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You're presupposing an answer to what is actually the most interesting question in AI right now: does scaling continue at a sufficiently favorable rate, and if

You're presupposing an answer to what is actually the most interesting question in AI right now: does scaling continue at a sufficiently favorable rate, and if so, how? The AI companies and their frontier models have already ingested the whole internet and reoriented economic growth around data center construction. Meanwhile, Google throttles my own Gemini Pro usage with increasingly tight constraints. The big firms are feeling the pain on the compute side. Substantial improvements must now come from algorithmic efficiency, which is bottlenecked mostly by human ingenuity. AI-assisted coding will help somewhat, but only with the drudgery, not the hardest parts. If we ask a frontier AI researcher how they do algorithmic innovation, I am quite sure the answer will not be "the AI does it for me."

asdff 8mo ago
Of course it continues. Look at the investment in hardware going on. Even with no algorithmic efficiency improvement that is just going to force power out of the equation just like a massive inefficient V8 engine with paltry horsepower per liter figures.
- getnormality 8mo ago
  I believe it continues, but I don't know if the rate is that favorable. Today's gigawatt-hungry models that can cost $10-100 per task or more to run... still can't beat Pokémon without a harness. And Pokémon is far from one task. I believe AGI is probably coming, but not on a predictable timeline or via blind scaling.
  - asdff 8mo ago
    The harness can be iterated upon (1). I don't think the sci fi definition agi is happening soon but, something more boring in the meanwhile that is perhaps nearly as destructive to life as we know it as knowledge workers today. That is, using a human still, but increasingly fewer humans of lower and lower skill as the models are able to output more and more complete solutions. And naturally, there are no geographic or governmental barriers to protect employment in this sector, or physical realities that demand the jobs take place in a certain place of the world. This path forward is ripe for offshoring to the lowest internet-connected labor available, long term. Other knowledge work professions like lawyer or doctor have set up legal moats to protect their field and compensation decades ago, whereas there is nothing similar to protect the domestic computer science engineer. By all means they are on this trajectory already. You often see comments on here from developers who say something along the lines of the models years ago needing careful oversight, now they are able to trust them to do more of the project accurately with less oversight as a result. Of course you will find anecdotes either way, but as the years go on I see more and more devs reporting useful output from these tools. 1. https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596
    - margorczynski 8mo ago
      > legal moats to protect their field I wonder how do they hold up when there's a big enough benefit of using AI over human work. Like how are politicians to explain these moats to the masses when your AI doctor costs 10x less and according to a multitude of studies is much better at diagnosis? Or in law? I've read China is pushing AI judges because people weren't happy with the impartiality of the human ones. I think in general people overestimate how much these legal moats are worth in the long run.
      - measurablefunc 8mo ago
        Who handles the liability when the AI makes a catastrophic error in your diagnosis?
        margorczynski 8mo ago
        Insurance? Some general fund ran by the government? There's a lot of options and the ones making the law can change it as seen fit.
        measurablefunc 8mo ago
        So profits go to the AI company but the liability is socialized? Where is the logic in your proposal?
      - asdff 8mo ago
        One might ask how they explain the moats already. A nurse can do plenty of what a doctor does. One questions if a law partner is really producing 10x the work of a new law grad to justify that hourly difference. Same is true for banking; all that money spent on salary, bonus, stock options, converted to luxury homes, products, and services, is surely a waste compared to the "efficiency" one might get out of a math post doctoral researcher clearing only $54k a year in academia. All examples of a field carving out a safe and luxurious harbor for themselves, protected by various degrees of regulation and cartel behavior, that has been practiced long enough now so as to be an unremarkable and widely accepted part of the field.
jwpapi 8mo ago
Honestly Im not even sure how much model improvement was in the last 12 months, or it was mainly harness improvement. It feels to me like I could’ve done the same stuff with 4, if I would be able to split every task into multiple subtasks with perfect prompts. So to me it could totally be that there is an inner harnessing happen that has been the recent improvements, but then I ask myself is this maybe the same with our own intelligence?
umairnadeem123 8mo ago
[dead]
p1esk 8mo ago
The AI companies and their frontier models have already ingested the whole internet Has the frontier models been trained on the whole of youtube?

asdff 8mo ago

Of course it continues. Look at the investment in hardware going on. Even with no algorithmic efficiency improvement that is just going to force power out of the equation just like a massive inefficient V8 engine with paltry horsepower per liter figures.

getnormality 8mo ago
I believe it continues, but I don't know if the rate is that favorable. Today's gigawatt-hungry models that can cost $10-100 per task or more to run... still can't beat Pokémon without a harness. And Pokémon is far from one task. I believe AGI is probably coming, but not on a predictable timeline or via blind scaling.
- asdff 8mo ago
  The harness can be iterated upon (1). I don't think the sci fi definition agi is happening soon but, something more boring in the meanwhile that is perhaps nearly as destructive to life as we know it as knowledge workers today. That is, using a human still, but increasingly fewer humans of lower and lower skill as the models are able to output more and more complete solutions. And naturally, there are no geographic or governmental barriers to protect employment in this sector, or physical realities that demand the jobs take place in a certain place of the world. This path forward is ripe for offshoring to the lowest internet-connected labor available, long term. Other knowledge work professions like lawyer or doctor have set up legal moats to protect their field and compensation decades ago, whereas there is nothing similar to protect the domestic computer science engineer. By all means they are on this trajectory already. You often see comments on here from developers who say something along the lines of the models years ago needing careful oversight, now they are able to trust them to do more of the project accurately with less oversight as a result. Of course you will find anecdotes either way, but as the years go on I see more and more devs reporting useful output from these tools. 1. https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596 https://news.ycombinator.com/item?id=46988596
  - margorczynski 8mo ago
    > legal moats to protect their field I wonder how do they hold up when there's a big enough benefit of using AI over human work. Like how are politicians to explain these moats to the masses when your AI doctor costs 10x less and according to a multitude of studies is much better at diagnosis? Or in law? I've read China is pushing AI judges because people weren't happy with the impartiality of the human ones. I think in general people overestimate how much these legal moats are worth in the long run.
    - measurablefunc 8mo ago
      Who handles the liability when the AI makes a catastrophic error in your diagnosis?
      - margorczynski 8mo ago
        Insurance? Some general fund ran by the government? There's a lot of options and the ones making the law can change it as seen fit.
        measurablefunc 8mo ago
        So profits go to the AI company but the liability is socialized? Where is the logic in your proposal?
    - asdff 8mo ago
      One might ask how they explain the moats already. A nurse can do plenty of what a doctor does. One questions if a law partner is really producing 10x the work of a new law grad to justify that hourly difference. Same is true for banking; all that money spent on salary, bonus, stock options, converted to luxury homes, products, and services, is surely a waste compared to the "efficiency" one might get out of a math post doctoral researcher clearing only $54k a year in academia. All examples of a field carving out a safe and luxurious harbor for themselves, protected by various degrees of regulation and cartel behavior, that has been practiced long enough now so as to be an unremarkable and widely accepted part of the field.

jwpapi 8mo ago

Honestly Im not even sure how much model improvement was in the last 12 months, or it was mainly harness improvement. It feels to me like I could’ve done the same stuff with 4, if I would be able to split every task into multiple subtasks with perfect prompts. So to me it could totally be that there is an inner harnessing happen that has been the recent improvements, but then I ask myself is this maybe the same with our own intelligence?

umairnadeem123 8mo ago

[dead]

p1esk 8mo ago

The AI companies and their frontier models have already ingested the whole internet Has the frontier models been trained on the whole of youtube?