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Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

cs.cmu.edu

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Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#311

Post by genericpseudo »

tim333 wrote: post #284
jknoepfler wrote: post #164

I really do not like this move. AI and Machine Learning require graduate-level mathematical and computational skills. I don't think it's productive to pretend that we can train someone to be even remotely useful in these fields in four years of an undergraduate education. It sounds like an attempt to get around the fundamentals of csci to "skip to the interesting bits," which will produce graduates with a cursory kno…

>even remotely useful in these fields in four years ...Condensed Matter I just looked up the Cambridge physics tripos and you do condensed matter in years 3 and 4. You can learn a lot in 4 years. Admittedly it's a specialisation in a general science degree.

Density functional theory, for example, is taught at undergraduate level as part of both chemistry and physics triposes. Probably materials science too, and it certainly used to be an option within earth sciences (as part of the mineral physics path).

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#312

Post by xxpor »

anonu wrote: post #285

So much negativity on this discussion. I'm very surprised to see this from the HN crowd. Guess what? Computer Science, Engineering, etc... is getting more complicated and complex. So seeing a discipline (assuming this is CS) get broken down into more distinct groupings is actually a good phenomenon. Of course there's always foundational knowledge that is important to learn - but with time I feel like that information…

I just hope that they still include software engineering etc. I've interviewed many "AI specialists" who probably know AI pretty well (I'm not qualified to make that judgement) but they can't code their way out of a paper bag. Basic data structure errors, terrible organization, etc.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#313

Post by nicoburns »

swiley wrote: post #276
MR4D wrote: post #237

Earlier quoted context omitted.

To me, your statement is like saying an airline mechanic needs to have a pilot's license because he needs to know how the rudder affects the flight. There are three different roles that I think you are conflating: Designing, Building (and maintaining), and using. Each has a different skillset. But to think that you need to determine the convergence of models makes no sense to me. Why can't an undergrad build a simple…

I don’t see how building a web page is any different now than it was in 1998, if anything it seems like everyone has made it harder to build correct pages.

If you stick to the basics of static html content + styling it's actually a lot easier because there are far fewer browser 'quirks' to work around nowadays (you rarely need browser specific code), and things like flexbox are a lot more intuitive than hacking around with floats.

I'm a front-end dev (amonst other things), so I'm pretty comfortable with React, Angular, etc. And therr are definitely cases where they make sense. But simple static or server side rendered sites are much simpler now.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#314

Post by mturmon »

zukzuk wrote: post #160
gandreani wrote: post #153

Earlier quoted context omitted.

What were they disappointed in? Also, what do you mean by "see the current ML hype as a glass half empty"? I take it that you are also disappointed with the recent research I'm just getting into the field, but it seems to me at least in computer vision, voice recognition, and text to speech there have been great strides in the recent years

Have a look at https://en.wikipedia.org/wiki/AI_winter I personally wasn't disappointed — I'm really glad I did this as my undergrad. AI research however tends to go through periods of hype followed by disillusionment. There's a history of promising developments that hit a wall or fizzle out in the long run. That's not to say there hasn't been progress (there's been tons!), but based on track record alone, it's prude…

You’re over emphasizing a particular historical fable. Yes, some AI hype has happened. We’ve all read the “summer project” of McCarthy, Shannon, et al.

But all these recent advances are not just hype. It’s real. Anyone who has been following this area for a long time knows that some big problems (like large-scale image classification) have been solved, and in an orderly way that builds on prior work going back to the 1990s and before. (My ML PhD was in 1995.)

Nobody here is referring to the “singularity” - that is obviously speculation that has nothing to do with the CMU program.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#315

Post by randcraw »

srinivasan wrote: post #173
aje403 wrote: post #161

Earlier quoted context omitted.

Are you trolling?

I did my undergrad in CS at CMU, and have first-hand experience of what’s covered in the core courses, which are also requirements for this new program. Perhaps you should take a look at the curriculum again like I told you, instead of spewing out falsehoods like “churning out candidates who don’t know what tcp is”. You’re not entitled to your own facts.

At CMU you took no courses in operating systems? Algorithms? Computer hardware or logic? Compilers? Graphics? Databases? Web programming? Distributed systems? Networks? Parallel/HPC? Language theory? Security/crypto?

Because these students will take none of these courses, they will differ significantly from those with a BS in CS. But their AI skills still won't run deep enough to make them expert there either. At best, they'll be conversant with a couple of foci in AI, but not in many other AI areas.

In fact, this program seems custom made to prep for work most typical at Google, Facebook, Microsoft, and not that many others -- doing pattrec forms of ML on large data. Yet they'll lack the skills typical of today's data engineers (basic ML plus HPC/distributed/throughput, networking, and DB /sys admin) or typical of data scientists (nasic ML with a BA in statistics, plus facility with RDBMSes).

Will the absence of these CS skills hamper their competitiveness one day in most mainstream general computing software jobs? I think it probably will.

Therefore, if those with this degree don't spend their entire careers working only in big data areas of AI, they will likely will be at a competitive disadvantage to those with broader skills in CS.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#316

Post by RandomCSGeek »

matthewbauer wrote: post #260
habosa wrote: post #216

Earlier quoted context omitted.

This is a lie that I hear a lot from AI/ML experts. To me it reeks of gatekeeping. Yes the foundations of the field and many of the breakthroughs require this knowledge, but one can be a very effective practicioner of AI/ML techniques with a few years of undergraduate level instruction. And given how many industries are kicking the tires of AI/ML, we're going to need hordes of practicioners.

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…

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.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#317

Post by MikkoFinell »

learc83 wrote: post #270
matthewbauer wrote: post #260

Earlier quoted context omitted.

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…

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 reall…

> 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.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#318

Post by [deleted] »

jknoepfler wrote: post #164

I really do not like this move. AI and Machine Learning require graduate-level mathematical and computational skills. I don't think it's productive to pretend that we can train someone to be even remotely useful in these fields in four years of an undergraduate education. It sounds like an attempt to get around the fundamentals of csci to "skip to the interesting bits," which will produce graduates with a cursory kno…

[deleted]

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#319

Post by hackermailman »

habosa wrote: post #216
jknoepfler wrote: post #164

I really do not like this move. AI and Machine Learning require graduate-level mathematical and computational skills. I don't think it's productive to pretend that we can train someone to be even remotely useful in these fields in four years of an undergraduate education. It sounds like an attempt to get around the fundamentals of csci to "skip to the interesting bits," which will produce graduates with a cursory kno…

This is a lie that I hear a lot from AI/ML experts. To me it reeks of gatekeeping. Yes the foundations of the field and many of the breakthroughs require this knowledge, but one can be a very effective practicioner of AI/ML techniques with a few years of undergraduate level instruction. And given how many industries are kicking the tires of AI/ML, we're going to need hordes of practicioners.

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.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#320

Post by moultano »

PascLeRasc wrote: post #294
freyir wrote: post #251

Earlier quoted context omitted.

> AI and Machine Learning require graduate-level mathematical and computational skills Yeah, not really. A lot of day-to-day work in ML requires rudimentary math, at most. I know PhDs who quickly get discouraged with ML because they're suddenly spending 95% of their time doing the grunt work. It would be a boon if we could hire non-PhDs who are competent in the fundamentals of signals, algorithms, statistics, and exp…

So essentially what we need is an "academic CSEE" degree, where you replace courses on industrial topics like application design and databases / circuits and electromagnetics with these theory-based classes from both departments. I'd also suggest adding some systems neuroscience courses in there too.

I think you could get away with swapping out upper level algorithms and systems courses and swapping in statistics and ML. I've used my OS class 0 times in my career. The class I've used the most was the second level statistics class I took for my econ minor.
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