4 ms·

The funny thing is Claude 4.0 isn't even that 'smart' from a raw intelligence perspective compared to the other flagship models. They've just done the work to

The funny thing is Claude 4.0 isn't even that 'smart' from a raw intelligence perspective compared to the other flagship models. They've just done the work to tailor it specifically for proper tool using during coding. Once other models catch up, they will not be able to be so stingy on limits. Google has the advantage here given they're running on their own silicon; can optimize for it; and have nearly unlimited cashflows they can burn. I find it amusing nobody here in the comments can understand the scaling laws of compute. It seems like people have a mental model of Uber burned into their head thinking that at some point the price has to go up. AI is not human labor. Over time the price of compute will fall, not rise. Losing money in the short term betting this will happen is not a dumb strategy given it's the most likely scenario. I know everybody really wants this bubble to pop so they can make themselves feel smart for "calling it" (and feel less jealous of the people who got in early) and I'm sure there will be a pop, but in the long term this is all correct.

macinjosh 1y ago
Prices for yesterday's frontier models will fall but there will always be the next big model. similar to how game graphics get ever better but ever more demanding at the bleeding edge.
- lillecarl 1y ago
  Yes but games also look an awful lot better (fidelity wise) than not so many years ago.
andix 1y ago
The thing is, all the models are not that 'smart'. None of them is AGI. Currently it's much more important to manage context, split tasks, retry when needed, not getting stuck in an infinite loop, expose the right tools (but not too many), ...
alphager 1y ago
Even if Moore's law was still in effect and the computer resources required stayed the same and compute stayed as efficient per watt (neither is true), it would just halve compute costs every 18 months. You're able to read about people hitting $4000 costs/month on the $200 plan upthread. That's 8 years until it's cost effective. Are they really ready to burn money for 8 years?
- pembrook 1y ago
  Uber operated at a loss for 9 years. They're now a profitable, market-winning business. Amazon operated at a loss for 9 years, and barely turned a profit for over a decade longer than that. They're now one of the greatest businesses of all time. Spotify operated at a loss for 17 years until becoming profitable. Tesla operated at a loss for 17 years before turning a profit. Palantir operated at a loss for 20 years before turning a profit. And this was before the real age of Big Tech. Google has more cashflows they can burn than any of these companies ever raised, combined.
  - klik99 1y ago
    Those aren’t good comparisons. Uber operated at a loss to destroy competition and raised prices after they did that. Amazon (the retailer) did the same and leveraged their position to enter new more lucrative markets. Dunno about Spotify, but Tesla and palantir both secured lucrative contracts and subsidies. Anthropic is against companies with deeper pockets and can’t spend to destroy competition, their current business model can only survive if they reduce costs or raise prices. Something’s got to give
    - pembrook 1y ago
      They are good comparisons. All startups go against incumbents/competitors with deeper pockets. Re: Anthropic specifically, I tend to agree, hence why I'm saying the deeper pockets (eg. Google, Amazon, etc) are perfectly positioned to win here. However, big companies have a way of consistently missing the future due to internal incentive issues. Google is deathly afraid of cannibalizing their existing businesses. Plus, there's many investors with deep pockets who would love to get in on Anthropic's next round if their technical lead proves to be durable over time (like 6 months in AI terms). This fight is still early innings.
      - willhslade 1y ago
        Haven't they already cannibalized search? It really sucks now.
lacker 1y ago
Will the other models really catch up, though? To me it seems like Anthropic's lead in programming has increased over the past year. Isn't it possible that over time, some models just become fundamentally better at some things than other models?
- danny_codes 1y ago
  I mean, not based on anything we’ve seen so far in the DL space. The algorithms are public, the compute is fungible: the only differentiator is data. But deepseek demonstrates that it’s somewhat easy to siphon data off other models so… yeah unclear where the moat is.
- mosdl 1y ago
  I've used Augment before moving to Claude, they are pretty similar, often can't tell the difference. I don't think there is that much difference in the dev focused llms.
- lelanthran 1y ago
  > Will the other models really catch up, though? To me it seems like Anthropic's lead in programming has increased over the past year. To me it seems that they are all converging over time. So what if one is "better"[1]? The others will soon be there too. [1] My experience with them is that Claude (Opus) is only slightly better than the competition at coding; it might do a better job on 2 out of every 5 tasks than the competition, but those people using the competition still get those two tasks done anyway.
layoric 1y ago
Claude is decent for sure, but if you are using these models for 'smarts', that is a whole separate problem. I also think honestly people are sleeping on Mistral's medium 3 and devstral medium. I know it isn't 'smart' either (none of them are), but for mundane tasks need valid code output, it is extremely good for the price.
- kadushka 1y ago
  I use o3 to brainstorm research problems, and it's been pretty useful. Especially the deep research feature.
  - layoric 1y ago
    As a sounding board for things you are already well familiar with, I agree, and have experienced the same, and that can be useful. It's also a much better experience than say using Google to do the same, or just a rubber ducky. The NLP these models can do is definitely impressive, but they aren't 'thinking'. I find myself easily falling into the habit of filtering a lot of what the model returns and picking out the good parts which is useful and relatively easy for subjects I know well. But for a topic that I am not as familiar with, that filtering (identifying and dismissing) I do is much less finessed, and a lot of care needs to be taken to not just accept what is being presented. You can still interrogate each idea presented by the LLM to ensure you aren't being led astray, and that is still useful for discovering things, like traditional search, but once you mix agents into this, things can go off the rails far too quickly than I am comfortable with.
com2kid 1y ago
> They've just done the work to tailor it specifically for proper tool using during coding. Once other models catch up, they will not be able to be so stingy on limits. I don't subscribe to the $100 a month plan, I am paying API usage pricing. Accordingly I have learned how to be much more careful with Claude Code than I think other users are. The first day I used it, Claude got stuck in a loop trying to fix a problem using the same 2 incorrect solutions again and again and burnt through $30 of API credits before I realized things were very wrong and I stopped it. Ever since then I've been getting away with $3-$5 of usage per day, and accomplishing a lot. Anthropic needs to find a way to incentivize developers to better use Claude Code, because when it goes off the rails, it really goes off the rails.
- nmadden 1y ago
  > The first day I used it, Claude got stuck in a loop trying to fix a problem using the same 2 incorrect solutions again and again and burnt through $30 of API credits before I realized things were very wrong and I stopped it. The worse it performs, the more you pay. That’s a hell of a business model. Will users tolerate that for long?
  - janejeon 1y ago
    > The worse it performs, the more you pay. That’s a hell of a business model. Will users tolerate that for long? I mean, AWS seems to be doing fine with that business model.
  - deleted 1y ago
    [deleted]
conartist6 1y ago
The problem with models is that they create lots of junk content. Industries can often get away with polluting when they're small, but once they reach planet scale salting the earth behind you is not as reliable of a tactic.
andrewstuart 1y ago
The latest trend for the anti AI folks is just to deny it - to say that developers are imagining the benefits and then they demand hard numbers and data and when such hard numbers are not produced - they claim victory.
qweiopqweiop 1y ago
I think you're right, but you're also ignoring the effects of monopolies and/or collusion. There's a absolutely a chance prices don't come down due to broader anti-competitive plays.

macinjosh 1y ago

Prices for yesterday's frontier models will fall but there will always be the next big model. similar to how game graphics get ever better but ever more demanding at the bleeding edge.

lillecarl 1y ago
Yes but games also look an awful lot better (fidelity wise) than not so many years ago.

andix 1y ago

The thing is, all the models are not that 'smart'. None of them is AGI. Currently it's much more important to manage context, split tasks, retry when needed, not getting stuck in an infinite loop, expose the right tools (but not too many), ...

alphager 1y ago

Even if Moore's law was still in effect and the computer resources required stayed the same and compute stayed as efficient per watt (neither is true), it would just halve compute costs every 18 months. You're able to read about people hitting $4000 costs/month on the $200 plan upthread. That's 8 years until it's cost effective. Are they really ready to burn money for 8 years?

pembrook 1y ago
Uber operated at a loss for 9 years. They're now a profitable, market-winning business. Amazon operated at a loss for 9 years, and barely turned a profit for over a decade longer than that. They're now one of the greatest businesses of all time. Spotify operated at a loss for 17 years until becoming profitable. Tesla operated at a loss for 17 years before turning a profit. Palantir operated at a loss for 20 years before turning a profit. And this was before the real age of Big Tech. Google has more cashflows they can burn than any of these companies ever raised, combined.
- klik99 1y ago
  Those aren’t good comparisons. Uber operated at a loss to destroy competition and raised prices after they did that. Amazon (the retailer) did the same and leveraged their position to enter new more lucrative markets. Dunno about Spotify, but Tesla and palantir both secured lucrative contracts and subsidies. Anthropic is against companies with deeper pockets and can’t spend to destroy competition, their current business model can only survive if they reduce costs or raise prices. Something’s got to give
  - pembrook 1y ago
    They are good comparisons. All startups go against incumbents/competitors with deeper pockets. Re: Anthropic specifically, I tend to agree, hence why I'm saying the deeper pockets (eg. Google, Amazon, etc) are perfectly positioned to win here. However, big companies have a way of consistently missing the future due to internal incentive issues. Google is deathly afraid of cannibalizing their existing businesses. Plus, there's many investors with deep pockets who would love to get in on Anthropic's next round if their technical lead proves to be durable over time (like 6 months in AI terms). This fight is still early innings.
    - willhslade 1y ago
      Haven't they already cannibalized search? It really sucks now.

lacker 1y ago

Will the other models really catch up, though? To me it seems like Anthropic's lead in programming has increased over the past year. Isn't it possible that over time, some models just become fundamentally better at some things than other models?

danny_codes 1y ago
I mean, not based on anything we’ve seen so far in the DL space. The algorithms are public, the compute is fungible: the only differentiator is data. But deepseek demonstrates that it’s somewhat easy to siphon data off other models so… yeah unclear where the moat is.
mosdl 1y ago
I've used Augment before moving to Claude, they are pretty similar, often can't tell the difference. I don't think there is that much difference in the dev focused llms.
lelanthran 1y ago
> Will the other models really catch up, though? To me it seems like Anthropic's lead in programming has increased over the past year. To me it seems that they are all converging over time. So what if one is "better"[1]? The others will soon be there too. [1] My experience with them is that Claude (Opus) is only slightly better than the competition at coding; it might do a better job on 2 out of every 5 tasks than the competition, but those people using the competition still get those two tasks done anyway.

layoric 1y ago

Claude is decent for sure, but if you are using these models for 'smarts', that is a whole separate problem. I also think honestly people are sleeping on Mistral's medium 3 and devstral medium. I know it isn't 'smart' either (none of them are), but for mundane tasks need valid code output, it is extremely good for the price.

kadushka 1y ago
I use o3 to brainstorm research problems, and it's been pretty useful. Especially the deep research feature.
- layoric 1y ago
  As a sounding board for things you are already well familiar with, I agree, and have experienced the same, and that can be useful. It's also a much better experience than say using Google to do the same, or just a rubber ducky. The NLP these models can do is definitely impressive, but they aren't 'thinking'. I find myself easily falling into the habit of filtering a lot of what the model returns and picking out the good parts which is useful and relatively easy for subjects I know well. But for a topic that I am not as familiar with, that filtering (identifying and dismissing) I do is much less finessed, and a lot of care needs to be taken to not just accept what is being presented. You can still interrogate each idea presented by the LLM to ensure you aren't being led astray, and that is still useful for discovering things, like traditional search, but once you mix agents into this, things can go off the rails far too quickly than I am comfortable with.

com2kid 1y ago

> They've just done the work to tailor it specifically for proper tool using during coding. Once other models catch up, they will not be able to be so stingy on limits. I don't subscribe to the $100 a month plan, I am paying API usage pricing. Accordingly I have learned how to be much more careful with Claude Code than I think other users are. The first day I used it, Claude got stuck in a loop trying to fix a problem using the same 2 incorrect solutions again and again and burnt through $30 of API credits before I realized things were very wrong and I stopped it. Ever since then I've been getting away with $3-$5 of usage per day, and accomplishing a lot. Anthropic needs to find a way to incentivize developers to better use Claude Code, because when it goes off the rails, it really goes off the rails.

nmadden 1y ago
> The first day I used it, Claude got stuck in a loop trying to fix a problem using the same 2 incorrect solutions again and again and burnt through $30 of API credits before I realized things were very wrong and I stopped it. The worse it performs, the more you pay. That’s a hell of a business model. Will users tolerate that for long?
- janejeon 1y ago
  > The worse it performs, the more you pay. That’s a hell of a business model. Will users tolerate that for long? I mean, AWS seems to be doing fine with that business model.
- deleted 1y ago
  [deleted]

conartist6 1y ago

The problem with models is that they create lots of junk content. Industries can often get away with polluting when they're small, but once they reach planet scale salting the earth behind you is not as reliable of a tactic.

andrewstuart 1y ago

The latest trend for the anti AI folks is just to deny it - to say that developers are imagining the benefits and then they demand hard numbers and data and when such hard numbers are not produced - they claim victory.

qweiopqweiop 1y ago

I think you're right, but you're also ignoring the effects of monopolies and/or collusion. There's a absolutely a chance prices don't come down due to broader anti-competitive plays.