[Geminidog]

It’s even boring to technical people. It reduces intelligence to a multidimensional optimization problem. Now intelligence just involves all kinds of mechanical ways to fill out the weights for a neural network. I use to be more interested. Upon learning more about it, I am less motivated.

[cercatrova]

I've found exactly the same experience. Data science is mostly cleaning data in the first place, and the 10% that isn't, it's just fiddling knobs (hyperparameter optimization) to get the model to work.

But man, I can't argue the incredible results it creates. Perhaps that's why people do it, for the ends not the means.

[karmakaze]

That's the difference between research and application. Someone had to first come up with better ways of formulating/training models.

[octodog]

I work in a data science team and I think that motivates a lot of my colleagues. Delivering a product and looking at the massive impact it has on the business is very satisfying.

[karmakaze]

That's one way to look at it.

What's described there is the predicting patterns, which is a part of intelligence but there's much more to discover and invent. Even within the 'optimization' task there's huge differences in the leaps from NNs to DNNs and from DNNs to AlphaGo/Zero. The details are what make it interesting.

If we were to understand exactly how the brain operates and learns, we'd see that it's solved/solving just an optimization problem, but that doesn't make it uninteresting.

[saeranv]

I'm sure this is due to my beginner status in ML/DL, but I'm really disappointed in how much deep learning seems removed from the things that I enjoyed the most in statistical learning.

I enjoy the creative challenge of applying domain knowledge when building (for example) linear or bayesian regressions. In contrast, DL seems like a whole bunch of hyperparameter tuning and curve plotting. Curious to see if this assessment seems correct from those more experienced...

[mmcnl]

Technical is quite a broad term. There are quite some challenges in designing and engineering large ML data pipelines, both from a technical and business perspective. But I agree it's a specific problem that is arguably boring to a lot of people. Some people take more fun in the modelling part, others more in the engineering. Personally, I'm more into the engineering part than creating the actual model.

[gnramires]

Isn't that like saying, "I used to marvel at nature, that it has elements such as fire, water, ice, and amazing living things. Then I discovered it is all made of atoms interacting... I am now less motivated." ?

I mean, the fire, the water, the ice, the amazeness of life and intelligence are still there. You just gained a new foundational view. Now you can understand and manipulate better what you already knew, maybe now you learned about plasma, or even extremely advanced and mysterious phenomena like bose-einstein condensates or superfluidity. The old wonders are still there, you've gained new ones.

I'm not going to claim complete cognitive equivalence (or even preference) between the two states of mind, but it is a bit like childhood: firmly believing in Santa Claus, or Wizards or whatever can be exciting, perhaps more exciting than knowing they are myths; but growing up and understanding they are mythical brings new opportunities, capabilities, and even new mysteries you could not reach before (buying and building whatever you want, vast amounts of knowledge, understanding more about technology and society, etc.). It's the adults that keep us alive and well, that make decisions for us and for society at large. So perhaps (although I'm not entirely convinced by the cumulative argument) truth is a sacrifice, but it is one well worth bearing, at least for me. I am deeply interested in how intelligence works, in how "the sausage is made" (at least for certain highly useful sausages that compose the fundamentals of the world).

Even more, understanding is above all a responsibility, if not for all of us, at least for some of us, or hopefully in one way or another for most of us.

I can't recommend enough Feynman on Beauty: (this argument is largely inspired by that)

https://fs.blog/2011/10/richard-feynman-on-beauty/

In the same vein, intelligence to me used to be a black box where you got input from the world, some kind of wondrous magic happened, and then you got talking kids, scientists, artists, and so on. Now I still view it as wondrous, but now I understand the fundamental is apparently a network-like structure with functional relationships that change, adapt to previously seen information in other to explain it, that there are a number of interesting phenomena and internal structures (going well beyond the simple idea of 'parameter tuning') that can be formalized -- essentially the architecture of the brain (or better, 'a brain').

To give an example, there have been formalizations of Curiosity, i.e. Artificial Curiosity, and I consider it essential for an agent interacting independently in the world or in a learning environment (part of the larger problem of motivation). How amazing is it to formalize and understand something so profound and fundamental to our being as Curiosity? I felt the same way about Information theory years ago. How amazing is it that we've built robots (in virtual environments), and it works -- they're curious and learn the environment without external stimulus?

Above considerations aside, I find that amazing, beautiful, awesome.

[gnramires]

There's another related concept I came up with thinking about this discussion (which I've had with friends as well): 'freedom of utility'.

The basic idea is, forget about what you think is beautiful or motivational. Suppose you could choose to be motivated by something. Would you choose to be motivated by superficial mystery, or by deep knowledge of how things are? Should you choose to find beautiful just the surface of the flower, or also the wonders of how it works, its structure as a system, the connections to evolution and theory of color and so on -- all of which could turn out to be useful one way or another. If you could choose, would you choose to be exclusively motivated by the immediate external appearance or by the depth and myriad of relationships as well?

Unfortunately, (unlike AI systems we could design) I don't think we have complete control of our motivation -- our evolutionary biases are strong. But I'm also fairly certain much of our aesthetic sense can be shaped by culture and rational ideals. If I hadn't heard Feynman, watched so many wonderful documentaries (and e.g. Mythbusters) and many popularizers of science, perhaps I wouldn't see this beauty so much as I do -- and I'm grateful for it, because I want to see this beauty, I want to be motivated to learn about the world, and to improve it in a way.

[jacquesm]

Sagan: "The very act of understanding is a celebration of joining, merging, even if on a very modest scale, with the magnificence of the Cosmos."

[Geminidog]

> Isn't that like saying, "I used to marvel at nature, that it has elements such as fire, water, ice, and amazing living things. Then I discovered it is all made of atoms interacting... I am now less motivated." ?

Yes it is exactly what I'm saying. I'm less interested because of this. I could turn it around and also say that with your extremely positive attitude you can look at a piece of dog shit and make it look "amazing." Think about it. That dog shit is made out of a scaffold of living bacteria like a mini-civilization or ecosystem! Each unit of bacteria in this ecosystem is in itself a complex machine constructed out of molecules! Isn't the universe such an interesting place!!!!!

This history of that piece of shit stretches back though millions of years of evolutionary history. That history is etched into our DNA, your DNA and every living thing on earth!!! All of humanity shares common ancestors with the bacteria in that piece of shit and everything is interconnected through the tree of life!!! We can go deeper because every atom in that DNA molecule in itself has a history where the scale is off the charts. Each atom was once part of a star and was once part of the big bang! We, You and I are made out of Star Material! When I think about all of this I'm just in awe!!!! wowowow. Not.

I'm honestly just not interested in a piece of shit. It's boring and I can't explain why, but hopefully the example above will help you understand where I'm coming from.

[gnramires]

Well... dog shit is kind of amazing. ;)

You see, there are people out there that legitimately, professionally study poop for a living. I read a book (well, part of it) Gorillas in the Mist, by Dian Fossey, and there is an appendix on parasites, mostly using fecal analysis. Literally, a chapter on poop and worms. Reading it without prejudice, I found it extremely interesting.

Should we just say 'ewww', 'dog shit is boring, no one should study it'; or should we give it the benefit of doubt? What makes something interesting? I'm sure you could study poop and parasites for years -- they tell you about the diet of an animal without having to follow it day and night, they reveal parasites that may be of health concern for human poop.

Should we, as a society, forsake all study of poop by deeming it boring? Are those people that study poop, and don't find it boring, wrong? Or maybe they secretly go about their job finding it extremely boring? I doubt it.

> Yes it is exactly what I'm saying. I'm less interested because of this.

I think you're falling victim to reductionism. I meant my example literally: because everything is just atoms, should everything be boring? (if intelligence is just parameter adjustment) I suppose you don't find literally everything boring despite literally everything being just interacting atoms.

You could have this reductionist attitude on anything really:

Once I found out mathematics is just manipulating symbols, I am less motivated/Once I found math is just deriving from axioms, I am less motivated/Once I found life is just a bunch of organisms fighting for survival, I am less motivated

Does it really make sense to be less motivated, is the subject matter really boring, or are you just taking a reductionist argument and replacing the nuance and complexity and beauty of the real thing with a reductionist model (that doesn't really tell us much about how it works)?

Going even further: forget about machine learning. You can formulate physics so that Nature, everything, is locally minimizing (optimizing) a high-dimensional energy function. Literally everything in the Universe is parameter tuning! Oh no, everything is boring! :p

To me, then, there are three pillars of what makes something interesting:

1) It is useful;

2) It has breadth of knowledge (i.e. it's not a trivial matter you can learn in one sitting);

3) It has structure (i.e. it's not just rote memorization)

If I pointed someone to a perfectly uniform white wall and with an extremely positive attitude he declared "Amazing!", and spent hours going "Look how white the white is... what purity, I will stand here all day contemplating different aspects of the whiteness", I'd think he's yes a bit different. But it's not difficult to argue why we think that.

Another point of confusion, is that we're not all in the same situation. Each person has a set of skills, and a background knowledge, such that, for an individual, a subject can seem more or less useful, more or less related to everything he knows (thus much structured, connected, rich), and more or less aligned with his skills. It's perfectly acceptable to declare something as not interesting to him, but not plain boring, universally uninteresting.

I cannot advance much further without talking about the specifics of intelligence: do you know learning theory (PAC learning, etc.), reinforcement learning, all the interesting mathematical structures e.g. in convnets, GANs, Wasserstein-GANs, cognitive psychology, neurobiology, etc.. I think my argument is easy because in this case 'intelligence' is so vastly broad, reaching most areas of math, engineering and science that I doubt with serious effort someone could still blankly classify it as uninteresting (unless you literally do find everything uninteresting... you should be a bit worried about that, I'm serious).

And like in every field in practice one would not sit every day thinking in abstract terms about 'intelligence' -- you would be trying to solve specific problems e.g. what kind of neural architecture could be used to solve a specific problem, what kind of data augmentation can I contribute, or more advanced problems like what is the internal architecture of a robot.

Thank you for the opportunity of laying out those thoughts :)

(Please read my other comment as well, and I have a few things to add w.r.t. hyper-specialization)

[Geminidog]

When I said you're the guy that can see the bright side of dog shit I was startlingly accurate. You're that one guy people call "excessively positive."

Every time your brain sees something related to "science" it automatically dumps a gallon of dopamine into the happy center of your brain giving you euphoria equivalent to a line of heroin.

I wonder what's your positive spin on the holocaust? There's actual science that came out of that event.

[Schiphol]

> It reduces intelligence to a multidimensional optimization problem.

Did you mean to say "... which it is not", or "which it is, thus the boringness"?

[Geminidog]

Let me clarify. I mean “intelligence from the perspective of modern ML” is just an optimization problem.