I can't create a new programming language that compiles to machine code. Maybe I shouldn't be programming?

I don't see why you need to be a domain expert of the low level details to make a career out of something so useful.

I don't see why you would need a graduate degree to create a new PL that compiles to machine code. In fact, many successful PL designers lack PhDs.

Most work in CS feeds more on experience than education. A PhD is simply a way of getting deep experience (and advice) in areas that a job probably wouldn't allow for. Since ML is hot, you can get hands on experience with it these days, its not like 10 years ago when the only people looking at deep learning were pretty much researchers, PhDs, and PhD students.

That is also taught to a useful level in undergraduate coursework. You can do useful ML using only first year undergraduate statistics, linear algebra, and multivariate calculus.

I don’t think it is actually gatekeeping because no one is saying that you CAN’T do AI/ML with this degree just that there is going to be a tradeoff in any curriculum focusing on a subset of CS.

A consequence of this degree is that it makes CS degrees worth less. Because AI/ML is by definition a subset of CS, this degree implies that you have CS + more. It doesn’t fairly show that there is a tradeoff in a specialized curriculum (less exposure to other areas of CS).

I would say that if you are at CMU or another school offering this degree, you would be a fool not to do it. Even if you are not interested in AI/ML, it will be more hirable than CS because the name implies it is “better” than a CS degree. It’s a similar situation with the new “cybersecurity” degrees being offered. Ideally the accreditation group would bring some sense into this but so far they have greenlit both degrees.

That's exactly the opposite of what happens to most graduates with specialized degrees.

They end up having to explain their degrees, which is generally not a good thing. It happens all the time with engineering. In the job market a degree in mechanical engineering is in general worth more than one in robotics.

You also run the risk of graduating into another AI winter, or just deciding you hate AI, and then you really have to try hard to explain that your degree is really just a CS degree.

Imagine graduating now with an undergrad in big data--that sounded like a good idea 5 years ago.

> Imagine graduating now with an undergrad in big data--that sounded like a good idea 5 years ago.

Is that a good analogy? Big data started out as a marketing buzzword, whereas AI always was an academic field of research.

AI is a very overloaded term. What we currently call "AI" is likely suffering from the same hype bubble that big data did.

And yet, most of today's commercial AI requires "big data".

Yeah big data can be very useful. The reality just doesn't match the hype.

I think you are confusing between specialization, and a degree in sub-branch. A degree in CS is always valued more than a degree in say IT.

On the other hand, a degree in CS with specialization in Networking, would be more valued than a plain degree in CS.

I'd say if you want to specialize, do a master's. A degree such as above would put the holder in really bad position if that field goes into ice age. In case that happens to master's degree, you always have your bachelor's degree to fall back to.

I took an open CMU grad course on the basics of AI from a year ago and generally I can understand papers in journals at an intuitive level and hack around with some existing libraries no problem. I won't be solving research problems or hired by Tesla or anything but writing amateur trade bots, and feeding predictive bids inside an app I wrote is possible with just an AI crash course. Rest of CMUs standard undergrad is pretty solid I imagine these will be good advanced undergrad courses.