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rohan404 | 6 years ago
AI is certainly not magic, and as an industry we're super far away from what would be considered real AI in the technical sense. That being said, AI has become a catch all term for everything as simple as linear regressions, all the way through to neural networks.
We don't claim to be able to write apps using AI, we're a platform that is trying to use AI and general automation in order to optimize the traditional SDLC. Actual code generation/synthesis is years away in my opinion and there is far more impact that can be had by going after other manual aspects of software development.
ammar2|6 years ago
I don't think you can get away with corp-speak/buzzwords here this easily. Could you elaborate on how exactly you're using AI to "optimize" software development?
DIVx0|6 years ago
If I were take a guess of the flow: As a customer creates a "new app" they go through some wizard type of process that will start to narrow down which templates are needed and what information to prompt the customer to fill in.
Once they have all of that they take that bundle of templates and "content" and hand it off to some developer to glue it all together and then perhaps add some other automation to handle small changes by the customer later automatically.
Could be a clever way to speed up app development if you can narrow the scope down but "AI" it is not.
Just some speculation, arm-chair-quarter backing
rohan404|6 years ago
Happy to elaborate - in a nutshell what we're trying to do is automate as many parts of the traditional software development lifecycle as we can, and for whatever cannot be automated, put in place the right tooling to allow for repeatable results.
Our thesis is that most applications today have a huge amount of duplication at a code level, and process level. We're trying to use reusable building blocks (well structured libraries, templated user stories, wireframes, common errors, etc.), in order to immediately solve that duplication. That being said, we're not talking about automatic code generation, it's more about being able to assemble these reusable building blocks together at the beginning of a project so you have a better starting point. There will always be customization required for any project however, and that is a human led process.
Apart from actual development, we're also trying to automate processes around project management, infrastructure management, and QA. For example, what we've already been able to do is automatically price and create timeline estimates for a project without any human involvement, determine which creators on our network are best suited for a given project, evaluate and onboard developers on to the network, setup developer environments, and a lot more!
YeGoblynQueenne|6 years ago
https://people.csail.mit.edu/rishabh/papers/cacm12.pdf
Which btw is absolutely an artificial intelligence application albeit one that has nothing to do with neural nets and deep learning.
Perhaps, if your company has trouble with acquiring data and training large deep neural nets, you could benefit from looking at other techniques that do not have such stringent requirements and that are much better suited to smaller companies (i.e. anyone but Google, Facebook, Amazon, Netflix et al).
gnulinux|6 years ago
rohan404|6 years ago
It's not just one problem we're tackling, it's actually more like 40 small issues that we're working on. You actually named a few right there - static code analysis, automatic UI generation from YAML. I also want to be clear that not all of it is AI or ML. For example how we price and spec out ideas (https://builder.engineer.ai/) is fully automated and leverages NLP and NNs, and how we handle developer verification uses facial recognition. However many of the problems we are going after don't require AI; heuristics based approaches and statistical models can actually have better results in many cases.
TrackerFF|6 years ago
And that's a problem. The problem is that this trend builds unrealistic expectations for pretty much anyone that doesn't know how the tech works.
Business people imagine some magic box that will just churn out stuff with (close to) zero workers involved.
Customers imagine the same magic box churning out tailored products built with AI fairy magic.
Then reality sets in, and people (investors included) start losing faith, and we're onto the next AI winter.
hitekker|6 years ago
rohan404|6 years ago
We've been very transparent with our investors on where we are in the process of creating this platform both pre-investment and post. They actually responded to the WSJ article:
A spokeswoman for Deepcore said it has complete confidence in Mr. Duggal’s vision and team.
A spokesman for Jungle Ventures said it is a proud investor in Engineer.ai and its technology, adding that “the AI landscape is a varied spectrum.”
A Lakestar spokeswoman said it also has confidence in Engineer.ai and its team, adding that “growth in the AI space does not happen overnight.” It said Engineer.ai had been very careful in presenting its technology to Lakestar and other investors
vanadium|6 years ago
rohan404|6 years ago
Apologies for that experience! We're currently working on a new iteration of that site and will be launching it very shortly. Come back soon and let us know what you think.