jmmcd

28 ms·

301.
by jmmcd 9y ago
> Genetic Algorithms do exactly the same thing that Deep Learning methods do: optimize a function for a particular criterion. The difference is that for a GA, that can be any function, whereas for NNs it must be decomposable into a sum o
302.
by jmmcd 9y ago
> make a return about a decade later. Maybe that is how it looked from the outside. But the field continued as normal with no major problems, solving lots of industry problems with little hype.
303.
by jmmcd 9y ago
I think you've confused genetic algorithms with genetic programming. They're not the same thing. > I don't know how Genetic Algorithms/programming could be made 'explainable' as to why they achieved an optim
304.
by jmmcd 9y ago
> The only thing EAs have going for them ... is the ability to optimise a black-box objective.
305.
by jmmcd 9y ago
Look up the author's name and then see if you can stand behind your comment.
306.
by jmmcd 9y ago
People don't care about the headphone jack enough to demand it. There may be a few people like the author here, but saying this -- > Tell them you see what they’re up to, and you don’t like it. You can say this part slightly deeper,
307.
by jmmcd 9y ago
> I especially like the early slides that help frame AI vs ML vs DL so that people can have a realistic understanding of what these technologies are for. But they're wrong! I read "Deep learning drives machine learning which dr
308.
by jmmcd 9y ago
"Decision theory is 1-player game theory" -- I think I saw this on LessWrong, once, but I can't find it now.
309.
by jmmcd 9y ago
> Daddy pig is portrayed as an idiot. I strongly disagree! It looks that way superficially, but he is highly resourceful and skilled. He's an engineer, a champion diver, and superb musician. In contrast, Mummy Pig is mostly a non-en
310.
by jmmcd 9y ago
I liked the world when people knew a joke when they read it.
311.
by jmmcd 9y ago
> And does having intent even mean anything when the goal is to win? I think "intent" implies consciousness (and so, when we say that a spider intends something, we are using the term metaphorically), but probably this is one o
312.
by jmmcd 9y ago
> When reviewing the games it is hard for Go players not to talk about 'intent' and 'planning'. An interesting point. Of course the AI is not planning with intent, but the language is useful. But it IS seeing that if
313.
by jmmcd 9y ago
> Go back to an empty slate, with the same exactly "untrained" AG0, and now teach it Go, to the same result. No fine-tuning for the domain of the game you are training -- it is general(ized). Not quite -- different input featur
314.
by jmmcd 9y ago
Well, it's not doing anything like that for now. Even though the algorithm, in an abstract sense, is the same for all three games, in fact it's a new network for each of the three games, with architecture and input features adapte
315.
by jmmcd 9y ago
> The sample size = 1 may not be enough to perceive any meaningful difference Yes, and I assumed this was obvious. I did say "expect", after all. But a large-N experiment where each child is in the "isolated" conditio
316.
by jmmcd 9y ago
The fact you chose 1M is telling. If you move 1 Mexican child, at birth, to Tokyo, and that Mexican is brought up by Japanese parents etc, I think you will expect fairly strong conformance to Japanese culture. This is sufficient to disprove
317.
by jmmcd 9y ago
Yes, every "run" of the network is generating pixels in those areas, but they're not being compared against the white (deleted) pixels. On the final run of the network, they're still not being compared against anything,
318.
by jmmcd 9y ago
> PS. This makes me wonder whether and to what degree the structure of the brain's connectome is a necessary prior for AGI. Well, I wouldn't mix up AGI and AGI by deep learning, and more important I would emphasise that this is
319.
by jmmcd 9y ago
Yes, for the inpainting, the parts to be painted (big white deleted areas) are supplied as masks, so it doesn't try to match them.
320.
by jmmcd 9y ago
No, the graphics are only being used as part of the explanation. The algorithm is not working with them.
321.
by jmmcd 9y ago
The question asks us to ignore time and cost!
322.
by jmmcd 9y ago
Everything to do with rubbish: putting it out, collecting it, processing/separating it, dumping it.
323.
by jmmcd 9y ago
I considered that interpretation before writing and I found it impossible to read that way. For a start, "imitations" is plural, so no, it doesn't just refer to Jupyter. And "started" certainly implies that other im
324.
by jmmcd 9y ago
Wolfram really is a terrible liar (also very, very smart). He knows damn well that Maple had notebooks in the mid-1990s, because it was one of Mathematica's main commercial rivals, so "started appearing 25+ years later" is no
325.
by jmmcd 9y ago
But when you buy a bitcoin, you don't own any of that.
326.
by jmmcd 9y ago
I wonder if those experimentName parameters are to do with serving different example images to different readers. Below, u/Anhkmorporkian mentions an image of sneakers, but I saw images of a woman and of the Golden Gate bridge. Did oth
327.
by jmmcd 9y ago
Interesting: I didn't see any images of sneakers. I saw the Golden Gate bridge, and a vague shot of a woman. Are they serving a different set of images (and example js) to different readers?
328.
by jmmcd 9y ago
Great tutorial. I see active learning as a halfway house between supervised learning and reinforcement learning, because requesting labels is an action (as in RL), but of a very limited, predefined type. A lot of problems which we initially
329.
by jmmcd 9y ago
"Sublinear space algorithms" is another phrase that ends up meaning the same thing.
330.
by jmmcd 9y ago
Idea for an app (what I thought this was going to be): you take a photo of your problem. That can be that your tie is untied, your plug's fuse is blown, your cable is frayed, your haircut is bad, your kid is having a tantrum, you'

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