3 ms·

A small team in a company I worked for got into machine learning a few years back. They had some success with some toy examples and were now looking for applica

by linza 6y ago

A small team in a company I worked for got into machine learning a few years back. They had some success with some toy examples and were now looking for applications. They tried to use it for optimizing some specific engineering procesess. Two people (one was me) were warning them that this is a waste of time and will cost the company a fortune and then no one will want it because the quality will be so much poorer. And the whole thing looked like an instance of hammer-looking-for-a-nail. Fast forward a few years, the team tripled in size, built a multi-million-euro product, and some very large customers now trust their operations research to that new thing.

deleted 6y ago
[deleted]
denispal 6y ago
So are you saying that the article is just written by "non-visonaries" who dont know what they are talking about? The old "If I had asked my customers for what they want, they would have said a faster horse"
the-dude 6y ago
So, an amazing succes story.
roryokane 6y ago
It's hard to take a lesson from this without hearing why you think that happened. Do you think the product got so big because the team applied AI usefully and your initial evaluation was wrong? Or do you think they gained customers because there is not much competition in that niche and customers were drawn to the sales team's claims of AI despite the AI not being very good?
- draw_down 6y ago
  The lesson is just because we think, with our big wonderful brains, that something isn’t going to work in the market, doesn’t mean we’re right. Or to say it another way, the lesson is that business people have jobs for a reason too. Or: if your job is computers, focus on the computers. For me, I don’t go around my company telling everyone whether their projects are going to take off or not. I assume the research a team did prior to starting gives them a familiarity with the problem space that I lack. Crazy thought, I know. The amount of “told ya so” in this thread is really something, so I appreciate GP’s post. Humility is good.
- linza 6y ago
  My personal takeaway was that I don't know as much as I think. I didn't produce any data at the time to prove my point (not that I would have known how to), and because of that it's hard for me to analyse the situation more meaningfully as to why I was wrong. Why they were successful in the end: the team struggled for some time before they got momentum with a single really large customer that put in resources, and made other customers follow. It's not that the tech got better that much, customers were just more willing after they saw one of the leaders in that space invest in that approach, and they were afraid of falling behind. It was not because of machine learning, but despite of it.

by linza 6y ago

deleted 6y ago

[deleted]

denispal 6y ago

So are you saying that the article is just written by "non-visonaries" who dont know what they are talking about? The old "If I had asked my customers for what they want, they would have said a faster horse"

the-dude 6y ago

So, an amazing succes story.

roryokane 6y ago

It's hard to take a lesson from this without hearing why you think that happened. Do you think the product got so big because the team applied AI usefully and your initial evaluation was wrong? Or do you think they gained customers because there is not much competition in that niche and customers were drawn to the sales team's claims of AI despite the AI not being very good?

draw_down 6y ago
The lesson is just because we think, with our big wonderful brains, that something isn’t going to work in the market, doesn’t mean we’re right. Or to say it another way, the lesson is that business people have jobs for a reason too. Or: if your job is computers, focus on the computers. For me, I don’t go around my company telling everyone whether their projects are going to take off or not. I assume the research a team did prior to starting gives them a familiarity with the problem space that I lack. Crazy thought, I know. The amount of “told ya so” in this thread is really something, so I appreciate GP’s post. Humility is good.
linza 6y ago
My personal takeaway was that I don't know as much as I think. I didn't produce any data at the time to prove my point (not that I would have known how to), and because of that it's hard for me to analyse the situation more meaningfully as to why I was wrong. Why they were successful in the end: the team struggled for some time before they got momentum with a single really large customer that put in resources, and made other customers follow. It's not that the tech got better that much, customers were just more willing after they saw one of the leaders in that space invest in that approach, and they were afraid of falling behind. It was not because of machine learning, but despite of it.