5 ms·

Yeah it's wild to me too, it feels like we are doing alchemy rather than programming, mixing intelligence out of a cauldron.

by Drakim 3y ago

echelon 3y ago
This whole field feels like magic, yet there are mathematical underpinnings behind all of it. I don't know why everyone isn't in love with this field. It's so utterly fascinating.
- JacksonWaschura 3y ago
  I couldn't agree more.
- mmoskal 3y ago
  I think it's a bit like saying microcode in CPU underpins high-level programming languages - kind of, but good luck understanding what a program does based on its microcode translation. OTOH you can mess with microcode and maybe get better performance, but you won't really know before you try. It's similar with ML - much more like alchemy than science...
- Almondsetat 3y ago
  Differential equations are mathematically quite simple, yet they are mostly intractable and the systems they describe chaotic and unpredictable. The mathematics in AI works similarly, being deceptively simple yet giving birth to incredible complexity
- emseetech 3y ago
  I'm not in love with it because it's magic. Not to say it isn't interesting, certainly it is, but I don't want my life ruled by magic. Predictability and reproducibility and a provenance of logic are important for computing systems and society as a whole.
  - olddustytrail 3y ago
    That's certainly an interesting viewpoint on life, but I suspect it's a very rare one simply because most people would never have considered it and those who had would tend towards the curious. You seem to be trapped in the interminable middle.
    - emseetech 3y ago
      I don't feel trapped. There is going to be (and has been in ways) a small reckoning when people realize magic (ai) and all its unpredictability is very difficult to manage. There is no field of "probabilistic UX" for example. How do you provide a consistent user experience when the underlying engine of your application is inconsistent? Same goes for QA, testing, root cause analysis. Adding features can have exponential side effects that cannot be predicted, which can be deadly at scale. Both figuratively and literally depending on how the technology is adopted.
      - echelon 3y ago
        > small reckoning when people realize magic (ai) and all its unpredictability is very difficult to manage. Deploy it in the right places first. Most people don't realize it's the arts where this works the best. They're too focused on LLMs and reasoning, but the first verticals that work will all be image, video, audio, and games. If you're imperfect, the human creator driving the creation can easily repair it. Nobody dies, no business is lost. Millions of hours are saved. Large capital intensive businesses get disrupted and democratized. Self-driving cars will be last.
        emseetech 3y ago
        > Deploy it in the right places first. 100% agreed. Unfortunately that’s not what we’re seeing.
      - bberenberg 3y ago
        > There is no field of "probabilistic UX" for example. How do you provide a consistent user experience when the underlying engine of your application is inconsistent? Sure there is. Every single in person store you go into and how staff are trained to interact with customers. It’s hard, and yet there are clear experts in it.
- moffkalast 3y ago
  Lots of reasons I suppose. Outside script-kiddying with mergekit it takes some serious knowledge to properly train anything, and expensive amounts of compute to actually do it or even run it in the end. It's not the most accesible thing. For classical methods once you got the algorithm nailed, it will work 100% of the time. For probabilistic methods, you do get better results most of the time but they can also screw up randomly for no reason so their deployability in production is hell on wheels. It's infuriating at times. Still can't argue against it being very fascinating.

Yeah it's wild to me too, it feels like we are doing alchemy rather than programming, mixing intelligence out of a cauldron.

by Drakim 3y ago

Yeah it's wild to me too, it feels like we are doing alchemy rather than programming, mixing intelligence out of a cauldron.

echelon 3y ago

This whole field feels like magic, yet there are mathematical underpinnings behind all of it. I don't know why everyone isn't in love with this field. It's so utterly fascinating.

JacksonWaschura 3y ago
I couldn't agree more.
mmoskal 3y ago
I think it's a bit like saying microcode in CPU underpins high-level programming languages - kind of, but good luck understanding what a program does based on its microcode translation. OTOH you can mess with microcode and maybe get better performance, but you won't really know before you try. It's similar with ML - much more like alchemy than science...
Almondsetat 3y ago
Differential equations are mathematically quite simple, yet they are mostly intractable and the systems they describe chaotic and unpredictable. The mathematics in AI works similarly, being deceptively simple yet giving birth to incredible complexity
emseetech 3y ago
I'm not in love with it because it's magic. Not to say it isn't interesting, certainly it is, but I don't want my life ruled by magic. Predictability and reproducibility and a provenance of logic are important for computing systems and society as a whole.
- olddustytrail 3y ago
  That's certainly an interesting viewpoint on life, but I suspect it's a very rare one simply because most people would never have considered it and those who had would tend towards the curious. You seem to be trapped in the interminable middle.
  - emseetech 3y ago
    I don't feel trapped. There is going to be (and has been in ways) a small reckoning when people realize magic (ai) and all its unpredictability is very difficult to manage. There is no field of "probabilistic UX" for example. How do you provide a consistent user experience when the underlying engine of your application is inconsistent? Same goes for QA, testing, root cause analysis. Adding features can have exponential side effects that cannot be predicted, which can be deadly at scale. Both figuratively and literally depending on how the technology is adopted.
    - echelon 3y ago
      > small reckoning when people realize magic (ai) and all its unpredictability is very difficult to manage. Deploy it in the right places first. Most people don't realize it's the arts where this works the best. They're too focused on LLMs and reasoning, but the first verticals that work will all be image, video, audio, and games. If you're imperfect, the human creator driving the creation can easily repair it. Nobody dies, no business is lost. Millions of hours are saved. Large capital intensive businesses get disrupted and democratized. Self-driving cars will be last.
      - emseetech 3y ago
        > Deploy it in the right places first. 100% agreed. Unfortunately that’s not what we’re seeing.
    - bberenberg 3y ago
      > There is no field of "probabilistic UX" for example. How do you provide a consistent user experience when the underlying engine of your application is inconsistent? Sure there is. Every single in person store you go into and how staff are trained to interact with customers. It’s hard, and yet there are clear experts in it.
moffkalast 3y ago
Lots of reasons I suppose. Outside script-kiddying with mergekit it takes some serious knowledge to properly train anything, and expensive amounts of compute to actually do it or even run it in the end. It's not the most accesible thing. For classical methods once you got the algorithm nailed, it will work 100% of the time. For probabilistic methods, you do get better results most of the time but they can also screw up randomly for no reason so their deployability in production is hell on wheels. It's infuriating at times. Still can't argue against it being very fascinating.