tikkun

29 ms·

361.
Declarai: A simple extensible framework for working with LLMs in software(github.com)
2 points by tikkun 3y ago|2 comments
362.
by tikkun 3y ago
Including the popup of how it works is neat! Edit: And I realize now it's also nice marketing - and I think it's tastefully done, too.
363.
by tikkun 3y ago
1) Low UI latency - I think this is partly why I dislike electron apps 2) Good UX (same principles apply everywhere) 3) Does something useful 4) Easy to install it and easy to pay for it (I love paying for apps, but only when it's easy
364.
by tikkun 3y ago
Do you mean for 2024, or do you mean for the remainder of 2023?
365.
by tikkun 3y ago
Nice! I’m guessing CPG type companies using it for product photos and such in particular
366.
by tikkun 3y ago
1) what do you want to use it for? 2) /r/localllama is good, and then also the “open llm leaderboard” and the “lmsys llm leaderboard”
367.
by tikkun 3y ago
Tbh I reference other notes by manually writing their name. I don’t do it much, if I was going to do a lot of that I’d use obsidian.
368.
Ask HN: What do you like for quick and easy (paid) back end hosting?
3 points by tikkun 3y ago|1 comments
369.
by tikkun 3y ago
In short, from a perspective of "can I train and get a job as a prompt engineer and just write great LLM prompts as a full time job" - no. From the perspective of - is there a skill to writing prompts that get good results from LL
370.
by tikkun 3y ago
Not GP commenter, but I've used Apple Notes, emacs org-mode, Evernote, Notion, Coda, Obsidian, and Google Docs. I prefer Apple Notes for personal notes, and Google Docs for shared notes, and Notion for ones that I publish as web pages.
371.
by tikkun 3y ago
This looks great, thanks See also this related tool: https://news.ycombinator.com/item?id=36907074
372.
by tikkun 3y ago
The image on the readme that talks about what the product does is a really nice way to do that - and in fact it's better than talking about what the product does because it's an example of an actual export - thanks for making this
373.
Ask HN: In which areas have you compared 3+ tools and formed strong preferences?
127 points by tikkun 3y ago|201 comments
374.
by tikkun 3y ago
I think you’re 100% right. I suspect a Reddit competitor that more closely copied Reddit would have much better odds of success.
375.
by tikkun 3y ago
Apply for the vercel accelerator, winners get OpenAI credits
376.
by tikkun 3y ago
The guide is copied below, from https://subredditstats.com/subreddit-user-overlaps/ -- #### I think this site may break or stop updating soon due to Reddit's API changes. I don't earn any money from this site
377.
Ask HN: Which Lemmy communities and instances are you visiting daily?
5 points by tikkun 3y ago|5 comments
378.
Ask HN: Which products that you use daily could be improved by LLMs?
1 points by tikkun 3y ago|2 comments
379.
by tikkun 3y ago
> All it takes is for a big successful deployment I think. Yes - I think one company doing a big deployment of AMD GPUs for training and inference would be extremely confidence boosting for other companies. I wonder why AMD doesn't
380.
by tikkun 3y ago
Side note: The current angle I'm thinking about for the post would be to actually use them all. Take Llama 2, and see which software and hardware approaches we can get inference working on (would leave training to a follow-up post), wr
381.
by tikkun 3y ago
Some are here - some of these are things people are using today, some are available but don't have much user adoption, some are technically available but very hard to purchase or rent/use, and some aren't yet available: * Sof
382.
H100s: Supply and Demand(gpus.llm-utils.org)
3 points by tikkun 3y ago|2 comments
383.
by tikkun 3y ago
It's a long read. I wrote it over the course of a month. GPUs are interesting. Yesterday had three front page posts about GPUs. The AMD driver thread I posted,[1] the SF Compute initiative for shared "burst" GPU rentals,[2] a
384.
by tikkun 3y ago
I'm not OP/submitter, but the main differentiator is that Lambda doesn't have on-demand availability for lots of interlinked H100s - you have to reserve them. Lambda has "Lambda Sprint" which is kinda similar,[1] bu
385.
by tikkun 3y ago
Additional clouds: For H100s and A100s - lambda, fluidstack, runpod. Also coreweave and crusoe and oblivus and latitude For non a/h100s: vast, Tensordock, also runpod here too
386.
by tikkun 3y ago
Couple things, mostly pricing and availability: 1) Margins. Public cloud investors expect a certain margin profile. They can’t compete with Lambda/Fluidstack’s margins. 2) To an extent also big clouds have worse networking for LLM trai
387.
by tikkun 3y ago
Some private cloud execs I talked with ballparked it at $15-25mm [1]. [1]: (I wrote this) https://gpus.llm-utils.org/nvidia-h100-gpus-supply-and-deman...
388.
by tikkun 3y ago
As context: 1x dgx gh200 has 256x gh200s which each have 1x h100 and 1x grace cpu
389.
by tikkun 3y ago
Nice. That does seem better (mostly because of the larger file size limit, diarization, word-level timestamps, increased speed, and hallucination and repetition reduction). I wondered what the rate limits are, looks like: > Use of Deepgr
390.
A dive into the AMD driver workflow(geohot.github.io)
153 points by tikkun 3y ago|76 comments

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