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Comment by yters | Hacker News Reader

What is the big job market for AI/ML? I see some Kaggle competitions, and a few high wage jobs working for the big tech companies, but it still seems pretty niche.

Makes sense from a theoretical viewpoint, b/c all AI/ML models are not Turing complete in order to be optimizable, whereas your average programmer easily churns out "models" in a Turing complete language. So, joe blow programmer is universally more powerful than any AI/ML algorithm. He can program an AI in his TC language, but AI cannot replicate his work in a non TC language.

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The bank where I work needs so many data scientists and AI/ML/DL engineers and they can't find enough of them to the point they're paying master degrees and MOOCs to all employees that want to study it, as long as they already have some experience with Python/R or a background in math/stats/engineering.

Cough. What company is this? I was looking into getting my Masters but would be much nicer if somebody was paying for it.

One of the top 20 investment banks.

I know you probably mean well and maybe want to stay anonymous, but it seems pretty clear to me that commenter was looking for a specific firm in response to their question. Is it the case that all of the top 20 IBs are offering tuition reimbursement for data science?

I understand the commenter wanted a clear answer but I don't know if I should be specific since I can't find a public source to go along. Maybe this is internal and I fd up?

I understood your answer and thought it was fine.

Just so you know its very easy to find out where you work. I can get your name from your keybase links, easily find your linkedin page, and verify your location to be sure from other links on keybase.

PhD in Computer Engineering with MSc in AI/ML here. Happy to do remote work for your bank :)

A very recent M.S. from a top 10 school in ML/DL here. Can chime in remotely as well. Need a new Lamborghini; Murcielago is getting old you know ;-)

Working remote is not allowed due to certain regulations. That's why it's so hard to hire good data scientists!

And you're in top-20 I-banking? So most likely in a huge city, with a huge swath of data science talent. The issue isn't folks not being able to work remotely.

The thing is that data scientists are wanted by so many companies that besides salary you have to compete with perks and other things. IBs can't provide some of the perks, like remote work and makes it less attractive to potential candidates. This is my opinion, not my employer.

Once an AI gets that good, good enough to reproduce even a junior developer, nobody can ever get paid to work again. Before that point, it’s still useful to know the basics of AI in the same way knowing about arrays or higher order functions is useful.

Do you know of a Turing complete AI/ML model?

- Neural turing machines: https://arxiv.org/abs/1410.5401

- Universal transformers: https://arxiv.org/abs/1807.03819

These are just 2 of most well known.

Definitely interesting stuff. Do you know of real world tasks where these sorts of models have proven more useful than non TC models?

I am not aware of any real world usage of these models. They are hard to train, and most of the papers consider toy examples.

many of them are Turing-complete almost by accident, if you are willing to add enough parameters. E.g. a shallow neural network with one layer is Turing-complete.

It's actually Turing-complete for rational-valued weights (countable). If you are willing to grant real valued weights (uncountable) then it is actually more powerful than a Turing machine, able to compute things in P/poly, a very weird complexity class that includes some encodings of the halting problem. But this is just because you're "cheating" by allowing infinite precision which is not possible in the real world.

That doesn't sound like TC for real world usage...unlike a regular programmer.

One layer is a surprise to me, I thought xor needed two?

One hidden layer. Commonly known as the "Universal approximation theorem"

Ah, I misunderstood GP saying one layer.

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