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> 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 ot

> 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.
- 0xFACEFEED 5y ago
  Thank you for the thoughtful response. > The best technology winds up disappearing into the background and is unremarked-upon. Very much agree, but what I've seen is that DL based solutions do not disappear into the background. It's so rare for them to disappear into the background that, sitting here at my computer right now, thinking real hard, I can't come up with a single consumer DL product that works reliably. I'm pretty sure there are a few things but it's soooo rare. Face ID works most of the time but the success rate for me is like 1 in 50. It's very very cool technology but it's also very unreliable. Also if face ID never existed I don't think my life would be worse off in any way. The same basic issue I can apply to ever DL solution I can think of. The best way I can describe it is they feel... janky. Always janky. I've had similar conversations before and, after some back and forth, the bullish-on-AI person ends up saying much of what you said. Here's where we end up in a weird stalemate... > I also wouldn't characterize "ability to automatically detect cardiac episodes and summon help" as some kind of marginal improvement! Maybe not a marginal improvement, but there's a lot of amazing technology in the medical, industrial, and military sectors. For example people are surprised that FLIR was actively used in the military in the early 90s! I have no doubt that DL is going to drive a lot of the innovation in highly specialized areas. What I'm talking about (and terrible at communicating, honestly) is general purpose consumer applications. Can DL significantly improve the lives of every day people? Right now I'm seeing a lot of toy applications, innovation in highly specialized areas, and only hopeful ambition for general use. What I'm waiting for is that magic moment when I use a technology that a) works flawlessly and b) changes how I live my life. As soon as I see a DL based solution that does that then I'm sold. I just haven't seen it yet.
  - m_ke 5y ago
    Deep learning is narrowly applicable to every domain, that's the beauty of it. It's delivering 1.1-10x efficiency improvements for a lot of common workflows, which might not seem that impressive but really adds up. My cousin is an MMA fighter in another country, just today he got a contract from an american agent and asked me to translate it. I was able to throw it into google translate and in under 2 seconds it produced a flawless translation of 20 pages of legalese. I have a fairly affordable Hyundai that's able to drive 80 miles on a highway without me touching the steering wheel. I built an app that uses image recognition to automate food logging, from the surveys that we did it cut down the time to log from 15minutes a day to under 2. I've worked on systems to monitor patients at risk of falling in a hospital setting. My friend built Tonal, which can track your exercise form (https://www.tonal.com/ https://www.tonal.com/) Alphafold will be a huge deal for drug discovery. I can keep going

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.

0xFACEFEED 5y ago
Thank you for the thoughtful response. > The best technology winds up disappearing into the background and is unremarked-upon. Very much agree, but what I've seen is that DL based solutions do not disappear into the background. It's so rare for them to disappear into the background that, sitting here at my computer right now, thinking real hard, I can't come up with a single consumer DL product that works reliably. I'm pretty sure there are a few things but it's soooo rare. Face ID works most of the time but the success rate for me is like 1 in 50. It's very very cool technology but it's also very unreliable. Also if face ID never existed I don't think my life would be worse off in any way. The same basic issue I can apply to ever DL solution I can think of. The best way I can describe it is they feel... janky. Always janky. I've had similar conversations before and, after some back and forth, the bullish-on-AI person ends up saying much of what you said. Here's where we end up in a weird stalemate... > I also wouldn't characterize "ability to automatically detect cardiac episodes and summon help" as some kind of marginal improvement! Maybe not a marginal improvement, but there's a lot of amazing technology in the medical, industrial, and military sectors. For example people are surprised that FLIR was actively used in the military in the early 90s! I have no doubt that DL is going to drive a lot of the innovation in highly specialized areas. What I'm talking about (and terrible at communicating, honestly) is general purpose consumer applications. Can DL significantly improve the lives of every day people? Right now I'm seeing a lot of toy applications, innovation in highly specialized areas, and only hopeful ambition for general use. What I'm waiting for is that magic moment when I use a technology that a) works flawlessly and b) changes how I live my life. As soon as I see a DL based solution that does that then I'm sold. I just haven't seen it yet.
- m_ke 5y ago
  Deep learning is narrowly applicable to every domain, that's the beauty of it. It's delivering 1.1-10x efficiency improvements for a lot of common workflows, which might not seem that impressive but really adds up. My cousin is an MMA fighter in another country, just today he got a contract from an american agent and asked me to translate it. I was able to throw it into google translate and in under 2 seconds it produced a flawless translation of 20 pages of legalese. I have a fairly affordable Hyundai that's able to drive 80 miles on a highway without me touching the steering wheel. I built an app that uses image recognition to automate food logging, from the surveys that we did it cut down the time to log from 15minutes a day to under 2. I've worked on systems to monitor patients at risk of falling in a hospital setting. My friend built Tonal, which can track your exercise form (https://www.tonal.com/ https://www.tonal.com/) Alphafold will be a huge deal for drug discovery. I can keep going