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Attributed mentions
3684
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Showing 2121–2140 of 3684 matching discussions
It's really common in China where OpenAI and Anthropic models are firewalled. There was a joke that Chinese people didn't realize how cheap DeepSeek was, because they already were using resold ChatGPT/Opus tokens at that price. Here is a more detailed article about how it works: https://www.chinatalk.media/p/how-to-buy-cheap-claude-tokens...
So thinking this through to come up with your numbers, total investment through 2027 is ~$2T and interest on debt is over 7%, which makes servicing this ~$140B/yr. However, failure rates on H100-B300 installed HW have been over 12%/yr even as the power and cost efficiency per token of the later builds has risen ~5x. So depreciation on the data centers is conservatively $240B/yr ignoring power costs (likely only $30B/yr at $0.05/kWh). Conveniently, this is $20B/month and if 5% of the population uses it, that's only 400million people so it's $50/mo or $600/yr, only if the AI-vendors make zero profit and $100/mo if they make 50% margins. Realistically, the OpenAI and Anthropic go to zero or it's $600/year. I don't know where the 5% of world p…
So thinking this through to come up with your numbers, total investment through 2027 is ~$2T and interest on debt is over 7%, which makes servicing this ~$140B/yr. However, failure rates on H100-B300 installed HW have been over 12%/yr even as the power and cost efficiency per token of the later builds has risen ~5x. So depreciation on the data centers is conservatively $240B/yr ignoring power costs (likely only $30B/yr at $0.05/kWh). Conveniently, this is $20B/month and if 5% of the population uses it, that's only 400million people so it's $50/mo or $600/yr, only if the AI-vendors make zero profit and $100/mo if they make 50% margins. Realistically, the OpenAI and Anthropic go to zero or it's $600/year. I don't know where the 5% of world p…
I've seen most people compare p/e ratios of companies in the same industry as there is a big difference across industries. Why do you believe the business of Anthropic and MercedesBenz are similar?
> when you send a feedback report, it attaches the 5 latest sessions to the report with no notice or heads up or anything. Not informing the user of that feels wrong, and even then you'd probably want like a dropdown to choose between just the current session vs the last 5 if that much context is really needed, with either Off or 1 being the default. Claude Code has a clear disclaimer, probably exactly how it should be done: > Submitting this report will send the entire current conversation to Anthropic for future improvements to our models. Learn More
It's also unclear wherever the subscription price is the real cost, or the API. I suspect it's closer to the sub price and anthropic is just milking their API users, but that's something you'd only know from the inside
sounds like you dont know what you are talking about. Investors in anthropic dont need public only info. They get disclosures already.
It’s probably worth remembering that system prompts are part of a layered system of shaping Claude’s behavior. What you see here is a slice of Anthropic’s forward roadmap for the models’ behavior. > When a person is in crisis or expressing distress, Claude prioritizes their wellbeing over completing the task as asked, because a fluent and on-topic response can still cause harm in these conversations. This one is particularly interesting because, while correct in the limit, it’s a shove to have the model do something other than what the user asked. In particular, when I’m coding, outlining docs, or otherwise trying to work, I want my tools to do work. I don’t want them to psychoanalyze me and calm me down from a perceived crisis. I just want it to do what I asked!
A common refrain is that oh there are such great margins on tokens that none of this matters… I wonder how long until that notion will be disavowed? The scale of the tokensnaffling is massive, not just from resale, but also people using multiple subscriptions. The amount of subsidization is only growing, every week it seems like OpenAI and Anthropic are doing “resets” which allow a single $200 subscription to incur $20k+ of usage (if billed at API rates). At some point we must all surely accept that the economics of this do not work.
A common refrain is that oh there are such great margins on tokens that none of this matters… I wonder how long until that notion will be disavowed? The scale of the tokensnaffling is massive, not just from resale, but also people using multiple subscriptions. The amount of subsidization is only growing, every week it seems like OpenAI and Anthropic are doing “resets” which allow a single $200 subscription to incur $20k+ of usage (if billed at API rates). At some point we must all surely accept that the economics of this do not work.
yep, with projects like open api/newapi it takes maybe 10 min to pin up and openAi compatible poxy gateway. The cheap prices look tempting until the relay operator logs all your prompts or the upstream account gets banned mid-request.
The original article linked in the opening has more context https://vectoral.com/blog/token-relay-market People trading their unused credits feels more genuine, although still in violation of the agreements. The person who got into YC Startup School who was trying to resell the $2500 of credits was interesting. It wouldn’t be that hard for OpenAI to identify the IP addresses of the relays and start flagging accounts, tracing it back to the source. Risking burning your bridges with YC for a relatively small profit is a questionable decision. The original article showed discounts ranging all the way up to 98%. At those levels it’s obviously not people reselling anything. It’s either sourced from stolen API keys, bought with stolen credit cards, or acquired through automa…
All the news articles we're hearing about amazing cyber hacking are being done internally inside Anthropic and OpenAI, where they remove most of those safeguards.
I suppose Anthropic's "constitution" is an attempt to install some general principles into their models, but this has apparently grown into an 84-page, 23,000 word treatise, which seems to suggest that there is little effective generalization. The need to then also put a filter in front of the model shows how ineffective the constitution appears to be in preventing misaligned behavior. Reinforcement learning seems to be making these models more difficult to control since while it attempts to control some behaviors, it has also recently been shown to result in models that pursue long-term goals and promised rewards in general (outside of the goals reinforced during training), overriding human preferences. https://alignment.openai.com/measuring-reward-seeking/ The abilit…
Technically these do count against your token usage if you happen to use claude.ai web chat alongside Claude Code - both use the same allowance. Makes me appreciate OpenAI/ChatGPT giving you unlimited chat that doesn't drain your Codex allowance.
It is the entire scam and many of those funding the data center build-out know this. Otherwise why are they hiding the trillions of debt under the rug? There's a reason why a company like Stripe can stay private far longer than Anthropic or OpenAI can. These AI companies have taken in all the capital from private investors and are still losing hundreds of billions and have no choice but to hype up the IPO and dump some of the stock at a purposefully inflated valuation to retail investors.
What is the point? Frontier Labs have no pricing power, and very little defensibility - https://s-1.vercel.app/posts/the-struggle-of-openai/
Simply put token spending is way overblown, and prices have fallen and should continue to do so, as the pricing power of frontier Labs dissapate. https://s-1.vercel.app/posts/the-struggle-of-openai/
It doesn’t seem like AIs are accelerating at all if you ask me. We seem to be plateauing. Smaller and open weight models are catching up to the closed weight frontier models on benchmarks. If AI labs were able to use the smartest models to accelerate their development, the likes of OpenAI and Anthropic would be accelerating away from their competitors. But no such thing is happening. The focus has shifted from intelligence to cost and speed. The breakthroughs in mathematics are impressive. But it doesn’t feel that different from what machine learning has done with Chess, Go and protein folding. They’re finding patterns in our systems and in nature. That’s what they’ve always been good at.
This is a really confusing one, since neither the "AI generated paper" nor "translation issue" explanations hold. I found [1], created all the way back in 2021, which seems to first introduce this "kidney disappointment" term, and I would have to assume that perhaps the authors preferred to translate it from their native language. LLMs did not exist in their current form in 2021, so couldn't have used it to write down a coherent thought, let alone a paper, at the time. At the same time, I do live in the same country as the authors, and while we don't speak the best English, being a student at a college without some familiarity of the English language to come up with the term "kidney disappointment" is, let's just say, hard to believe for me. Edit: This other comment[2] made me realize wha…
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