341–350 of 822 posts
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Maybe. But that sounds like a large amount of bespoke work for what seems like a common problem?
I was talking about enterprise agents and then realized the question is more about coding agents.
Seems to be another great incremental update to the workhorse, nice! I've been using Sonnet instead of Opus for almost all coding tasks for a while now. A little elbow grease to break down tasks and you can spend a lot less money for just about the same output quality.
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At some point it's going to plateau, maybe already has. Then they will switch to FPGA/ASIC-based model-specific hardware for lower consumption. I'm pretty sure the "space data centers" won't use GPUs, they are not radiation-tolerant whereas FPGAs can be. https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest...
I would not take "space data centers" as a given! from most to least likely these will be vaporware, vaprorized-ware, rubble-ware, loss leaders.
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I think you should try an OpenAI model like GPT 5.5. It is better at following instructions and boundaries set during prompt. It feels like a more capable "agent assistant" than Claude models but without loss of intelligence. Most of my work involves "Agentic engineering" instead of fire-and-forget. I like to stay involved during the planning as well as review and ask a lot more questions from the agent than I've see…
I prefer GPT 5.5 to Opus but both are absurdly expensive token hogs, I can't afford to use either as my main model at $work with the monthly spend cap we have. I use Composer (since we use Cursor) or GPT 5.3-codex as my workhorse models and only break out the big guns when I have a genuinely difficult problem to solve. IMO somewhat weirdly 5.3-codex might be the best overall coding model OpenAI have ever released. It…
OpenAI claims to have made their new Terra model as good as GPT 5.5, but with half the cost per intelligence. Hopefully, this will bring it closer to the price you're expecting (or even better considering GPT models have good acceptance/success rates according to benchmarks).
Have they ever said what the difference is between Sonnet and Opus? Are they trained differently? Different architectures? Is Sonnet a distillation? Is it just that Sonnet has less resources for inference? None of the other labs are doing this kind of long lived two model series.
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I think they don’t understand that cybersecurity skills are what prevent bad code from making it into production. It’s like telling a chef to cook without a knife because knives can kill people. Dario and his lackeys at Anthropic aren’t visionaries.
I think you misunderstood what their vision is, or rather what their possible futures are. They are many steps ahead of almost everyone, both in wargaming possibilities and the actual realized path. What doesn’t make sense to you may be the only safe option for them.
Are there some Less Wrong posts or similar I should read that probably explain it?
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There’s no way to justify their valuations if they get downgraded to a pair programming tool. They need fully agentic stuff to work and replace human engineers to even come close. Offhand, I’m not even certain whether a model like that could justify the constant retraining we’re doing on the agentic models. It doesn’t make a lot of sense to spend millions or billions on training to reduce hallucinations by 0.3% if yo…
Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher/labor-share-of-gdp This source claims that knowledge workers alone (probably because they are paid much more) account for 35 - 50 Trillion of that: https://github.com/danielmiessler/Substrate/blob/main/Data/K... If LLMs can boost their productivity even by an…
Pre-bubble pricing: $1400 gets a 128GiB iGPU optimized for inference. Glm and kimi need 800-1000GiB. Call it 1TiB. The $1400 boxes could be ganged into sets of 4-8, with a switch. Call the switch $1000.
Each box has a TDP of 250W. 8 x 250/120V = 16.666A, or one household circuit in the US, so no new power infrastructure is needed.
$1400 x 8+1000=$12,200. Assuming standard five year depreciation, that’s $2440 a year. There are a billion knowledge workers alive today. So that’s $2.4T annual revenue. Average net profit margins on computer hardware are 4.3%. That works out to $105B net income, globally.
So, I guess the question is whether the (currently #2) open weight models provide $1.4-2.4T less value per year than the #1 and #3 models, and, if so, if customers can measure this, or are willing to spend 2x more and deal with censorship, data theft, intentional enshitification, sabotage, ads, product placement, etc, to get the slightly “better” model.
Also, note that my numbers assume moore’s law stopped for all time in 2024, but we’ve seen HW improvements since then.
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Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher/labor-share-of-gdp This source claims that knowledge workers alone (probably because they are paid much more) account for 35 - 50 Trillion of that: https://github.com/danielmiessler/Substrate/blob/main/Data/K... If LLMs can boost their productivity even by an…
I want to propose alternative reality where 1.5-2.5T in value doesn't go to a handful of companies. Instead it turns out to be like restaurants where this gets distributed to lots and lots of small, local, mostly interchangeable teams. There will of course be some super star "chefs" leading the industry and setting trends and some "restaurant chain" like big businesses and supply chain for all of this.
Claude Sonnet 5 is built to be the most agentic Sonnet model yet. It can make plans, use tools like browsers and terminals, and run autonomously at a level that, just a few months ago, required larger and more expensive models. I have been using Sonnet 4.6 more than Opus, because I'm mostly doing agent-assisted development and not fully agent-driven development. This announcement does not make me positive, I have fou…
Yeah, there's a real opportunity for one of these companies to invest time in a model that's tuned for, to use your term, agent-assisted developement. Trouble is, everyone inside their buildings seems to believe that no one will be working like that in a year or two.
I don't know if it's a matter of just requiring a tiny amount of optimization or wholesale redesign.
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Some napkin math -- total global labor compensation is about 50% of the GDP, which puts it in the USD 50 - 60 Trillion range: https://ourworldindata.org/grapher/labor-share-of-gdp This source claims that knowledge workers alone (probably because they are paid much more) account for 35 - 50 Trillion of that: https://github.com/danielmiessler/Substrate/blob/main/Data/K... If LLMs can boost their productivity even by an…
I am deeply surprised by the silence of philosophers, sociologists, liberal arts majors, economists. Where are the think tanks who contemplate and debate the societal aspects? The tech is advancing full steam but the "other side" doesn't feel anywhere nearly ready.
They'll show up after the fact and whinge endlessly about how they should have been involved.