Is it the new gold rush though. I work in a large organisation that has a lot of data and inefficient processes, and we haven’t bought anything.

It hasn’t been for a lack of trying. We’ve had everyone from IBM and Microsoft to small local AI startup try to sell us their magic, but no one has come up with anything meaningful to do with our data that our analysis department isn’t already doing without ML/AI. I guess we could replace some of our analysis department with ML/AI, but working with data is only part of what they do, explaining the data and helping our leadership make sound decisions is their primary function, and it’s kind of hard for ML/AI to do that (trust me).

What we have learned though, is that even though we have a truck load of data, we can’t actually use it unless we have someone on deck who actually understands it. IBM had a run at it, and they couldn’t get their algorithms to understand anything, not even when we tried to help them. I mean, they did come up with some basic models that their machine spotted/learned by itself by trawling through our data, but nothing we didn’t already have. Because even though we have a lot of data, the quality of it is absolute shite. Which is anecdotal, but it’s terrible because it was generated by thousand of human employees over 40 years, and even though I’m guessing, I doubt we’re unique in that aspect.

We’ll continue to do various proof of concepts and listen to what suppliers have to say, but I fully expect most of it to go the way Blockchain did which is where we never actually find a use for it.

With a gold rush, you kind of need the nuggets of gold to sell, and I’m just not seeing that with ML/AI. At least no yet.

AI != gold. The market for selling tools to people who are essentially chasing buzz words is much smaller than that of selling tools to people extracting scarce metals from the ground.

Ultimately the value of selling tools is dependent on the riches being mined actually existing. The value of AI/big data to the average business has yet to be determined

>"Most people in AI forget that the hardest part of building a new AI solution or product is not the AI or algorithms — it’s the data collection and labeling."

A lot of those companies are styled as "AI" companies themselves, aiming to automate the process of labeling.

The main winner here really is Amazon. They get a chunk by serving up infrastructure and in labeling through mechanical turk.