Attributed mentions
3684
Across all collected Hacker News results
Discussion intelligence
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
3684
Across all collected Hacker News results
Companies represented
14
Exact-name monitor matches only
Collection source
Hacker News
Latest new record seen
Source-backed records
Showing 3301–3320 of 3684 matching discussions
These are free due to some different type of reasons like Nvidida sponsoring free tokens or the model companies. My company checks the models and pays for Opus through AWS. You still send the WHOLE context of whatever you want to do to a random endpoint on the internet. If you want to write a good email, you give that context your email address, names, the reason for it etc. Big companies don't randomly use some random api endpoint to do so. Anthropics quarerly revenue is still growing very fast. I don't think we have seen even the real potenzial of it yet at all. Not only are still a lot of countries missing which do not even use anthropic or any other frontier model yet but also all the agentic based solutions enterprise companies are currently building on mass (at least in my industry)
> 2. OpenAI’s harness and network security controls were unintentionally so bad that it should reflect more poorly on them as a company more than it should reflect positively on their latest model. Why un intentionally? Move fast and break things implies intentionally bad controls. Can't get distracted from profit by such menial labor. Also remember, these are the same people we're supposed to trust to deliver the guardrails.
Isn't OpenAI burning billions and have billions more spending commitments? If they managed to downsize so much the cost they should have kept the price the same and become profitable, really weird move, unsure what led to this.
This doesn’t quite count as “API”, but OpenAI’s roll out of OAuth device code authentication was poor, to say the least.
> Aschenbrenner, who had no prior trading experience before starting the fund, worked for the FTX Future Fund, the philanthropic arm of Sam Bankman-Fried’s empire before it collapsed in late 2022. He later joined OpenAI’s “Superalignment” team before being fired over an alleged leak. A CV worthy of a bailout
5-10% over months would still be quite crazy. But yeah I do'nt want to know what Kimi 3 is pushing buttons inside Anthropic, OpenAI and Google. Besides any floor: For every year the tokens get faster and cheaper, we will see new things like properly working AI factories which mimic expert teams. A lot more parallism as well.
5-10% over months would still be quite crazy. But yeah I do'nt want to know what Kimi 3 is pushing buttons inside Anthropic, OpenAI and Google. Besides any floor: For every year the tokens get faster and cheaper, we will see new things like properly working AI factories which mimic expert teams. A lot more parallism as well.
> Google acting like a normal but competent company that's just chugging away Competent is a stretch. Google's AI offering seems to be, once again, PM led–lots of constantly-changing brands being merged and deprecated with zero customer support or service. They'll almost certainly be one of the survivors. Their technical competece is unmatched. But that doesn't mean they have a great product in the way both OpenAI and Anthropic do. (Outside their datacentres, which are a legitimate feat.)
> Google acting like a normal but competent company that's just chugging away Competent is a stretch. Google's AI offering seems to be, once again, PM led–lots of constantly-changing brands being merged and deprecated with zero customer support or service. They'll almost certainly be one of the survivors. Their technical competece is unmatched. But that doesn't mean they have a great product in the way both OpenAI and Anthropic do. (Outside their datacentres, which are a legitimate feat.)
I built this after noticing that Anthropic, Google and GitHub have each rebuilt the same fix for their CLIs to replace animated spinners and boxed tables with plain text if a screen reader is detected. Since there was no reusable version of this fix, I built one. It auto detects if it is running in a screen reader context and swaps the output automatically, as well as providing a linter to find these anti patterns in any codebase.
Anthropic basically downgraded all their tiers when they released Mythos, no nah, Sonnet 5 is the successor to Haiku 4.x
You actually can blame OpenAI for it. Because if a tool exists and people use it, that tool is an effective means of normalizing behaviour. We change our perception and behaviour through the use of tools, at least partially. So if someone invents a tool to do something poorly, and it becomes popular, then doing things poorly becomes more normalized. It can work in a positive direction, too. Have you ever used Vim or Emacs? Haven't you noticed how dedicating some time to learning a complex system like this also makes you proud of mastering a precise set of tasks? It almost becomes religious. The tool promotes care. We all have a societal responsibility to consider our inventions and what behaviour they'll encourage when people use them. OpenAI should also be held responsible, like all AI c…
So how exactly are people setting up these agents? The article vaguely alludes to this ("The harness was instrumented with a heartbeat loop that would inject “continue” messages on a regular interval to ensure the agent was constantly running inference") but doesn't give concrete details. Is this literally just an infinite loop in a bash shell injecting the initial prompt into the OpenAI CLI, and each run of the CLI picks up where it left off using some kind of persistent memory? Or is it a single context window? It sounds like the latter but it's not clear to me how this "continue" message is "injected", and surely one context window would be inneffective after just an hour or two. Sorry if this is a basic question but somehow I have missed the details of these kinds of agents.
Seems like they're working to destroy the local LLM argument. Right now Haiku is $1/$5 in/out. You can grind out $12,000 worth of haiku (or arguably, sonnet) class tokens in about 5 months on a Blackwell RTX 6000 96GB especially if using concurrency. BUT, but, if you use a g6e.xlarge on aws it's now more expensive than buying tokens from OpenAI @ $0.20/$1.20. It also destroys "the Mac Mini argument", pushing the ROI to ~4 years.
That’s ridiculous. Every major AI lab is compute constrained. That’s exactly why nvidia is worth trillions today. If OpenAI had a single extra GPU they’d be using it to run another training cycle or experiment for their next model.
You know SpaceX is still publicly valued at $1.5T marketcap, right? (offering price has nothing to do with anything other than ego of founders/bankers). Yes, I will wait for the correct valuation when all stocks enter the liquidity pool. OpenAI/Anthropic obscenely profitable is an easy bet (for me)
Methodology: HN Search returns recent public items matching a monitored company name. AIIStack stores a short normalized excerpt and the original link, deduplicates by company/provider/item ID, and creates an activity signal only after a threshold of newly observed records. Review the original discussion before making a decision.