Engineer.ai raises $29.5M Series A for its AI+Humans software building platform
techcrunch.com
techcrunch.com
[0] https://medium.com/@seibelj/the-grid-over-promise-under-deli...
There doesn't appear to be AI involved. A very good business model, but no AI.
What I expected the founder to say was "we've proven people want our product, now we can scale it even further by building the ai tool we always wanted to build," but I don't see that.
I went to my first tech conference when I was 13. One of the hot items was a tool that made programmers unnecessary. It was targeted at cheapskate businesspeople. Decades later the company is long dead. But the suckers are still out there. They think that coding is the hard part, in the same way that they think the hard part about building a house is nailing things together. But in both cases, the part you're really paying for is expertise: good development firms and good homebuilders know how to turn hazy human desires into very specific implementations, while also shaping those desires to be reasonable and achievable.
- Disclaimer, I'm a VP E at Engineer.ai
- Pricing is a Supervised Learning Model.
- Custom Features are a Convolutional Neural Net + NLP.
- Resource Allocation (we tap into capacity of other dev shops) is an OR/ML combination.
- Sequencing of what to do is an ML/SL problem.
- Complexity is a Clustering Problem.
- Grading Devs is a Static Code Analysis (industry standard) + NLP Problem.
- Quality Early Warning is a Supervised Learning + Heuristics (we identify early potential problems based on a developer + feature set history analysis)
- Templates being updated based on features being added by onward customers.
---> Building Blocks
- Features are one or many building blocks
- They communicate through an ESB thats allows a smarter way of messaging between individual areas.
- The ESB allows us to "plug n play" -> today it still needs human stitching but that a scale problem we are looking to fix.
We are step 5 out of 12 steps of the way through the final vision - and the above are at varying stages of deployment (some early, some more established).
What this means to their clients is that if the client hires Engineer.ai to build something, their next client can get the same product for free. Good luck with that, Engineer.ai.
They can do whatever they feel like doing.
Venture investment at this level of sophistication typically involves the purchase of equity in a company with the general expectation that the value of the investment will increase over time, as valued by other actors in the market. However, at this stage there are little to no financial or legal negative repercussions for a company failing to meet this expectation as long as they've acted ethically. (I mean, outside of the value of equity going to zero and having to shut down the company.)
There are forms of investment, or vehicles of financing - venture debt and specific types of convertible notes - that have the expectation of repayment given a timeframe, but they're not typically what we're talking about when we talk about modern venture investment and straightforward equity transactions (like a Series A here).
In fact, YC explicitly invented the SAFE (Simple Agreement for Future Equity) as a way to prevent "bad actor" investors from asking for returns from convertible notes ("repayment") and sinking companies early. The unwritten rule in venture investing in SV was literally, "don't ask for your money back," some Angels were screwing companies over by doing exactly that, so the SAFE codified protection against it into a low-friction investment vehicle.
tl;dr: Investment is not constraint-free, but there is certainly not an expectation of "repayment." It might seem a little semantic (versus, say, "generating returns") but it's important people understand the difference between equity transactions and debt - the constraints exist but they differ and, as such, incentivize behavior, growth and spend differently as well.
- Disclaimer, I'm a VP E at Engineer.ai
That's what most agencies do (even IBM, CGI, etc) but you're doing it through an online interface. If I'm not mistaken, you are leveraging economies of scale to make your offerings cheaper than those of smaller agencies, effectively trying to squeeze them out.
My comment was specific to the marketing. You make it seem like I can get a copy of someone else's app if I just want the exact same thing that someone else got, for next to nothing.
they are just an outsorce provider. plain and simple.
not trying to pick on you (specially as I have nothing to gain doing so), but this is exactly how I deal with them. with the option to have the engineers hosted or remote. Add a beefy ORM with a client UI and they could also claim 50% of the work done by machines...
> Software is the centre of every business today and the market has been waiting for a solution that eliminates technical barriers to build software so that everyone can engage in the new economy,” said Manu Gupta, Partner at Lakestar. “By creating a software powered assembly line combined with the best global human talent, Engineer.ai’s Builder bridges the gap between an idea and a software product to enable it.”
- .ai domain name
- No mention of how they use or define AI
- "AI + Humans"
- Banner picture from science fiction film (Prometheus)
(Disclaimer: I used to work at an AI startup and am generally interested in how companies market themselves)edit: Okay, I'm slightly wrong. I looked it up due to curiosity. This would qualify as the 3rd major ai bubble, but there have been a few minor ones. Also known as "ai winters": https://en.wikipedia.org/wiki/AI_winter
AI winter referring to the lack of funding in ai projects instead of collapse in companies.
Not going to lie. If someone ran for president on just that platform alone, where it's illegal to make any overblown promise/hype on tech, the contenders really need to come up with some good arguments for me not to vote for the hype killer.
I'm just afraid what's going to be the next hype train. The blockchain hype train was just plain dumb. It's a super niche piece of tech with really limited uses. Still cool for that. But will never revolutionize the world. This AI bandwagon is getting out of hand. People think all AI tech is perfect 100% of the time, all the time. It's more, works 93% of the time, 23% of the time.
The next hype tech... scares me what it could be.
But that’s sort of humans in a nutshell, isn’t it?
But take crop circles. Over and god damn over, they're proven to be some bored asshole that went out with a board, some rope, and free time to make shit in a field. But every time a new one pops up, "Oh my god... is it aliens!?!?!"
Every time in tech. Overblown claims are made and shown to be false or limited in scope. By "smart people" towards "smart people". But we still get "No! This will change the world!". "It might change the way we take dumps on the shitter, but not the world." "IT WILL CHANGE THE WORLD!".
Or "Making the world a better place through statistically blockchain distributed interconnected AI designed silicon chips... 2.0"
I mean... it's all a religion. Looking at it in another light. Heavy prayer and belief in things you probably shouldn't. Makes tech people more religious than those that are "religious".
I might be reaching and ranting at this point.
"When a cheap laptop beats the smartest mathematicians at some tasks, but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other – they’re categorically different."
"Palantir takes a hybrid approach: the computer would flag the most suspicious transactions on a well designed user interface, and human operators would make the final judgement as to their legitimacy."
- Peter Thiel, "Zero to One", Chapter 12
Thiel is going long on these AI+human startups.
Yeah, a cheap laptop can do arithmetic faster than 'the smartest mathematicians'. And the smartest mathematicians can do arithmetic faster than many children. Does that make mathematicians and children 'categorically different things' as well? In some trivial sense, sure, but it doesn't preclude any kind of connection between the two, or require some deep new ontological commitments to model.
I'm all for the current practical approach of using 'AI technology' as a human supplemental. But I'd rather not frame it as (what I perceive) as some kind of mystic, dualistic argument. At least not until we know more about both.
I also don't really think Peter Thiel is worthy of being the keystone of any kind of argumentum ab auctoritate in this particular field.
I've read the rest of what you have to say on this, and it is precisely the kind of mysticism that bothers me. There are no means of disproving it, it reduces to dogma in the end, but it's philosophically disingenuous to assert that because computers and people feel like different things in some cases, they must be, and then to argue backwards from there; it's question-begging in the original sense.
https://www.am-nat.org/site/halting-oracles-as-intelligent-a...
If I'm right, then all AI only companies will be beaten by a AI+human company, so we can make market predictions and propose research directions based on the hypothesis. Doesn't seem entirely without technical/financial merit. I make a note of the economic implications at the bottom of the following proof:
https://www.am-nat.org/site/law-of-information-non-growth/
Why do you say it a form of mysticism?
I don't think anyone is positing that that's true forever and all time. It seems reasonable to bet on AI at some point becoming sophisticated enough to outperform AI+human. I think it'll happen shortly after the point where AI can identify a new problem (or class of problems) by itself that it hasn't been taught about & then build new tools to help itself tackle that problem. After that it's the singularity because that process repeats ad infinitum. The only value-add of humans after that is if our creativity is somehow better/different than & can explore problems in ways the AI can't (& even that feels like a very short-lived advantage unless there's some crucial physical/mathematical impossibility standing in the way).
- Disclaimer, I'm a VP E at Engineer.ai
- Disclaimer, I am the aforementioned VP Blockchain at Engineer.ai
Jokes aside, my colleague @sachmans has posted a comment above that should hopefully answer your question on how we use AI. As for how we define AI, as an engineer myself, I'm a little annoyed by how it's become an umbrella term for everything from basic statistical models to ANNs. Unfortunately that is the reality of it - and so we've consciously decided to use it as an umbrella term for the various applications of ML/NLP/NNs that we use internally.
- Disclaimer, I'm a VP E at Engineer.ai
I always have a hard time to see the benefit of code-generation tools in general. If you can generate the code for a piece of functionality, you may as well abstract away primitives for that and make it a one-liner operation in the code you're writing. If that's not possible, it's probably a shortcoming of the language, framework or whatever system you're using (which is admittedly the case sometimes in the real world, because things evolve slowly).
Sounds like just marketing bull. It sounds like they have libraries and they are using them to spin up apps faster. That might have value if the libraries are good but that's clearly not AI.
What if you stuff the Qt docs into a DL model and using the qt source code as training data? Could the network produce usable source code based on docs?
https://en.wikiquote.org/wiki/Charles_Babbage#Passages_from_...
But Babbage’s machine was not différentiable.
Train a series of neural networks in order to provide buzzwords at a fast enough rate to trick actual people with more money that brain to give them money.
Getting almost 30 millions with just vaporware is always impressive. I won't be capable of doing anything similar myself.
I'm not an expert in this, but one of the founders is nephew to Indian billionaire Venugopal Dhoot (chairman of Videocon); according to Wikipedia and news sources he's wanted by the police since April 2018 for irregular loans between his companies accounting for hundreds of millions.
Videocon filed for bankrupcy procedures in June 2018. That connection is very sketchy.
- Disclaimer, I'm a VP E at Engineer.ai
From my understanding, Nivio was merged into one of the investor's companies.
- Disclaimer, I'm a VP E at Engineer.ai
Building modules that can interact with any one of hundreds of other modules usually requires a fair amount of adapter code. This code comes with a performance penalty.
Maybe their market is ok with lesser performance. But I am highly skeptical that apps built this way will ever compete with apps built for a single, specific purpose.
I do hope they can advance the state of the art in some way though, because software development still feels way more tedious to me than it should be.
This just seems like gig-economy + 90s Windows Widget business
I'll believe that when I see it.
- Disclaimer, I'm a VP E at Engineer.ai
- Disclaimer, I am the aforementioned VP Blockchain at Engineer.ai
What exactly is AI about this?
What did the BBC use?
Our platform is actually made up of a collection of tools and microservices including everything from a user story management system (similar to Jira/PivotalTracker), to the assembler itself which stitches components together and creates scaffolding for applications (infrastructure and code). We use AI in a variety of ways throughout this ecosystem (my colleague @sachmans has touched upon a few of those ways above).
The BBC asked us to build their BBC Click Live app. They were launching Click in India for the first time ever, and wanted an application to allow for audience participation. Since their app was relatively simple and was composed of primarily reusable components, we were able to do it a fraction of the price and timeline that it would have taken if it was created entirely by a human team.
- Disclaimer, I'm a VP E at Engineer.ai
"Building blocks" without operational support is useless. How do you provide support for some closed "building block" contributed by someone you will never meet? Open source solves this by making "building blocks" available to everyone freely. Clouds solve this by selling you a service and you don't worry about the code.
https://news.ycombinator.com/item?id=18381723
Formal proof:
https://www.am-nat.org/site/law-of-information-non-growth/
Discussion of proof:
"When a cheap laptop beats the smartest mathematicians at some tasks, but even a supercomputer with 16,000 CPUs can’t beat a child at others, you can tell that humans and computers are not just more or less powerful than each other – they’re categorically different."
- Peter Thiel, "Zero to One", Chapter 12
Further discussion: https://news.ycombinator.com/item?id=18381723
Think about this: we engineers are writers of specs, the same way as product owners are writers of specs, except they do it at a much higher level.
The high level spec (lets say the top 5%) gets passed down and we fill out the ~middle 50%. What's the rest at the bottom? It's the shoulders of giants we stand on.
So the same way as we welcome the increasing abstraction levels, from machine code to C, from C to TypeScript and GraphQL, why don't we welcome this development too?
It's not probable that we will get automated away anytime soon, and if we are, well that means AI has truly advanced, certainly something to celebrate, even if it comes at a financial loss for us.
Perhaps, once we won't get paid anymore to improve ad networks, we will have the time to do something that actually improves the human condition...
Edit: can the downvoter please elaborate?
My guess is they are being built with a cloud acquisition in mind.