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It's pretty lonely to be a bull on machine learning right now. It's weird because the successes in ML just keep on rolling in.


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At least someone doing something useful with ML

Yeah, exactly. I am actually solving problems with ML these days.

With all the advancements in ML, there's a new set of lowest hanging fruit, and it's incredibly exciting.

The pace that ML seems to be advancing right now is amazing. I don’t believe in the singularity but it’s changing software and then society in ways no one can predict.

Looks like ML is getting better every day at solving the generalized inverse problem.

Doing ML in ML seems like an under-explored area.

Anyone else stressed out how good ML approach is advancing in AI? I feel left behind...

I think it's interesting that there's a few things you could start thinking about when you see the title.

I might be alone but it's feeling a little bubbly to me in a few different areas. ML is certainly one of them.


Machine learning was up and coming in 2012 when I graduated college. Not to say it is a bad career choice, just that it's safe to say that ML's time has already come.

The results are living up. ML is integrated into the core of so many companies at this point it’s not like it was 10 years ago. ML is here to stay and it will be almost the entire economy in the not to distant future

ML is slowly approaching the blockchain bubble I think. You have ALOT of people just chucking random bs data into insert popular model and hoping for the best.

I think the ML hype is actually slowing down. I've been interviewing for ML positions as a new grad and a number of companies have told me they have an excess of data scientists who can train the models, but a dearth of engineers who can actually scale the models up to production. Friends at FAANGs have similar stories.

I agree completely. Doing novel things with ML is very, very, very hard, and (afaict) hasn’t been particularly successful at the startup level. But operatonalizing existing techniques is _very_ promising, and where I think a lot of the wins will come from.

Nice to see a roundup of ML that doesn't just go straight to Deep Learning for a change :-)

Seems like people are slowly running out of ideas what to do with ML.

What progress? We’re bruteforcing solutions without any way to learn from then. ML eliminates serendipity. I’m not strictly anti-ML. Horses for courses and all that, but I’ve got to admit I get weird, “The humans stopped learned and the computers started,” sci-fi vibes sometimes.

ML is going mainstream. Most programmers don't know algorithms and data structures, I bet, if you consider all programmers around the world.

It's pattern recognition. Machines replace human labor, people get sacred, the world doesn't end, we move on. ML is no different.

Isn't ML the only kind of successful AI?
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