects evaluated just on paper. Given good evaluations of the work just on paper, the rest is relatively routine and low risk.

Well, that project funding technique does not fully solve the problem of the VCs: The VCs also need to know that the resulting product will have big success in the market. But for that there is an okay approach: The dream product would be one pill taken once, cheap, safe, effective, to cure any cancer. In that case, the technology is so good for such an important practical problem in such a large market that there's no question about making the $1+ billion. So, from this hypothetical lesson, net, need the technology to be the first good or a much better solution, a "must have", for a really pressing problem in a big market. So, right, this filter would reject Facebook, Snap, and more. So, right, need to start with a really big problem where with new technology, say, as in the US DoD examples, can get a "must have" solution for a really big problem, and Facebook and SNAP are not such problems. Just what are such problems? That's part of the challenge. But with current VCs, come up with such a problem and a solution on paper, with brilliant founders, with AI, etc., then still will need more than a time to cover a 10 cent cup of coffee. Again, to get VCs up on their hind legs, bring then good data on traction, significant and growing rapidly in a large market; if the secret sauce technology helps, fine; brilliant founders, fine; even if there is no technology, fine; in all cases, what really matters is the traction.

[untangle]

I think that you are over-generalizing. VCs use a number of disparate investment theses, including gut feel and betting-the-team in a "hot" (trendy?) space. Another dynamic is funding a team that previously produced a big win for the VC firm (as appears to be the case here).

And do you have a reference for the "fantastically high batting average" of US DoD research? Are you familiar with the SBIR program, for example?

I would judge that neither DoD/DARPA nor VCs have a great batting average. But both have some spectacular wins.

[graycat]

> VCs use a number of disparate investment theses

To be more clear, I believe that such other issues, often mentioned, some on the Web sites of VCs, are nearly all just smoke to hide what I listed as the main issues. In particular, of course, I was pushing back against the statement I quoted from the OP -- their statement was much worse than mine!

But here on HN, I warn entrepreneurs who have already sent 100+ e-mail pitch decks to VCs: I gave my best guess on really how VCs select deals.

Batting average reference? I'm not considering the SBIR program at all. E.g., GPS, coding theory, e.g., as part of radar, lots more in high end radar, e.g., phased arrays, Keyhole (a Hubble, before Hubble, but aimed at the earth), the SR-71, the F-117 stealth, the SOSUS nets and adaptive beam forming sonar, some of ABMs, a huge range of parts of the SSBNs, high bypass turbo fan engines, the nuclear power reactors on the submarines and air craft carriers of the US Navy, and much more were not SBIR projects. I am drawing from early in my career in applied math and computing for problems of US national security within 100 miles of the Washington Monument and comparing with what I've seen in VC work.

The Navy's work on rail guns looks darned promising.

For DARPA, yes, they flop a lot, on their batting average, much more than the rest of DoD, but DARPA also has some spectacular wins. E.g., of course, TCP/IP. And they fooled me on their autonomous vehicle "challenge": While I believe that autonomous vehicles are a long way from being ready for real roads with real traffic, I can believe that so far already the DoD has gotten some good progress for some cases of logistics. E.g., one of the issues in Gulf War I was truck drivers. There an issue was that a lot of the drivers for the US were women, and the Saudis didn't like women driving vehicles. So, there was a trick, a deal: The US and the Saudis agreed that when the women were in uniform and driving US military vehicles, they were "soliders" and not women. Otherwise they were still women and could not drive!!!

Uh, the robots of Boston Dynamics are impressive, maybe still less good on legs than a cockroach, but already or well on the way to being useful for the US Army.