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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

#301

Post by z3phyr »

joshuamorton wrote: post #234
triska wrote: post #146

Personally, I find the lack of logic programming, and logic in general, a rather notable property of the outlined curriculum. In fact, "logic" is nowhere explicitly mentioned in the course titles. Neither are "formal" and "method". For comparison, at the department of AI in Edinburgh, Prolog was very important and even actively developed to such an extent that current Prolog systems are still hugely influenced by "Ed…

>Also, theorem proving is an important area of computer science with many connections to AI. I think this is only true if you use a different definition of AI than the one likely used here. Expert systems aren't considered to be very effective tools for useful "AI" anymore. You can't define a procedure to recognize a happy face in logic programming, at least not with any degree of efficiency.

> You can't define a procedure to recognize a happy face in logic programming, at least not with any degree of efficiency

This cannot be the test to differentiate between AI and "AI"?

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#302

Post by bkanber »

matthewbauer wrote: post #268
asafira wrote: post #241

Earlier quoted context omitted.

Would you consider an undergraduate degree in Physics the same as a graduate degree in physics? No, I would not expect a person with an undergrad degree in physics to have nearly the same capabilities and understanding of a PhD holder in general. Similarly, it would be silly to assume the alums from this program are going to be considered to be of the same caliber. Instead, they will fill roles in which having a rich…

Isn’t most AI work in research though? I think the problem most are having with this is we generally consider AI to be more prestigious than something like data science (which seems like it would be a better name for a degree in its own right).

AI is a broad field. Much of it is applied these days.

Even setting a very high bar for what constitutes "AI", I would concede that Google Assistant, Siri, Alexa, and Cortana are AI systems. How many jobs are there supporting those products today? How many will there be 5 years from now when these kids graduate?

But there are many other AI products out there, and moreso, machine learning is now widespread as a supporting tool in very many places. The data science field of today/tomorrow is ML and AI, and we definitely will need more practitioners.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#303

Post by dgacmu »

learc83 wrote: post #287
dgacmu wrote: post #281

Earlier quoted context omitted.

We actually have a set of criteria for what makes a qualifying systems elective. As with many things at CMU, we don't generally care what details you learn. We care greatly what higher-level concepts you get exposed to, and the systems courses are the place we try to focus on the development of abstractions; modularity; isolation; reasoning about failures and complexity; integrating security concerns. They're also th…

>It's much like programming languages. We don't care much if you graduate knowing a particular language -- any CMU CS graduate should be able to pick up a new language in short order. We care greatly that you've been exposed to a mix of programming styles and thinking -- imperative, functional, and logical or declarative, and can successfully use those tools to reason about code, program structure, algorithms, and da…

We encourage it back towards systemsy-ness. ;). (in other words - nothing's perfect, and we accept some occasional compromises in service of providing a diverse menu. Compilers has other value. If it got too PL-centric, we would just move it to the PL cluster, but it's generally stayed systems for the last decade.)

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#304

Post by hyperpallium »

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…

Computer Science courses omit essential electrical engineering and transistor physics.

The issue is whether a field can be understood at a higher level, atop blackboxes. All abstractions leak, but some are good enough.

DL NNs are no where near being a science yet - it's empirical let's try this architecture. But... you could have a trade-school technician degree in present techniques that can be applied. Like an electrician.

You could also have a degree aimed at preparing you for graduate AI - which would include a lot of mathematics.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#305

Post by bkanber »

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…

There's a big difference between being able to calculate the gradient of an activation function you just invented and apply it to a backpropagation algorithm or analyze it for convergence, and simply understanding what a gradient is and how it is used when training the model.

I find that the understanding and ability to visualize the mathematical concepts is the important part, for everyday practitioners. It is not necessary to be able to derive a gradient in order to understand the differences between sigmoid and hyperbolic tangent. Being able to do the calculation on paper is not a prerequisite for understanding the process.

The rigorous mathematics come into play if you wish to advance the field as a whole, but is not necessary to successfully design and train efficient models.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#306

Post by 131012 »

GeorgeTirebiter wrote: post #288
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 completely agree. CS started often from the Math department, sometimes from the Engineering department. Further specialization is to be not only expected, but welcome, as complexity increases. Is there a better way?

I totally agree. I really think it is heading toward a med school styled specialization. And with that will come the added prestige. CS is so remote from pure/natural sciences, it screams for standalone schools, like law and medicine. And with it, prestige and power. Why are people against that?

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#307

Post by doppp »

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…

CMU's CS program is very rigorous and tough. A lot of CMU's undergraduate courses are actually graduate courses in other universities' CS program e.g. CMU's 15-213 course (sophomore level) is a graduate requirement in Stanford's MSCS course as well as CMU's MSCS curriculum. Looking at CMU's curriculum for this degree, it seems that they did a good job at not "skipping to the interesting bits."

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#308

Post by scott_russell »

SamReidHughes wrote: post #224
asdsa5325 wrote: post #208

Earlier quoted context omitted.

They taught gradient descent in my lower division math courses in college.

Multivariable calculus is a lower-division math class.

yep, softmore level math.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#309

Post by stuxnet79 »

willhslade wrote: post #242
naeemtee wrote: post #147

Earlier quoted context omitted.

Ah, EngSci - the most freakishly difficult undergraduate curriculum on the planet.

Care to elaborate?

The University of Toronto Engineering Science program has a reputation of being very rigorous, difficult.

Re: Carnegie Mellon Launches Undergraduate Degree in Artificial Intelligence

#310

Post by anitil »

esahione wrote: post #239
drngdds wrote: post #195

Earlier quoted context omitted.

Serious question, from someone who hasn't had to do it: how is it possible to do productively study for 16 hours a day? Controlled substances? I don't last that long even on occasion, much less regularly.

Everyone takes Adderall. Not just that, but a lot of the time is spent explaining things to your classmates, getting answers to match our expectations, etc. So it's not like 16 hours of reading and trying to understand the material, more like 16 hours of school work.

What's it like with Adderall? Does it impact your sleep cycle, or just allow you to concentrate?
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