turmeric_root | 2 years ago | on: The Persistent Myth That Most Americans Are Miserable at Work
turmeric_root's comments
turmeric_root | 2 years ago | on: Saying Goodbye to OpenSubtitles.org API
whisper doesn't seem to support diarization (identifying when the speaker changes), which is needed for subtitle formatting.
turmeric_root | 2 years ago | on: Recursively summarizing enables long-term dialogue memory in LLMs
c'mon just write a function that takes in text and tells you whether or not it's true, how hard could it be
turmeric_root | 2 years ago | on: libjpeg-turbo 3.0 has been released, and why there may never be a 3.1
i think it'd be cool if you could make art and still own a house
turmeric_root | 2 years ago | on: Reddit Threatens to Remove Moderators from Subreddits Continuing Blackouts
> When users join a sub it's because they like the content and tacitly approve of the moderation.
I disagree, I see tons of people blaming admins for moderation actions and vice-versa.
turmeric_root | 2 years ago | on: Software developer gets $5M judgement against My Pillow CEO Mike Lindell
clearly the arbitration panel ruled against Lindell because it's part of the deep state. /s
turmeric_root | 2 years ago | on: MiniGPT-4
Windows reserves a certain percentage for VRAM for some reason. So I'd recommend Linux. Or find a way to disable the desktop/UI in Windows.
turmeric_root | 2 years ago | on: Sam Altman: OpenAI is not training GPT-5 and "won't for some time"
exactly! I gave a heartfelt letter to my shredder the other day and it simply destroyed it. issues like these are why AI alignment research is so critical.
turmeric_root | 2 years ago | on: Ask HN: Why don't smartphones encourage programming like early 80s computers?
Have you tried writing code on a smartphone?
turmeric_root | 2 years ago | on: Show HN: Debate Devil – AI debating practice app
this seems like it might be useful for arguing on HN
turmeric_root | 2 years ago | on: Sam Altman: OpenAI is not training GPT-5 and "won't for some time"
Worldcoin price skyrockets => cryptocurrency speculation returns => GPU shortage prevents further training of LLMs
turmeric_root | 2 years ago | on: Sam Altman: OpenAI is not training GPT-5 and "won't for some time"
Hell, what about Skynet?
turmeric_root | 2 years ago | on: The Coming of Local LLMs
The model weights were only shared by FB to people who applied for research access. Github repos containing links to the model weights have been taken down by FB.
turmeric_root | 2 years ago | on: The Coming of Local LLMs
I like using them for memeing
turmeric_root | 2 years ago | on: The Coming of Local LLMs
More VRAM => larger models. IME it is absolutely worth maxing out VRAM for the significant improvement in quality, especially with LLaMA (though even with a 4090, you won't be able to run the largest 65-billion parameter model even with 4-bit quantization).
That said, I recommend renting a cloud GPU for a few hours and trying the larger models on them before buying a GPU of your own, just to see if the models meet your requirements.
turmeric_root | 2 years ago | on: Unpredictable black boxes are terrible interfaces
they're just microdosing it's ok
turmeric_root | 2 years ago | on: Unpredictable black boxes are terrible interfaces
A lot of the 'look what I made with AI' images that get shared around also don't include the creator's workflow. There's usually lots of trial-and-error, manual painting/inpainting, multiple models involved etc. and explaining all that is a lot harder than just saying 'I used stable diffusion'.
turmeric_root | 2 years ago | on: Revert for jart’s llama.cpp MMAP miracles
ugh, that's so shitty. so many people in this space seem to be absurdly demanding and angry at devs, but one thing I've noticed is that every text AI project discord I've hung out in has this sleazy, obsessive 4chan /g/ vibe hiding somewhere in it.
turmeric_root | 2 years ago | on: Llama.cpp 30B runs with only 6GB of RAM now
> the "number B" stands for "number of billions" of parameters... trained on?
No, it's just the size of the network (i.e. number of learnable parameters). The 13/30/65B models were each trained on ~1.4 trillion tokens of training data (each token is around half a word).
turmeric_root | 3 years ago | on: Autodoc: Toolkit for auto-generating codebase documentation using LLMs
'accuracy' and 'truth' are legacy 0.1X concepts, move fast and break things
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