LLMs are already pretty intelligent; they can distinguish between strong and weak arguments, predict stances based on beliefs and demographic characteristics, and determine the appeal of an argument to an individual based on their traits. The paper below shows that LLMs perform
MACHINE LEARNING
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Dataset Quality: The Foundation of AI Model Performance
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The dataset is everything. Great read: https://
nonint.com/2023/06/10/the
-it-in-ai-models-is-the-dataset/
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Fast Generation in Large Models with Sparse Parameter Activation
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Not sure how it will play out, but it means that generations will be very fast for such a big model, as only a small portion of params will be active at a time.
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Snowflake Releases Largest Open-Source Model 482B Parameters
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Snowflake just launched the largest open-source model yet. A 482B parameter MoE. 17B active parameters and 128 experts, trained on 3.5T tokens. This model is more open than others — even the data recipe is open-source!
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Chanel emerges as major open source machine learning benefactor
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move over meta, the true biggest benefactor of open source machine learning is CHANEL
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ChatGPT keyboard shortcut extension for writing, coding, and blog posts
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9. CMJ
— God of Prompt (@godofprompt) 24 avril 2024
Improve your writing, get answers to coding questions & generate blog posts with ChatGPT keyboard shortcut.
Install this Chrome extension and press Cmd/Alt + J!https://t.co/REDEeFm4pg pic.twitter.com/QHCFTtpwmB9. CMJ Improve your writing, get answers to coding questions & generate blog posts with ChatGPT keyboard shortcut. Install this Chrome extension and press Cmd/Alt + J! https://
cmdj.app -
PhotoRoom Builds Custom Image Model Instead of Relying Closed AI
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Interesting in-depth read from @BenTheEgg about how PhotoRoom trained their own image model from scratch Another proof point that you should build your own ML capabilities rather than rely on closed AI
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Apple releases CoreNet: open neural network training library
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CoreNet looks to be the parent project – brand new on GitHub as of a few hours ago, "a library for training deep neural networks" Includes:
– OpenELM: a brand new LLM with open training data
– CatLIP: a CLIP-like model with more efficient training? More: https://
github.com/apple/corenet -
Apple Releases Significant ML and LLM Research
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Apple appear to have just released a huge volume of fascinating ML and LLM work in one go, I'm still trying to get my head around what they've published here
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Fine-tuning Primer: Guide to Timing, Budget, Data, and Tools
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Check out this informative primer on all things #finetuning from Daniel Porras Reyes at @flybridge
. Topics: When's the right time to fine-tune Budget / resource considerations Prepping data for fine-tuning Choosing the right tool Check it out: https://
pbase.ai/3JxpMI7