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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
2851
Across all collected Hacker News results
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Showing 2301–2320 of 2851 matching discussions
> Action LLMs work by generating text underneath This isn't true. Obviously there is a lot of variety in architecture, but in the prototypical example there are vision and languages encoders and an action decoder which decodes direction into action steps. Eg, Hugging Face SmolVLA: > Specifically, the VLM processes sensorimotor states, including images from multiple RGB cameras, and a language instruction describing the task. In turn, the VLM outputs features directly fed to the action expert, which outputs the final 3 continuous actions .[1] Or NVidia's GR00T N1: > A diffusion transformer (DiT) processes the robot’s proprioceptive state and action, which are then cross-attended with image and text tokens from the Eagle-2 VLM backbone to output the denoised motor actions .[2] (Emp…
Author here — great question, and you've hit the exact reason the calculator uses an adjustable cache-hit ratio (default ~70%) instead of assuming 100%: real hit rates depend on session gaps, and TTLs differ a lot by provider. Rough current state: OpenAI's automatic caching typically keeps prefixes warm for ~5–60 min depending on load; Anthropic's default cache TTL is 5 min (extendable to 1h for an extra write fee); Gemini's explicit caches let you set your own TTL with per-hour storage pricing. So your 20-minute coffee break is usually fine on OpenAI, a cold cache on default Anthropic, and whatever you paid for on Gemini. Adding an "average gap between messages" input that derates the hit rate per provider is a really good idea — putting it on the list. Thanks!
$100/month * 12 months is 1200/year. Yeah, normal working people even in the USA don't have that extra money to spend. And let's be realistic: anyone doing the "greenhouse" method probably has both Anthropic and OpenAI $200/month subscriptions, otherwise, this is going to use up your tokens pretty fast. So $4800/year to have this as a normal practice that you do. The median household income in the US is $64000/year.
False dichotomy. The books could have been digitized WITHOUT being destroyed. There’s no reason to assume that digital ebooks/documents will be accessible or readable to anyone in say 75 years. A physical book will be just as accessible today, as it will be practically forever. Okay there’s the acid paper thing but still… there’s no reason for Anthropic to destroy the books.
It's been great. I hope they keep importing them, Qwen and Z.ai have done far more for humanity with that compute than Anthropic or OpenAI ever did.
Jesus christ, did you people watch those videos! there so long and coherent and WOW.
There's an env var you can set to tell it when to compact. It's especially helpful for models with big context that lose coherence much earlier.
> little demand for the AI compute power outside of OpenAI and Anthropic. I think every other business is going to slowly wake up to how powerful machine learning can be, and or, how important it will be to run your own models you can trust. I don't doubt that there is a bubble, but once the hardware is built, there will be plenty of customers. I guess if you overpay for hardware, you can be undercut by data centers built after the bubble pops, but that might just mean your return on investment is slower.
It has improved a lot, but these demo reels still have all AI video issues. Flash cut salad (including the scenes that should have longer cuts), unnatural motion that looks animated, unprompted YouTube-face acting, etc. Admittedly it's all a lot less pronounced in this version. What is much more interesting is how well it behaves off distribution (e.g. how far it can deviate from that movie/trailer aesthetics and still stay coherent)
There is a woman on twitter who makes seedance videos of her and Dario from anthropic, they're kinda weird but generally pretty high quality: https://x.com/CuiMao/status/2058458683781365873 (full collection: https://x.com/CuiMao/status/2082740754380984373 ) - seeing them was the first time I'd been impressed with AI video gen.
If you read more of Zitron's work, he says that there's little demand for the AI compute power outside of OpenAI and Anthropic. If they are bled dry, then the hyperscalers will not have enough customers for the data centers which they have blown so much capex spend on and will have to soon go into debt to ensure they can be built. The GPUs and the high bandwidth memory they use have little use other than to run and train these LLMs.
So right towards the end Zitron says it isn't clear what Google, MS and Amazons plan is. But he just finished explaining that Anthropic and Open AI are paying for them to build data centers, and implied that on face value, this was to rent the data centers back to Anthropic and Open AI. Seems to me they are just bleeding them dry so that when the money runs out for Anthropic and Open AI, they will be left with data centers that the can run their own (or open) models.
it seems perfect for that - maintaining coherence over 30s-1min type window is achievable and so many ads are built on unrealistic premise to begin with. To me, just reducing the cost alone seems secondary, far more important is putting the actual creative and marketing people directly in control of the output. Maybe the end result still gets sent to a pro studio for final production, but letting the true stakeholders directly create what they want could be a killer app. It may also be a terrible idea, like Homer Simpson's car - but that won't stop it being successful.
I think the big problem is administrative capacity. There are better run governments than we have in the US. The contempt for the state is a self-fulfilling prophecy. The state is incompetent because many of us believe it is inevitable that it will be. Compensation is just a part of it; coherent administration with continuity is even more important.
The funny thing is that in some cases using a different harness with the subscription plan could actually be very good for Anthropic: e.g. if I were to use smol with Opus, it could use fewer tokens than CC for the same task. People on subscription plans burning fewer tokens is a good thing for Anthropic. The only downside for Anthropic that I can see is that hitting your limits more often (while using CC) could make you want to upgrade plans, and a more efficient harness could keep you from doing that. But I can't imagine the cost (to Anthropic) of those inefficient tokens is worth it to them.
If you have dependents that are children, I feel there is a moral consideration. If you have earned $1M and then take the family to live who-knows-where slowly drawing on that $1M.. will your children be able to replicate your success? Will they be able to earn their own $1M? Or will leading this new life significantly impair their prospects? To me this is the most critical problem with the "move somewhere crazy cheap" plan. I feel a parent owes their children at least somewhat similar opportunities as they themselves had. If you got to work as " high flying white collar tech worker ", but the only option your children have is " subsistence fisherman ", you have wronged them.
There are thriving Ai video communities who are trying to replicate big budget productions with indie resources. Look up Gossip Goblin. There's a parallel explosion of memes at the same time, like Balenciaga Harry Potter
I also want to believe that Cursor team working on harnesses for much longer then openAI and Anthropic can deliver better results overall. Claude code is being pretty much vibe-coded slop doesn’t give a feel of a good product.
From a job listing I saw here on the front page today. Instantly repulsive: > About the role > "Men wanted for hazardous journey. Low wages, bitter cold, long hours of complete darkness. Safe return doubtful. Honour and recognition in event of success" > You gotta be in founder mode. > Next.js web / React Native app. / Supabase, firebase, and Prisma. / Nest.js for WhatsApp / Open AI and Anthropic APIs for agents / Solidity and web3.js for Smart contracts. / A lot of Typescript. It is a reference, but seemingly also sincere, at least to a non-trivial extent. Edit: I do not mean this to imply the same company as in the OP
I don't mean replicating the exact order of results, I mean I cannot replicate any of the alleged bugs. When you're reporting bugs and especially when you're making such a strongly-worded claim, it's best practice to be as detailed as possible. The claim is "a huge majority" of queries are fundamentally breaking logical operators. My point is that if you're reporting a bug you claim is so systemic it has made the product useles, sharing just one cropped screenshot with zero details about the actual query isn't very helpful.
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