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Comment by Laurentvw | Hacker News Reader

Sounds interesting! Does anyone have examples of AI startups that solve real world problems? Just trying to get a picture of what companies would fit their fund.

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I think mapping roads is a real world problem. But for a few urban areas, maps are rarely updated. Of course Google has some sort of monopoly here, but there is a LOT of work to be done.

Planet labs now have the ability to map the entire planet every day at a 3m resolution. So object detection applied on these images can be a quite efficient. I still wouldn't call this AI as we are talking mostly about supervised learning but it's a highly practical real world use case. CrowdAI and the like are on this path already.

I'm not sure if this falls (strictly speaking) under AI but lately I have been using Google Maps for Traffic almost daily. It shows the congested roads, estimates the time, suggests paths and show length, etc...

It is battle tested by me and I can say it is surprisingly accurate.

We're "horizontal".

We would not fit his definition of a vertical specific startup. (We have also been around a while though) The bulk of what we do is time series.

Applications we do for real paying customers include:

Detecting theft of power on the raw grid

Online payments fraud

Detecting people stealing from the telco network

Detecting faults in assembly line machines

Detecting computers about to fail

Detecting root cause of dropped calls

Kind of researchy, but we've also done robotics with RL to teach a robot to learn an obstacle course.

Tell me more, who is 'we' ?

Just look at his profile (a click away). He is the founder of Skymind.

Yeah sorry, I just assume people click profiles :).

Aren't you describing a consultancy?

No we're a horizontal AI platform vendor with a strong focus on anomaly detection in time series applications. Our main product is a competitor to AWS sagemaker for on prem and hybrid cloud deployments.

I mean these are great stuff. But do you plan to be a venture-backed company (i.e. looking for hyper-growth and an exit, e.g. acquisition or IPO) or are you planning on being some sort of LLP?

The problem is that though the above may currently be a profitable business, I can't see how you will generate a "moat" and mature into a monopoly or a big market share in a vertical.

I'm a YC founder with 7 mill in funding and 40 employees. We already are :).

Skymind is a weird mix of joint ventures in asia, US and Chinese investment. We're not looking for an exit anytime soon. We are looking to build a big business though.

The "moat" is a land and expand strategy. There is lockin with our tooling. It's a standard on prem play. We're hard to get rid of once you install us. We help in house teams compete with external vendors. Interest actually aligns there. Happy to elaborate a bit otherwise.

My startup, RAMM Science (https://ramm.science) has a Deep Learning Platform, we have customers using Deep Learning for:

Predicting real estate opportunities (which houses are about to sell) predicting energy usage for thousands of sites in real-time, predicting churn, predicting Ad-Tech prices and fraud in real-time, predicting anomalies in seismic radar scans, customer segmentation and recommender engines.

Those are examples of real world paying customers using Deep Learning

Manufacturing is a big one -- right now most factories are still run very manually, but advances in robotics, computer vision, and AI will change the game. In terms of companies here in the bay area working on this, theres Andrew's own Landing.ai as well as Instrumental (https://www.forbes.com/sites/aarontilley/2017/06/22/instrume...).

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