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>Now, how would you know? What steps would you take to that you suspect these people did not?

Hire two or three ML people for the VC firm and have them audit the company's code. Anyone with some engineering experience is going to be able to tell if the company just shows you random tensorflow code or has actual data and a codebase.

With all these blockchain and AI mumbo-jumbo companies it would probably be a good idea to have more tech workers around rather than just business types.

That is scenario #1. What about scenario #2?

> very optimistic about their chances, and about their ability

this is the very definition of due diligence...you don't take their opinions as fact. to answer how:

* meet with their senior engineers * review code * talk to former colleagues * talk to former professors * review any academic papers, blogs, github repos * talk to customers or MVP users

If you don't have the first hand ability to directly evaluate their AI technology, or an extended network who can assist, you should not be investing in AI startups.

well if they aren't lying and the investors have an accurate picture of what the company is actually up to then there's no problem, that's how venture capital is supposed to work, VC investment is always risky.

But there's an increasingly large amount of companies that are purely selling snakeoil that is way beyond any sort of grey area. You just need to look at the infosec scene.

Although I haven't quite cured cancer yet, I'm optimistic that if you give me a billion dollars I'll find a cure for cancer. So can I please have a billion dollars?

Good VCs almost never fund the idea, but the team. So, if Atul Gawande comes up and ask that question, he most surely will get it

Sometimes the answer has to be yes, right? Otherwise how can you ever do something expensive which hasn't been done before?

Why would a company allow a VC firm that they haven't received money from allow the VC firm to audit their code? Seems like a recipe for disaster.

Investments goes through "due diligence" between signing a term sheet and closing. During this time, the VC gets to look at the company's financials, legal liabilities, and all the other stuff that they don't get to look at before then.

On the engineering side, it's common for investors to ask for a list of software vendors and open source licenses. It would seem pretty legit to me for an investor to ask an outside firm to audit whether a product's code matches what they claim during the pitch.

I don’t know how common it is.

All I know is that I had a short gig last year to do a code review on a potential acquisition, so this can happen at least sometime.

This was for a much smaller product, though.

for the same reason any company accepts due diligence: they won't get the investment if they don't accept.

Of course all of these are negotiable and not all investors do their due diligence, but it is in a well-performing VC's interest to do so.

I feel the business model of artificial artificial intelligence / fake it until you make it, is a valid business model, unless you obfuscate your progress to investors.

If you can either hire an AWS cluster or an army of cheap human contractors for the same money, and your AI-process relies more on common sense over easy calculations, why would you not hire the human contractors?

They are basically taking Searle's Room, but instead of a robot, they are filling it with necktops/meatbags. If it works, it works. Why reverse the argument? The room is filled with humans, and not a robot, so it can't be (artificially) intelligent? Even if the humans do nothing more than following a tree-script?

I would ask them to write out/sketch out a complete project, from inception, to code delivery, which steps require humans and which steps already have automation. They should already have this. If suspect, walk through it in person.

Remember, the AI hype is a market for suckers. VC's who lose their mind over the AI hype, while they were level-headed when dealing with traditional software companies, deserve this.

From what it sounds like, it is a traditional IT outsourcing (sweatshop) company, with more focus on automation and structuring the process. If they can unify software building blocks (pagination, REST api's, user profiles, ...) and better match experts with glueing these building blocks together, they can be very efficient and low-margin.

Forward-thinking: In 10-20 years, there will be an outsourcing company that is highly reliant on decision and data science. Funding and market fit decides if it is this AI startup or another.

> The purpose of AGI is twofold: first to improve the efficiency of organizations of humans by facilitating communication and access to information, and second, to automate the economy with respect to those functions that require human labor.

> With respect to communication, the goal is to make information easy to find and publish. ... When enough narrowly intelligent experts are added to the network, you should not care (or may prefer) that your conversation be with machines rather than humans.

http://mattmahoney.net/agi2.html

> For all those people asking why the VCs did not catch this: what sort of diligence would you do?

I mean, it claims to do 80% of the work to create an app in an hour. I'd have them demonstrate that - "OK, have it generate one for this random concept I just came up with" - and provide the resulting code for an independent developer to look at.

If the answer is "that'll take a week", there's your tell.

That is a good one. They should do that.

But, as I understand the claim, it doesn't do 80% of the work but are 80% of the way there. Even if you can easily see that they are actually 10% of the way there, and this is just optimism/hyperbole, you may think the approach has merit.

> But, as I understand the claim, it doesn't do 80% of the work but are 80% of the way there.

No, they claim both that it will do 80% of the work to build the app within an hour and that they are 80% done with the app. (Both claims being 80% makes it easy to mistake them for a single claim, but both are stated separately in the article.)

Tangentially, the two 80% claims together seem to me to pretty forcefully bring to mind the 80/20 rule even before considering whether the claims are completely fraudulent.

> I mean, it claims to do 80% of the work to create an app in an hour

No, it claims that it will do that, not that it does do that. If it was “does”, yes, the VC would be able to verify it. If it is “will”—and that's what they are seeking funding to build out—its a lot harder to verify.

If it claims it will do that, it sounds like they should be raising an Angel or Seed round, not a massive A round.

They raised $29.5 million in a Series A round. That sounds like find-product-market-fit money, possibly a bit of growth money -- NOT pre-product money. You dont need to raise $30M to go from pre-product to product.

The financiers were Swiss VC firm Lakestar and Singapore’s Jungle Ventures led the financing and participation from Softbank’s DeepCore. I'm surprised this would get past them.

> If it claims it will do that, it sounds like they should be raising an Angel or Seed round, not a massive A round.

That is what they claim, though they claim it's 80% done, too (they seem to like “80%” a lot.)

Disclaimer - I'm a VP E at Engineer.ai

You're more or less correct in your understanding, we're trying to get to 80%, and are certainly not there yet. The other thing to keep in mind is that there's a lot more than goes into developing software than just code.

We've already been able to automate problems such as selecting the optimal creators (developers, QAs, designers) for a given project from our capacity network, the ability to price out and estimate timelines for a project (something that takes our competitors 2-3 weeks), onboard and evaluate engineers on our platform, predict, arbitrage and scale cloud infrastructure for our client's projects, along with a bunch of other areas.

There's definitely a long way for us to go, however we have been able to show proven success on these problem areas already.

but how is the accuracy of your quicker timeline estimates? being faster isnt always the only important factor.

however i disagree with your third paragraph, you have not solved any problems in the problem area you are raising money for, which is AI created software. best i can tell, based on your commentation you are just streamlining onboarding, hiring and estimating. No offense, but none of this has anything to do with AI, IMO. Just a glorified project management and outsourcing company at this point.

For #2, ask them to give a process flow of how an app goes from customer request to executed. Drill down on the differences they claim between their approach and "standard development" or their competitors. Clarify which differences are already realized, and which are optimistic projections.

Thanks for answering. I think this would be a sound approach.

I will point out that different reasonable people -- let's assume yourself and myself -- taking this approach can come to different conclusions as to whether it is worth investing.

It seems like VCs make their money by hoping someone dumber than them is willing to buy out the business, I feel as though generating revenue or sustainable business models is secondary to being able to run massive losses, convince someone else (or the market) that profitably is just a few quarters away so that they buy the business at an inflated price and when it collapses use it as a tax write down.

VC don't care. It's expected that some investment will fail one way or the other. VC's investment approach is to invest in 10 startups and hoping one will hit it big.

if the take is "VCs expect startups to fail so they don't do due diligence..."

I mean you can already tell how ridiculous that is just by laying it out

They do do due diligence. I meant they don't care if the due diligence turns out to be wrong because it's part of the risk profile of the investment. This was a response to GP's question of how could VC's due diligence miss the mark so badly.

It's not an unsolvable problem. Software is much easier to read than to write. It's much easier to see if something works than to make it yourself.

Yes, but let's say they are just exploring the problem but they haven't solved it.

You can see that they are breaking the problem into various cost estimates, and other features, and just running a simple regression to figure out which features they should target for automation.

The problem with ML is that you don't know now if it will work. You just have an intuition that, eventually one of these areas will be able to be automated.

You notice that their approach to the front end is to make various modules (log in etc) that the AI can automatically deploy in various starter packages.

Kind of simplistic at the moment, but maybe it will yield something?

>Software is much easier to read than to write

If you mean software is easier to use than create, sure. But if you mean it's easier to understand existing code than write new code, countless rewrites suggest it's not so simple.

Not quite sure that that's even true

You have not read much PERL or J for that matter then :)

Of course there is plenty of unreadable code in any language.

Javascript after Babel and Webpack is done with it is pretty near unreadable as well.

In fact pretty much most autogenerated code is horribly annoying for humans to read.

Do a quick audit. Get a technical person to submit a sample, and find out what their AI returns. The result to examine should be almost instant.

You'd be surprised. Investor tech due diligence is often very, very light. More than likely nobody needed to be tricked.

if the company was lying to VC's, is it possible for them to recoup their investments outside of a civil lawsuit? I'm imagining some sort of criminal fraud investigation could happen, but dont really know.

>if the company was lying to VC's, is it possible for them to recoup their investments outside of a civil lawsuit?

It's all a game. The founders are friends with VCs, then when they fail out of the startups, they join the VCs.

From my perspective it is all a game against the foolish and greedy LPs.