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Discrediting work being done by others in the realm of self driving cars is rarely a good segway for introducing a company that automates checkout-free stores p

Discrediting work being done by others in the realm of self driving cars is rarely a good segway for introducing a company that automates checkout-free stores powered by machine learning / image recognition (which the articles builds up to). Sure, the developments have been quite disappointing for the cars but that's a way bigger challenge that currently has examples running. And what is the source of that disappointment? "X said it should be there in 3 years and it's not so it's a fail", really? That strikes me as dismissive and at best counter productive. Marketing and developping are two different things, don't use the shortcomings of the former to discredit the latter. It doesn't help anyone, especially new people joining the field. > "The deep learning hype is now deflating pretty strongly too, with even the biggest "enthusiasts" now admitting that things ain't as rosy as they were hoping." This comes out as bad faith, so a reference would be needed... Andrew NG was pointing at the use of wrong/bad data, and not the models or approach per se... So yeah, crapping on a trendy topic (deep learning) to market your venture that ironically itself uses that trendy topic (i quote "artificial intelligence"), is at best totally uncool...

DoingIsLearning 5y ago
I read it in quite the opposite direction, the cautionary note here is that if you overpromise and under deliver you might be able to secure early funding but eventually you precipitate yet another AI winter. The author, as someone in the space, is cautioning for more realism which arguably is lacking in public communications within that field.
- ghaff 5y ago
  I think his last paragraph makes that very clear and echoes a conversation I was having with someone last week. There are a lot of practical if often boring wins to be had. We're just probably not going to get some of the things like "never need to own/drive a car" that had some people so excited. As the piece articulates, there has been a big deflation of many high expectations from "just around the corner" to "maybe in 40 or 50 years."
  - WDCDev 5y ago
    Has there? I can't imagine investors/corporations dumping billions, annually, into an project which won't produce a return for 40-50 years.
    - ghaff 5y ago
      >Has there? Yes? That's what the whole article is about. To be clear, it's doubtless brought benefit to assistive driving systems. And we may even see full autonomy under limited conditions (e.g. specific limited access highways in good weather) in a significantly shorter period of time. But door to door robo taxis? Seems highly unlikely. >I can't imagine investors/corporations dumping billions There have been big pullbacks. And I wouldn't be the slightest bit shocked if Google/Alphabet pull the plug on Waymo one of these days--especially if they have to start tightening their belt for some reason.
      - WDCDev 5y ago
        > Yes? That's what the whole article is about. Articles like this have been written for 5 years now, but the money keeps flowing into these projects. Argo, Aurora and Aptiv etc. are all still burning mountains of cash. I am shocked the industry didn't take Uber/Lyft selling off their self-driving divisions as the signal to stop funding these efforts.
        ghaff 5y ago
        Lots of stupid money flowing around these days. I'm genuinely curious how the various self-driving efforts broke down among: - We can do it! - Maybe we can't do it but even partial success makes it worthwhile - What a pipe dream but it would be morally wrong not to separate greedy VCs from their cash I do think it's different from 5 years ago. Yes, some researchers were throwing cold water on the idea then but they were seen as contrarians. And, on boards like this one, you'd have no shortage of people going but Waymo is going to have a taxi service next year! Today, it's closer to being accepted wisdom.
PaulDavisThe1st 5y ago
> Andrew NG was pointing at the use of wrong/bad data, and not the models or approach per se... Except that Deep Learning is equal parts data & model. And he wasn't saying that the data was bad, he was saying that it turns out that the data collected turned out to be so context-dependent that it wasn't usable with even a small change in that context. That's not "bad data", that's "the real world".

DoingIsLearning 5y ago

I read it in quite the opposite direction, the cautionary note here is that if you overpromise and under deliver you might be able to secure early funding but eventually you precipitate yet another AI winter. The author, as someone in the space, is cautioning for more realism which arguably is lacking in public communications within that field.

ghaff 5y ago
I think his last paragraph makes that very clear and echoes a conversation I was having with someone last week. There are a lot of practical if often boring wins to be had. We're just probably not going to get some of the things like "never need to own/drive a car" that had some people so excited. As the piece articulates, there has been a big deflation of many high expectations from "just around the corner" to "maybe in 40 or 50 years."
- WDCDev 5y ago
  Has there? I can't imagine investors/corporations dumping billions, annually, into an project which won't produce a return for 40-50 years.
  - ghaff 5y ago
    >Has there? Yes? That's what the whole article is about. To be clear, it's doubtless brought benefit to assistive driving systems. And we may even see full autonomy under limited conditions (e.g. specific limited access highways in good weather) in a significantly shorter period of time. But door to door robo taxis? Seems highly unlikely. >I can't imagine investors/corporations dumping billions There have been big pullbacks. And I wouldn't be the slightest bit shocked if Google/Alphabet pull the plug on Waymo one of these days--especially if they have to start tightening their belt for some reason.
    - WDCDev 5y ago
      > Yes? That's what the whole article is about. Articles like this have been written for 5 years now, but the money keeps flowing into these projects. Argo, Aurora and Aptiv etc. are all still burning mountains of cash. I am shocked the industry didn't take Uber/Lyft selling off their self-driving divisions as the signal to stop funding these efforts.
      - ghaff 5y ago
        Lots of stupid money flowing around these days. I'm genuinely curious how the various self-driving efforts broke down among: - We can do it! - Maybe we can't do it but even partial success makes it worthwhile - What a pipe dream but it would be morally wrong not to separate greedy VCs from their cash I do think it's different from 5 years ago. Yes, some researchers were throwing cold water on the idea then but they were seen as contrarians. And, on boards like this one, you'd have no shortage of people going but Waymo is going to have a taxi service next year! Today, it's closer to being accepted wisdom.

PaulDavisThe1st 5y ago

> Andrew NG was pointing at the use of wrong/bad data, and not the models or approach per se... Except that Deep Learning is equal parts data & model. And he wasn't saying that the data was bad, he was saying that it turns out that the data collected turned out to be so context-dependent that it wasn't usable with even a small change in that context. That's not "bad data", that's "the real world".