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As a layman I wonder when we're going to start bearing the fruit of all this effort in DL. In the average person's day to day life I mean. I don't rely on DL d

As a layman I wonder when we're going to start bearing the fruit of all this effort in DL. In the average person's day to day life I mean. I don't rely on DL driven systems and I'm not even a skeptic. I want it to work. But I can't rely on these systems in the same way that I rely on my computer/phone, a light bulb, or a refrigerator. Is that ever going to change?

m_ke 5y ago
Most people unlock their phones using a deep learning model based facial recognition system, they talk to their devices thanks to deep learning, they translate documents with transformers, even google maps uses GNNs for ETA estimates and routing (https://arxiv.org/abs/2108.11482 https://arxiv.org/abs/2108.11482). The cameras on mobile phones got so much better thanks to deep learning, snapchat filters, zoom backgrounds, etc all use CNNs.
- edgyquant 5y ago
  These things work so well and are so ingrained we don’t even notice them: which is what we should be going for
potatolicious 5y ago
DL is already bearing fruit everywhere - the key is that the places where it works are narrow domains. In general the larger the scope of intelligent behavior the less successful it has been. Someone has already mentioned face unlock, but also dictation is miles ahead of where it used to be. Similarly text-to-speech is absurdly better than it used to be and is approaching indistinguishability from human speech in some cases (again, narrow domains are more successful!) Smartwatches are capable of detecting falling motion and alerting emergency responders, and are increasingly able to detect (some types of) cardiac incidents. Again here the theme is intelligent behavior in very narrow domains, rather than some kind of general omni-capable intelligence. The list goes on, but I think there's a problem where so many companies have overpromised re: AI in more general circumstances. Voice assistants are still pretty primitive and unable to understand the vast majority of what users want to speak about. Self-driving still isn't here. To some degree I think the overpromising and underdelivering re: larger-scoped AI has poisoned the well against what is working, which is intelligent systems in narrow domains, where they are absolutely rocking it.
- 0xFACEFEED 5y ago
  > the key is that the places where it works are narrow domains I've observed that not only are the domains narrow, but the domains of domains are narrow. In other words the real-world applications are mostly limited to pattern recognition, reconstruction, and generation. What I wonder is this. Is DL a dead end? Are we going to reach a ceiling and only have Face ID, Snapchat filters, spam detection, and fall detection to show for it? Certainly there'll be creative people that'll come up with very clever applications of the technology. Maybe we'll even get almost-but-not-really-but-still-useful-actually vehicle autonomoy. I can't imagine a world without the transistor, the internet, ink, smart phones, satellites, etc. What I'm seeing coming out of DL is super cool but it feels like a marginal improvement on what we have now and no more. And that's fine... but a lot of very smart people that I know are heavily investing in AI because they're banking on it being the new big technological leap.
  - potatolicious 5y ago
    > What I'm seeing coming out of DL is super cool but it feels like a marginal improvement on what we have now and no more "Marginal" here seems to be doing a lot of heavy lifting and IMO isn't fair. The ultimate point of technology isn't to inspire a Jetsons-like sense of wonder (though it is nice when it happens), it's to make life better for people generally. The best technology winds up disappearing into the background and is unremarked-upon. Like better voice recognition or text-to-speech. We've become accustomed to computers being able to read things without sounding like complete robots - and the technology has become so successful that it's simply become the baseline expectation - nobody says "wow Google Assistant sounds so natural" - but if you trotted out a pre-DL voice synthesis model it would be immediately rejected. I also wouldn't characterize "ability to automatically detect cardiac episodes and summon help" as some kind of marginal improvement! I think there's a bit of confusion here re: a desire for DL to be the revolutionary discovery that enables a sci-fi expectation of AI (self driving cars! a virtual butler!), vs. the reality of DL being a powerful tool that enables vast improvements in various narrow domains - domains that can be highly consequential to everyday life, but ultimately isn't very sci-fi. Does that make DL a dead-end? For those who practice it we aren't close to the limits of what we can do - and there are vast, vast use cases that remain to be tackled, so no? But for those whose expectations are predicated on a sci-fi-inspired expectation, then maybe? It's likely DL in and of itself won't lead us to a fully-conversant virtual butler, for example. [edit] And to be fair - the sci-fi-level expectations were planted by lots of people in the industry! Lots of it was mindless hype by self-described thought leaders and various other folks wanting to suck up investment money, so it's not fair to blame folks generally for having overinflated expectations about ML. There's been a vast amount of confusion about the technology in large part because companies themselves have vastly overstated what it is.
nly 5y ago
Amazon have already demonstrated till free grocery stores where you scan in, take what you want, and walk out. I expect this to be the norm in decade or two....fewer and fewer staff will be necessary
- mupuff1234 5y ago
  I think that's exactly the point - why hasn't Amazon rolled it into whole foods yet? DL makes for great constrained/cherry picked demonstrations, but it seems to fall flat on the last mile (unless the domain is extremely narrow).

m_ke 5y ago

Most people unlock their phones using a deep learning model based facial recognition system, they talk to their devices thanks to deep learning, they translate documents with transformers, even google maps uses GNNs for ETA estimates and routing (https://arxiv.org/abs/2108.11482 https://arxiv.org/abs/2108.11482). The cameras on mobile phones got so much better thanks to deep learning, snapchat filters, zoom backgrounds, etc all use CNNs.

edgyquant 5y ago
These things work so well and are so ingrained we don’t even notice them: which is what we should be going for

potatolicious 5y ago

DL is already bearing fruit everywhere - the key is that the places where it works are narrow domains. In general the larger the scope of intelligent behavior the less successful it has been. Someone has already mentioned face unlock, but also dictation is miles ahead of where it used to be. Similarly text-to-speech is absurdly better than it used to be and is approaching indistinguishability from human speech in some cases (again, narrow domains are more successful!) Smartwatches are capable of detecting falling motion and alerting emergency responders, and are increasingly able to detect (some types of) cardiac incidents. Again here the theme is intelligent behavior in very narrow domains, rather than some kind of general omni-capable intelligence. The list goes on, but I think there's a problem where so many companies have overpromised re: AI in more general circumstances. Voice assistants are still pretty primitive and unable to understand the vast majority of what users want to speak about. Self-driving still isn't here. To some degree I think the overpromising and underdelivering re: larger-scoped AI has poisoned the well against what is working, which is intelligent systems in narrow domains, where they are absolutely rocking it.

0xFACEFEED 5y ago
> the key is that the places where it works are narrow domains I've observed that not only are the domains narrow, but the domains of domains are narrow. In other words the real-world applications are mostly limited to pattern recognition, reconstruction, and generation. What I wonder is this. Is DL a dead end? Are we going to reach a ceiling and only have Face ID, Snapchat filters, spam detection, and fall detection to show for it? Certainly there'll be creative people that'll come up with very clever applications of the technology. Maybe we'll even get almost-but-not-really-but-still-useful-actually vehicle autonomoy. I can't imagine a world without the transistor, the internet, ink, smart phones, satellites, etc. What I'm seeing coming out of DL is super cool but it feels like a marginal improvement on what we have now and no more. And that's fine... but a lot of very smart people that I know are heavily investing in AI because they're banking on it being the new big technological leap.
- potatolicious 5y ago
  > What I'm seeing coming out of DL is super cool but it feels like a marginal improvement on what we have now and no more "Marginal" here seems to be doing a lot of heavy lifting and IMO isn't fair. The ultimate point of technology isn't to inspire a Jetsons-like sense of wonder (though it is nice when it happens), it's to make life better for people generally. The best technology winds up disappearing into the background and is unremarked-upon. Like better voice recognition or text-to-speech. We've become accustomed to computers being able to read things without sounding like complete robots - and the technology has become so successful that it's simply become the baseline expectation - nobody says "wow Google Assistant sounds so natural" - but if you trotted out a pre-DL voice synthesis model it would be immediately rejected. I also wouldn't characterize "ability to automatically detect cardiac episodes and summon help" as some kind of marginal improvement! I think there's a bit of confusion here re: a desire for DL to be the revolutionary discovery that enables a sci-fi expectation of AI (self driving cars! a virtual butler!), vs. the reality of DL being a powerful tool that enables vast improvements in various narrow domains - domains that can be highly consequential to everyday life, but ultimately isn't very sci-fi. Does that make DL a dead-end? For those who practice it we aren't close to the limits of what we can do - and there are vast, vast use cases that remain to be tackled, so no? But for those whose expectations are predicated on a sci-fi-inspired expectation, then maybe? It's likely DL in and of itself won't lead us to a fully-conversant virtual butler, for example. [edit] And to be fair - the sci-fi-level expectations were planted by lots of people in the industry! Lots of it was mindless hype by self-described thought leaders and various other folks wanting to suck up investment money, so it's not fair to blame folks generally for having overinflated expectations about ML. There's been a vast amount of confusion about the technology in large part because companies themselves have vastly overstated what it is.

nly 5y ago

Amazon have already demonstrated till free grocery stores where you scan in, take what you want, and walk out. I expect this to be the norm in decade or two....fewer and fewer staff will be necessary

mupuff1234 5y ago
I think that's exactly the point - why hasn't Amazon rolled it into whole foods yet? DL makes for great constrained/cherry picked demonstrations, but it seems to fall flat on the last mile (unless the domain is extremely narrow).