Andreessen-Horowitz craps on “AI” startups from a great height

Is the misspelling of "Andreessen-Horowitz" and use of "A19H" instead of "a16z" intentional?

You mean the fact that they left out an "s" in Andreessen?

The number of places where machine learning can be used effectively from both a cost perspective and a return perspective are small. They are usually tremendously large datasets at gigantic companies, and they probably have to build in house expertise because it's hard to package this up into a product and resell it for various industries, datasets, etc.

Certainly something like autonomous driving needs machine learning to function, but again, these are going to be owned by large corporations, and even when a startup is successful, it's really about the layered technology on-top of machine learning that makes it interesting.

It's kind of like what Kelsey Hightower said about Kubernetes. It's interesting and great, but what will really matter is what service you put on top of it, so much so that whether you use Kubernetes becomes irrelevant.

So I think companies that are focusing on a specific problem, providing that value added service, building it through machine learning, can be successful. While just broadly deploying machine learning as a platform in and of itself can be very challenging.

And I think the autonomous driving space is a great example of that. They are building a value added service in a particular vertical, with tremendous investment, progress, and potentially life changing tech down the road. But as a consumer it's really the autonomous driving that is interesting, not whether they are using AI/machine learning to get there.

"Huge compute bills" usually come from training, or to be more precise, hyperparameter search that's required before you find a model that works well. You could also fail to find such a model, but that's another discussion.

So yeah, you could spend one or two FTE salaries' (or one deep learning PhD's) worth of cash on finding such models for your startup if you insist on helping Jeff Bezos to wipe his tears with crisp hundred dollar bills. That's if you know what you're doing of course. Literally unlimited amounts could be spent if you don't. Or you could do the same for a fraction of the cost by stuffing a rack in your office with consumer grade 2080ti's. Just don't call it a "datacenter" or NVIDIA will have a stroke. Is that too much money? Not in most typical cases, I'd think. If the competitive advantage of what you're doing with DL does not offset the cost of 2 meatspace FTEs, you're doing it wrong.

That, once again, assumes that you know what you're doing, and aren't doing deep learning for the sake of deep learning.

Also, if your startup is venture funded, AWS will give you $100K in credit, hoping that you waste it by misconfiguring your instances and not paying attention to their extremely opaque billing (which is what most of their startup customers proceed to doing pretty much straight away). If you do not make these mistakes, that $100K will last for some time, after which you could build out the aforementioned rack full of 2080ti's on prem.

On the other hand some of the startup is doing absolutely fraud on the name of AI.I went to a self checkout store (AIFI.io). I did not touch anything but they charge me $35.10. According to the receipt I took 17 packs of snacks :) These guys are doing fraud on the name of AI. They have no technology no software just put up some camera and open a store so that they can defraud the investor. Anyone can try if intersted https://www.aifi.io/loop-case-study