491–500 of 1001 posts
Earlier quoted context omitted.
Dario said this in a podcast somewhere. The models themselves have so far been profitable if you look at their lifetime costs and revenue. Annual profitability just isn't a very good lens for AI companies because costs all land in one year and the revenue all comes in the next. Prolific AI haters like Ed Zitron make this mistake all the time.
Do you have a specific reference? I'm curious to see hard data and models.... I think this makes sense, but I haven't figured out how to see the numbers or think about it.
Earlier quoted context omitted.
Great question, and my guess: If you build React in C++ and Rust, even if the framework is there, you'll likely need to write your components in C++/Rust. That is a difficult problem. There are actually libraries out there that allow you to build web UI with Rust, although they are for web (+ HTML/CSS) and not specifically CLI stuff. So someone needs to create such a library that is properly maintained and such. And…
and why do they need react...
Most modern UI systems are inspired by React or a variant of its model.
Does anyone with more insight into the AI/LLM industry happen to know if the cost to run them in normal user-workflows is falling? The reason I'm asking is because "agent teams" while a cool concept, it largely constrained by the economics of running multiple LLM agents (i.e. plans/API calls that make this practical at scale are expensive). A year or more ago, I read that both Anthropic and OpenAI were losing money o…
Gemini-pro-preview is on ollama and requires h100 which is ~$15-30k. Google are charging $3 a million tokens. Supposedly its capable of generating between 1 and 12 million tokens an hour. Which is profitable. but not by much.
Earlier quoted context omitted.
A place I worked at used it as part of an interview question (it wasn't some pass/fail thing to get it 100% correct, and was partly a jumping off point to a different question). This was in a city where nearly everyone uses bicycles as everyday transportation. It was surprising how many supposedly mechanical-focused people who rode a bike everyday, even rode a bike to the interview, would draw a bike that would not w…
This is why at my company in interviews we ask people to draw a CPU diagram. You'd be surprised how many supposedly-senior computer programmers would draw a processor that would not work.
They are also giving away $50 extra pay as you go credit to try Opus 4.6. I just claimed it from the web usage page[1]. Are they anticipating higher token usage for the model or just want to promote the usage? [1] https://claude.ai/settings/usage
How long before the "we" is actually a team of agents?
Just tested the new Opus 4.6 (1M context) on a fun needle-in-a-haystack challenge: finding every spell in all Harry Potter books. All 7 books come to ~1.75M tokens, so they don't quite fit yet. (At this rate of progress, mid-April should do it ) For now you can fit the first 4 books (~733K tokens). Results: Opus 4.6 found 49 out of 50 officially documented spells across those 4 books. The only miss was "Slugulus Eruc…
> The smug look on Malfoy’s face flickered.
> “No one asked your opinion, you filthy little Mudblood,” he spat.
> Harry knew at once that Malfoy had said something really bad because there was an instant uproar at his words. Flint had to dive in front of Malfoy to stop Fred and George jumping on him, Alicia shrieked, “How dare you!”, and Ron plunged his hand into his robes, pulled out his wand, yelling, “You’ll pay for that one, Malfoy!” and pointed it furiously under Flint’s arm at Malfoy’s face.
> A loud bang echoed around the stadium and a jet of green light shot out of the wrong end of Ron’s wand, hitting him in the stomach and sending him reeling backward onto the grass.
> “Ron! Ron! Are you all right?” squealed Hermione.
> Ron opened his mouth to speak, but no words came out. Instead he gave an almighty belch and several slugs dribbled out of his mouth onto his lap.
Earlier quoted context omitted.
The estimation I did 4 months ago: > there are approximately 200k common nouns in English, and then we square that, we get 40 billion combinations. At one second per, that's ~1200 years, but then if we parallelize it on a supercomputer that can do 100,000 per second that would only take 3 days. Given that ChatGPT was trained on all of the Internet and every book written, I'm not sure that still seems infeasible. http…
How would you generate a picture of Noun + Noun in the first place in order to train the LLM with what it would look like? What's happening during that 1 estimated second?