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I saw an ad recently "You'll never code as well as ChatGPT." I suspect we'll see some changes to both how and why people code, and it's entirely likely that app

by lumost 3y ago

I saw an ad recently "You'll never code as well as ChatGPT." I suspect we'll see some changes to both how and why people code, and it's entirely likely that application types which are difficult for AI to code will become scarcer. Similar dynamics have happened with cloud/mobile/commodity hardware/PC. Every time there is a change, there are folks who claim that the old way was easier and had been working forever.

sandspar 3y ago
I suspect as much as well. If AI makes it easier to produce certain products, then advertisers will do their damndest to create demand for those products. And if AI makes production cheaper, safer, and faster, then planners will orient their constructions and designs around making use of those efficiencies. Similar to how the widespread adoption of the car changed our cities, so too will AI change what we build, AI's limitations and all. I wouldn't be surprised if, at some point, we have a mental model of "things AI can build" and companies just assume that the majority of our solutions to problems will come from within that set. It doesn't even matter if those AI solutions don't fit the problems very well, as long as they're cheap. The smaller set of "things we still have to get humans to build" will cost more and therefore be de-emphasized and seen as a last resort. An equivalent might be producing features that introduce legal vulnerabilities. You can imagine lots of planners saying, "Can we do without that feature?"
- 082349872349872 3y ago
  I like this graphic of draft (working) horses vs. other (companion/sport) horses over time (1800-2010 in France): https://www.researchgate.net/publication/338480301/figure/fig1/AS:845430833283085@1578577826802/Evolution-of-the-horse-population-in-France-from-1800-to-2010-translated-from-French.ppm https://www.researchgate.net/publication/338480301/figure/fi... It shows clearly that farm (and transport) automation wiped out the draft horse population, but that the other horse population, having traversed the same bottleneck (ca. 1970), has rebounded. (and in fact there were absolutely more "others" in 2010 than there were in 1840) Moral: try to be the sort of programmer a little girl (little AI?) would love? > It had come to [Squealer's] knowledge, he said, that a foolish and wicked rumour had been circulated at the time of Boxer's removal. Some of the animals had noticed that the van which took Boxer away was marked "Horse Slaughterer," and had actually jumped to the conclusion that Boxer was being sent to the knacker's. It was almost unbelievable, said Squealer, that any animal could be so stupid. Surely, he cried indignantly, whisking his tail and skipping from side to side, surely they knew their beloved Leader, Comrade Napoleon, better than that? But the explanation was really very simple. The van had previously been the property of the knacker, and had been bought by the veterinary surgeon, who had not yet painted the old name out. That was how the mistake had arisen. —EAB
jasonjmcghee 3y ago
ChatGPT even with the best prompts is, in general, not great at coding. Being able to pass leet code isn't a threat to software developers. "You'll never code as well as ChatGPT" is just not true. It has next to no idea what it's doing, and this is very clear if you're experienced in software. It's useful as all hell, as a tool. But the original statement is wholly untrue.
- gravity2060 3y ago
  So true. Yet, right now it’s the worst it will ever be.
  - almatabata 3y ago
    There is the threat of model collapse though as discussed in this paper: https://browse.arxiv.org/pdf/2305.17493v2.pdf https://browse.arxiv.org/pdf/2305.17493v2.pdf? They discuss that if you train models with the output of other models you can get worse results. If we all start using code from those models how will that impact GPT-5?
    - MacsHeadroom 3y ago
      This paper is a joke in the ML community. Model collapse is not real. This paper made some seriously faulty assumptions in their contrived lab experiment. State of the art models are trained entirely or largely on "synthetic" generated datasets to surpass models trained on purely human data in quality and capability. Even training on uncurated synthetic generated data, from web scrapes after the advent of genersgofe AI, actually leads to more capabilities and quality in models in practice (the exact opposite of what is prediction by the failed model collapse paper).

by lumost 3y ago

sandspar 3y ago

I suspect as much as well. If AI makes it easier to produce certain products, then advertisers will do their damndest to create demand for those products. And if AI makes production cheaper, safer, and faster, then planners will orient their constructions and designs around making use of those efficiencies. Similar to how the widespread adoption of the car changed our cities, so too will AI change what we build, AI's limitations and all. I wouldn't be surprised if, at some point, we have a mental model of "things AI can build" and companies just assume that the majority of our solutions to problems will come from within that set. It doesn't even matter if those AI solutions don't fit the problems very well, as long as they're cheap. The smaller set of "things we still have to get humans to build" will cost more and therefore be de-emphasized and seen as a last resort. An equivalent might be producing features that introduce legal vulnerabilities. You can imagine lots of planners saying, "Can we do without that feature?"

082349872349872 3y ago
I like this graphic of draft (working) horses vs. other (companion/sport) horses over time (1800-2010 in France): https://www.researchgate.net/publication/338480301/figure/fig1/AS:845430833283085@1578577826802/Evolution-of-the-horse-population-in-France-from-1800-to-2010-translated-from-French.ppm https://www.researchgate.net/publication/338480301/figure/fi... It shows clearly that farm (and transport) automation wiped out the draft horse population, but that the other horse population, having traversed the same bottleneck (ca. 1970), has rebounded. (and in fact there were absolutely more "others" in 2010 than there were in 1840) Moral: try to be the sort of programmer a little girl (little AI?) would love? > It had come to [Squealer's] knowledge, he said, that a foolish and wicked rumour had been circulated at the time of Boxer's removal. Some of the animals had noticed that the van which took Boxer away was marked "Horse Slaughterer," and had actually jumped to the conclusion that Boxer was being sent to the knacker's. It was almost unbelievable, said Squealer, that any animal could be so stupid. Surely, he cried indignantly, whisking his tail and skipping from side to side, surely they knew their beloved Leader, Comrade Napoleon, better than that? But the explanation was really very simple. The van had previously been the property of the knacker, and had been bought by the veterinary surgeon, who had not yet painted the old name out. That was how the mistake had arisen. —EAB

jasonjmcghee 3y ago

ChatGPT even with the best prompts is, in general, not great at coding. Being able to pass leet code isn't a threat to software developers. "You'll never code as well as ChatGPT" is just not true. It has next to no idea what it's doing, and this is very clear if you're experienced in software. It's useful as all hell, as a tool. But the original statement is wholly untrue.

gravity2060 3y ago
So true. Yet, right now it’s the worst it will ever be.
- almatabata 3y ago
  There is the threat of model collapse though as discussed in this paper: https://browse.arxiv.org/pdf/2305.17493v2.pdf https://browse.arxiv.org/pdf/2305.17493v2.pdf? They discuss that if you train models with the output of other models you can get worse results. If we all start using code from those models how will that impact GPT-5?
  - MacsHeadroom 3y ago
    This paper is a joke in the ML community. Model collapse is not real. This paper made some seriously faulty assumptions in their contrived lab experiment. State of the art models are trained entirely or largely on "synthetic" generated datasets to surpass models trained on purely human data in quality and capability. Even training on uncurated synthetic generated data, from web scrapes after the advent of genersgofe AI, actually leads to more capabilities and quality in models in practice (the exact opposite of what is prediction by the failed model collapse paper).