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A source-linked Hacker News monitor for the tracked company graph. These are attributable public discussions—not sentiment, endorsements, or unverified company facts.
Attributed mentions
2835
Across all collected Hacker News results
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Showing 2681–2700 of 2835 matching discussions
Yes, it IS confident of its weights & biases... but, if you keep at it, Claude WILL find the smoking gun, eventually. Even a broken watch is correct twice a day ( unless it's a digital watch, without a battery, in which case, it's just broken... ) But seriously -- newer Claude (and OpenAI and Google and ???) models DO find the smoking gun, if you let them keep going until they reveal the weird chain of events that leads to a bug. I was seeing the most obscure UART driver bug, where it would work at 1,500,000 baud (!) but fail by only outputting the 1st char at 230.4k and 460.8k -- and it was due to a very narrow race that would check the buffer, if not full, insert a character, and return BUT sometimes the TX Complete interrupt would happen between the check and the insert, and something …
Wonder if that means if I knock out an app using a Claude Code sub in an afternoon, that would've taken me a week previously, and the result is better than what I could've done, does that mean that gross productivity went down? - I didn't make money, since I got paid for my time - Anthropic didn't make money, since the amount I paid them for AI is tiny This sounds wrong to me.
These aren't stolen credit cards. This hack works by maxing out subscription limits of the Anthropic/OpenAI plans, so you never pay additional API fees. It's fraud but not theft.
These aren't stolen credit cards. This hack works by maxing out subscription limits of the Anthropic/OpenAI plans, so you never pay additional API fees. It's fraud but not theft.
The only metric that matters is f(cost, time, task). If Anthropic has a SOTA model, it can easily distill every model in the pareto frontier and have the SOTA model route appropriately. They haven't felt the 'sting' yet to optimize that (still growing their ARR at a crazy growth rate) Ant can top any benchmark that measures f(cost, time, task). The only entities that can beat them in costs are infrastructure providers who can do optimization at that layer. But a pure Model company can *never* compete with Anthropic on f(cost, time, task) if they continue to have SOTA models
and Anthropic can top that benchmark if that's what the users are optimizing for...which is my original point
I don't understand this take. Ultimately, people pay for how much they're able to accomplish with the model, not raw token count. If Anthropic thought people could accomplish the same amount with fewer tokens, they'd adapt the harness to do that and then raise the cost of tokens to make more profit (or lose less).
It's not _theft_ because nothing is _stolen_. The tokens are being used in a way that breaches the contract agreed to by whomever set up the account with OpenAI, Anthropic, Kilo, Antigravity etc. but it's not theft.
The man just cannot stop. First, a lengthy introduction with caveats which can be used to hedge later. Then he goes all in on AI again. He is sponsored by the AI for Math Fund (Renaissance Technologies) and I'd really like a yes/no disclosure about OpenAI stock options. People give him the benefit of the doubt because he always has been unable to stay off the Internet for more than a day. But this is really unprecedented.
The problem with Empire of AI is that it takes such a scattergun approach and doesn't really build a coherent thesis. It is also very difficult to draw clear directional information from the book. I can strongly agree that OpenAI should not have put Kenyan workers in the position in which they were. I can also agree that they should take steps to ensure that it does not happen again. Hao's frequent retelling of the story in interviews tells me nothing about what is being done to address this concern. The criticisms of potable municipal water usage by datacentres in the book are hard to fault, but they have little to do with what most people think of as generative AI. Again, it does little to aid understanding of the resource usage of contemporary datacentres and the politics of their siti…
The problem with Empire of AI is that it takes such a scattergun approach and doesn't really build a coherent thesis. It is also very difficult to draw clear directional information from the book. I can strongly agree that OpenAI should not have put Kenyan workers in the position in which they were. I can also agree that they should take steps to ensure that it does not happen again. Hao's frequent retelling of the story in interviews tells me nothing about what is being done to address this concern. The criticisms of potable municipal water usage by datacentres in the book are hard to fault, but they have little to do with what most people think of as generative AI. Again, it does little to aid understanding of the resource usage of contemporary datacentres and the politics of their siti…
Hi HN - author here. Problem I kept hitting: ask the agent for a 15-line fix, get a 500-line renovation that still compiles and passes tests. Boffin is a small control layer for AI coding agents. Before an edit, it feeds the agent only the architectural constraints for the file it is about to touch, then makes it verify the result. Not another static AGENTS.md for the whole repo. On DuckDB, a guided refactor landed at +17 / -17 lines with 2,104 assertions passing. Same shape of cases also on FastAPI and LangChain (in the repo examples/). Try it: npx boffinit cursor Also works with Claude Code, Codex, and OpenCode. Happy to answer questions — especially if you have a place where the agent keeps "improving" load-bearing code.
We're not that deep yet. OpenAI has federal stakeholders, they're already playing dirty. Why you would give Scam Altman the benefit of the doubt is beyond my understanding.
that could also be just marketing. OpenAI has been doing the "too dangerous to release" playbook since GPT-2 at the very least.
You're mixing up a few things. A company valuation alone is irrelevant, you have to take in account the way it relates to the underlying business. In the case of both google and apple their valuation is mostly based on the fact that they own entire ecosystems and have consistently generated significant profits over decades. That's not the case of AI vendors. Their valuation is based solely on the belief they will eventually develop an actual business model. Apple and alphabet are both trading at something like 10x revenue, with very high operating margins. On the other hand you have AI vendors: OpenAI $852 valuation is ~34x revenue, with $14B losses projected for 2026. Their infra commitment through 2030 is more than $600B (that's on the low end of numbers floating around). Just for the i…
Nice research and structuring into 4-tier layer. For providers like Anthropic and OpenAI, subscription is the entry point for all these, right? Besides the measures proposed in the article, can token usage % determine these clusters of accounts?
I was primarily referring to the acquisition of musk's ai company. But the more general (and unfortunately widely accepted practice of) government contracting culture certainly applies to OpenAI and Anthropic as well. EDIT: cleaned up my comment; removed a more inflammatory claim about corruption in the private sector.
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