[nolemurs]

I've always understood the claim that deep learning scales to be a claim about deployment and use of trained models, not about training. The whole point is that you can invest (substantial) resources upfront to train a sufficiently good model, but then the results of that initial investment can be used with very small marginal costs.

OP's argument on this front seems disingenous to me.

His focus on Uber and Tesla (while not even mentioning Waymo) is also a truly strange omission. Uber's practices and culture have historically been so toxic that their failures here are truly irrelevant, and Tesla isn't even in the business of making actual self driving cars.

I'm the first to argue that right now AI is overhyped, but this is just sensationalist garbage from the other end of the spectrum.

[felippee]

Hi, it appears that "sensationalist garbage" triggered quite a bit of a discussion. This is typically indicative that the topic is "sensitive". Perhaps because many people feel the winter coming as well. Maybe, maybe not, time will tell.

And FYI, Tesla is in the business of making self driving car. If you read the article, you might learn that Tesla is actually the first company to sell that option to customers. You can go to their website right now and check that out.

Uber, like it or not is one of the big players of this game. I agree they may have somewhat toxic culture, but I guarantee you there are plenty of really smart people there who know exactly the state of the art. And their failure is therefore indicative of that state of the art.

I also omitted Cruise automation and a bunch of other companies, perhaps because they have more responsible backup drivers that so far avoided fatal crashes. But I analyze the California DMV disengagement reports in another post if you care to look. And by no means any of these cars is safe for deployment yet.

[nolemurs]

> Hi, it appears that "sensationalist garbage" triggered quite a bit of a discussion.

Yes. Sensationalist.

> I also omitted Cruise automation and a bunch of other companies, perhaps because they have more responsible backup drivers that so far avoided fatal crashes.

So your explicit reason for omitting Waymo, as I understand it, is that it didn't support your argument?

[felippee]

> Yes. Sensationalist.

Yes, perhaps. But I'm entitled to my opinion just as you are entitled to yours. And time will tell who was right.

> So your explicit reason for omitting Waymo, as I understand it, is that it didn't support your argument?

You see, when you make any argument, you always omit the infinite number of things that don't support it and focus on the few things that do. The fact that something does not support my argument, does not mean it contradicts it.

You might also note that this is not a scientific paper, but an opinion. Yes, nothing more than an opinion. May I be wrong? Sure. And yet this opinion appears to shared by quite a few people, and makes a bunch of other people feel insecure. Perhaps there is something to it? We will see.

But in the worst case it will make some people think a bit and make an argument either for or against it. I may learn today a good argument against it, that will make me think about it more and perhaps I will change my opinion, or I'll be able to defend it.

So far you have not provided such an argument, but I wholeheartedly encourage you to do so.

[gliboc]

This is a list of your phrases in this comment that I find, in my opinion, condescending.

> And time will tell who was right.

> You see, when you make any argument

> You might also note that this is not a scientific paper, but an opinion. Yes, nothing more than an opinion.

> And yet this opinion appears to shared by quite a few people, and makes a bunch of other people feel insecure. Perhaps there is something to it? We will see.

> So far you have not provided such an argument

I immediately identified this same tone in your paper. In your argumentation, you quite agressively hinted hat people which don't share your views are not very intelligent. You also have a tendency to present your sayings as prophetic, which appeared multiple times both in the paper and in this comment.

These observations put me in alarm towards your arguments, which I found mostly weak, sometimes used in bad faith. I flagged as such the Twitter argument, analysing the frequency of A. Ng's tweets, and denouncing its "outrageous claims", with an example where the AI score is overall only 0.025 less accurate than a practician.

I also thought that you used a different (your own) definition of scaling than most, and used it to make an argument, which was therefore unconvincing (but parent said that already).

Overall, to me, this was not a very pleasant read, and I dislike the fact that you attack the hype on machine learning by enjoying the polarization that comes with anti-hype articles such as yours. I also don't think that making people feel insecure is such a great indicator that what you're saying is relevant or prophetic.

I hope this helps you prophecies https://www.physics.ohio-state.edu/~kagan/AS1138/Lectures/Go... ;)

[nolemurs]

> You see, when you make any argument, you always omit the infinite number of things that don't support it and focus on the few things that do.

No. When I make an argument, I try to omit the infinite number of things I think are unlikely to be important, and focus on the few things that I think are most important whether they support my position or not.

Everyone's fallible, and I do my share of focusing too much on points that support my position over more important counter points, but I see that as a failing, not as the reasonable thing to do.