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Claude Opus 4.7

anthropic.com

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Re: Claude Opus 4.7

#971
post #121

Earlier quoted context omitted.

They don't have enough compute for all their customers. OpenAI bet on more compute early on which prompted people to say they're going to go bankrupt and collapse. But now it seems like it's a major strategic advantage. They're 2x'ing usage limits on Codex plans to steal CC customers and it seems to be working. It seems like 90% of Claude's recent problems are strictly lack of compute related.

Hard for me to reconcile the idea that they don't have enough compute with the idea that they are also losing money to subsidies.

- Not enough compute for the requests they have

- Selling those requests at less money than it cost to run the compute for those requests (because if you raise price clients go to openai)

The statements are not contradicting each other? They keep subsidizing to try to grow customer base, but they can't serve the customer base they have, they're expecting customer base grows faster than it drops from people bothered with rate limits (it probably will, average user won't hit rate limits enough to change)

Probably expecting a breakthrough in efficiency for compute, or getting enough cash flow (IPO?) to get more compute before it all comes crashing down

Re: Claude Opus 4.7

#972

I'm not sure how much I trust Anthropic recently. This coming right after a noticeable downgrade just makes me think Opus 4.7 is going to be the same Opus i was experiencing a few months ago rather than actual performance boost. Anthropic need to build back some trust and communicate throtelling/reasoning caps more clearly.

They don't have enough compute for all their customers. OpenAI bet on more compute early on which prompted people to say they're going to go bankrupt and collapse. But now it seems like it's a major strategic advantage. They're 2x'ing usage limits on Codex plans to steal CC customers and it seems to be working. It seems like 90% of Claude's recent problems are strictly lack of compute related.

Betting on continued exponential growth is basically a game of chicken. Growth has to slow down and level off at some point as adoption and usage saturates.

It's a bit like playing roulette by always betting on black and doubling your bet every time you lose. When you eventually, inevitably, do lose, your loss is going to be huge because you've been doubling your bet at each stage.

With LLM model generations and investment, it goes something like this. Let's say profits have been doubling year over year for each new model/investment cycle, and you want to bet on this doubling continuing forever.

Year 1 you get $10B in profit, and spend $20B on extra capacity for next year

Year 2 you get $20B in profit, and spend $40B on extra capacity

Year 3 you get $30B in profit, and spend $??? on extra capacity

You're already in trouble. Profit growth from Year 2 to 3 was "only" 50% vs the doubling you were gambling on, so you've now lost $10B ($40B spent only earnt you $30B of profit), and what are you going to do? Double down like the roulette player?

The longer the pattern of profit doubling goes, before it slows down, the worse it will end for you, since your bets are doubling each year. Saying "woo hoo, look at me! risk pays!" is a bit like saying the same while playing russian (not casino) roulette for money.

I worked for Acorn Computers UK in the early 80's and saw something similar firsthand. The brand new personal computer market was exploding, a once in a lifetime phenomenon, that no-one knew how to forecast. To make matters worse the market was highly seasonal with most sales at xmas, so the company had to guess what continued year-on-year exponential growth might look like (brand new market - no-one had a clue), and plan/spend ahead and stock warehouses full of computers ready for xmas. Sadly Acorn took the Sam Altman highly optimistic/irresponsible approach, got the forecast wrong, and was left with a huge warehouse full of rapidly depreciating computers. The company never fully recovered, although ARM rose out of the ashes.

Re: Claude Opus 4.7

#973

Earlier quoted context omitted.

This is the same paranoid, anxious behavior that ChatGPT has. One hell of a bad sign.

Models are not paranoid or anxious, they do not think or have feelings. I know you're probably using those words as a metaphor but we need to be careful about anthropomorphizing LLMs.

They are trained on natural language. Not anthropomorphizing them is the worse end of the spectrum.

Re: Claude Opus 4.7

#974
So many comments on Claude having gotten worse over the last weeks. Haven’t noticed it myself apart from one very stupid thing it did recently. Is there any proper data on this? I saw this one claim recently (can’t find the link) but I believe they didn’t run the same test twice but tested different things over time

Re: Claude Opus 4.7

#975
post #203

I'm finding the "adaptive thinking" thing very confusing, especially having written code against the previous thinking budget / thinking effort / etc modes: https://platform.claude.com/docs/en/build-with-claude/adapti... Also notable: 4.7 now defaults to NOT including a human-readable reasoning token summary in the output, you have to add "display": "summarized" to get that: https://platform.claude.com/docs/en/build-…

bigger change here might not be model quality, but debuggability.

once you hide the reasoning, remove the knobs, and let the model choose its own effort, it gets much harder to tell whether the model got worse or just got harder to inspect.

that’s a real shift. less tool, more black box.

Re: Claude Opus 4.7

#977
post #468

Quite a big improvement in coding benchmarks, doesn’t seem like progress is plateauing as some people predicted.

But it majorly regressed in long context retrieval? Which is arguably getting more and more important?

Supposedly that's because they stopped optimizing for MRCR and use GraphWalks as their measure of long context now: https://twitter.com/bcherny/status/2044821690920980626

Re: Claude Opus 4.7

#978
post #355

I've been using up way more tokens in the past 10 days with 4.6 1M context. So I've grown wary of how Anthropic is measuring token use. I had to force the non-1M halfway through the week because I was tearing through my weekly limit (this is the second week in a row where that's happened, whereas I never came CLOSE to hitting my weekly limit even when I was in the $100 max plan). So something is definitely off. and i…

They reduced the cache TTL to one hour so if you leave your prompt sitting idle for an hour at 700,000 tokens the next time you hit enter send it it will be completely uncached and eat a ton of tokens. Something to look at.

Re: Claude Opus 4.7

#979
post #835

I can't notice any difference to 4.6 from 3 weeks ago, except that this model burns way more tokens, and produces much longer plans. To me it seem like this model is just the same as 4.6 but with a bigger token budget on all effort levels. I guess this is one way how Anthropic plans to make their business profitable. During the past weeks of lobotomized opus, I tried a few different open weight models side by side wi…

Its funny to think that with a model release Anthropic can slide in some instructions ("be a bit more detailed" or something similar) that affect the token output by a few percent, 5-10%, which will not be noticeable by most users but over the course of the year would bring solid growth (once the VC craze is over, if ever) and increase income. "Regular companies" would love to have a growth like that without effectiv…

Like a reverse speed-up loop https://thedailywtf.com/articles/The-Speedup-Loop
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