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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
142
Across all collected Hacker News results
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Showing 1–20 of 142 matching discussions
Otoh I don't care about the ethics of doing this to big companies like OpenAI and anthropic and not small ones
And that's why OpenAI bought all the future ram contracts
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 …
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 …
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.
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…
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.
I'm building a SaaS platform in Sri Lanka that handles documents and other sensitive data. Each user can upload their own documents and information, and the platform uses RAG to answer questions based on that user's data. That part makes sense to me. My main concern is what happens when the user hasn't uploaded enough information. I still want the LLM to provide accurate answers using reliable information from the internet (or from a curated knowledge base), with proper citations. These are the two architectures I'm considering: Option 1: Base LLM (OpenAI/Anthropic via Azure AI Foundry or Amazon Bedrock) ↓ Platform RAG (global knowledge base managed by us) ↓ User-specific RAG In this approach, we maintain a global knowledge base that we (the platform admins) curate and update. Every …
OpenAI has been way more aggressive about capacity than anyone else (as evidenced by the fact that it was them that caused the RAM price spike)
Which corruption exactly? NASDAQ giving them fast entry so the biggest IPO in history is done on NASDAQ and not on NYSE who was also competing for it? Both are fighting for OpenAI and Anthropic listings as well which likely influenced their choice to get in early with SpaceX
Weave is a React app that provides a multi-track timeline editor to perform basic video edits like trimming, stitching, transitions, audio tracks etc. which maps directly to an FFmpeg command to render the video. I tried my best to have the React "video" preview closely replicate the FFmpeg lavfi filtergraph output, but naturally this is not perfect (especially replicating the `eq` filter using SVG filters is quite inaccurate). I've built this as a prototype for another project I'm working on, so I don't plan to actively maintain it, but I thought it'd be cool to share it. Try it live: https://weave.salviano.xyz/
Curiosity: For most of the past five years, I've known ways to do better than Anthropic, OpenAI, and friends in many ways, at least on paper. I know I was right about many of them since many would show up 6-24 months later tools from the major providers, or otherwise become standard practice. A central problem is the Mythical Man-Month. True, I could do those, beating then-state-of-the-art, but only given 2-5 years. I suspect many other people knew about them too and could do so as well. As I noted above, throwing people and dollars caused many of those to be built in less time than I could have regardless. Other methods, I'm less confident about (>50%, <80%), but would lead to similar speeds, but would need $$$$$ in compute and engineering infrastructure to build out. E.g. they nee…
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