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Holy cow their chatapp demo!!! I for first time thought i mistakenly pasted the answer. It was literally in a blink of an eye.!! https://chatjimmy.ai/ https://
by freakynit 8mo ago
Holy cow their chatapp demo!!! I for first time thought i mistakenly pasted the answer. It was literally in a blink of an eye.!!
https://chatjimmy.ai/ https://chatjimmy.ai/
- elliotbnvl 8mo agoThat… what…
- zwaps 8mo agoI got 16.000 tokens per second ahaha
- bsenftner 8mo agoI get nothing, no replies to anything.
- freakynit 8mo agoMaybe hn and reddit crowd have overloaded them lol
- gwd 8mo agoI dunno, it pretty quickly got stuck; the "attach file" didn't seem to work, and when I asked "can you see the attachment" it replied to my first message rather than my question.
- freakynit 8mo agoHmm.. I had tried simple chat converation without file attachments.
- scosman 8mo agoIt’s llama 3.1 8B. No vision, not smart. It’s just a technical demo.
- anthonypasq 8mo agowhy is everyone seemingly incapable of understanding this? waht is going on here? Its like ai doomers consistently have the foresight of a rat. yeah no shit it sucks its running llama 3 8b, but theyre completely incapable of extrapolation.
- amelius 8mo agoOK investors, time to pull out of OpenAI and move all your money to ChatJimmy.
- freakynit 8mo agoA related argument I raised a few days back on HN: What's the moat with with these giant data-centers that are being built with 100's of billions of dollars on nvidia chips? If such chips can be built so easily, and offer this insane level of performance at 10x efficiency, then one thing is 100% sure: more such startups are coming... and with that, an entire new ecosystem.
- codebje 8mo agoRAM hoarding is, AFAICT, the moat.
- freakynit 8mo agolol... true that for now though
- Windchaser 8mo agoYeah, just cause Cisco had a huge market lead on telecom in the late '90s, it doesn't mean they kept it. (And people nowadays: "Who's Cisco?")
- wmf 8mo agoThey did mostly keep it though.
- Windchaser 8mo agoSure, but it's taken their stock price about 20 years to recover.
- 8mo ago
- Etheryte 8mo agoIt is incredibly fast, on that I agree, but even simple queries I tried got very inaccurate answers. Which makes sense, it's essentially a trade off of how much time you give it to "think", but if it's fast to the point where it has no accuracy, I'm not sure I see the appeal.
- kaashif 8mo agoIf it's incredibly fast at a 2022 state of the art level of accuracy, then surely it's only a matter of time until it's incredibly fast at a 2026 level of accuracy.
- PrimaryExplorer 8mo agoyeah this is mindblowing speed. imagine this with opus 4.6 or gpt 5.2. probably coming soon
- scotty79 8mo agoI'd be happy if they can run GLM 5 like that. It's amazing at coding.
- Gud 8mo agoWhy do you assume this? I can produce total jibberish even faster, doesn’t mean I produce Einstein level thought if I slow down
- 8mo ago
- b0ner_t0ner 8mo agoI asked, “What are the newest restaurants in New York City?” Jimmy replied with, “2022 and 2023 openings:” 0_0
- jvidalv 8mo agoIs super fast but also super inaccurate, I would say not even gpt-3 levels.
- empath75 8mo agoThere are a lot of people here that are completely missing the point. What is it called where you look at a point of time and judge an idea without seemingly being able to imagine 5 seconds into the future.
- Alifatisk 8mo ago“static evaluation”
- roywiggins 8mo agoThat's because it's llama3 8b.
- smusamashah 8mo agoWith this speed, you can keep looping and generating code until it passes all tests. If you have tests. Generate lots of solutions and mix and match. This allows a new way to look at LLMs.
- MattRix 8mo agoThis is what people already do with “ralph” loops using the top coding models. It’s slow relative to this, but still very fast compared to hand-coding.
- Retr0id 8mo agoNot just looping, you could do a parallel graph search of the solution-space until you hit one that works.
- xi_studio 8mo agoInfinite Monkey Theory just reached its peak
- dave1010uk 8mo agoYou could also parse prompts into an AST, run inference, run evals, then optimise the prompts with something like a genetic algorithm.
- Epskampie 8mo agoAnd then it's slow again to finally find a correct answer...
- rvz 8mo agoFast, but stupid. Me: "How many r's in strawberry?" Jimmy: There are 2 r's in "strawberry". Generated in 0.001s • 17,825 tok/s The question is not about how fast it is. The real question(s) are: 1. How is this worth it over diffusion LLMs (No mention of diffusion LLMs at all in this thread) (This also assumes that diffusion LLMs will get faster) 2. Will Talaas also work with reasoning models, especially those that are beyond 100B parameters and with the output being correct? 3. How long will it take to create newer models to be turned into silicon? (This industry moves faster than Talaas.) 4. How does this work when one needs to fine-tune the model, but still benefit from the speed advantages?
- refsys 8mo ago[dead]
- simlevesque 8mo agoLLMs can't count. They need tool use to answer these questions accurately.
- CamperBob2 8mo agoThat particular one can't count without using external tools. Others can, and do.
- mike_hearn 8mo agoThe blog answers all those questions. It says they're working on fabbing a reasoning model this summer. It also says how long they think they need to fab new models, and that the chips support LoRAs and tweaking context window size. I don't get these posts about ChatJimmy's intelligence. It's a heavily quantized Llama 3, using a custom quantization scheme because that was state of the art when they started. They claim they can update quickly (so I wonder why they didn't wait a few more months tbh and fab a newer model). Llama 3 wasn't very smart but so what, a lot of LLM use cases don't need smart, they need fast and cheap. Also apparently they can run DeepSeek R1 also, and they have benchmarks for that. New models only require a couple of new masks so they're flexible.
- 8mo ago
- PlatoIsADisease 8mo agoWell it got all 10 incorrect when I asked for top 10 catchphrases from a character in Plato's books. It confused the baddie for Socrates.
- Rudybega 8mo agoWell yeah, they're running a small, outdated, older model. That's not really the point. This approach can be used for better, larger, newer models.
- qingcharles 8mo agoI asked it to design a submarine for my cat and literally the instant my finger touched return the answer was there. And that is factoring in the round-trip time for the data too. Crazy. The answer wasn't dumb like others are getting. It was pretty comprehensive and useful. While the idea of a feline submarine is adorable, please be aware that building a real submarine requires significant expertise, specialized equipment, and resources.
- robotpepi 8mo agoit's incredible how many people are commenting here without having read the article. they completely lost the point.
- rstuart4133 8mo ago> It was literally in a blink of an eye.!! It's not even close. It takes the eye 100mm .. 400ms to blink. This think takes under 30ms to process a small query - about 10 times faster.