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.
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.
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.
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.
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.
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.
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.
> 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.
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.
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.
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.
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.
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.
That is what they claim, though they claim it's 80% done, too (they seem to like “80%” a lot.)
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.
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 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.
I mean you can already tell how ridiculous that is just by laying it out
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.
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?
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.
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.
I don't know the company or the details. Assume two scenarios:
1. The target company is willing to lie, fabricate code, mix in tensorflow etc.
2. The company will not outright lie, and will answer honestly. However, they are very optimistic about their chances, and about their ability to deliver some sort of AI-enabled solution.
Right now they have -- let's hypothesize -- some sort of funnel and they route bits of code to different developers. They think they will replace some of it. They are using various AI libraries.
Suppose you believe that even if the AI won't eventually code the whole app from scratch, it will make huge strides in certain areas that we don't even know about. These strides will dramatically reduce the cost of making an app (eventually, you believe). Suppose you think that this company is basically an exploration of those areas.
In other words, be generous to the diligence undertaker.
Now, how would you know? What steps would you take to that you suspect these people did not?
(Because this is the internet and no one knows for sure: this is a real question, and not a rhetorical attack on people asking why VCs were "tricked")