And using RAG could close the gap even further between the performance of open source alongside the API providers, particularly for companies that don’t want to hand over control to a provider and are looking for a cheaper, faster, and perhaps more importantly, predictable tool.
TOOLS
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Open Source AI Models Accessible Without Fine-Tuning Resources
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It's a tantalizing prospect for companies that are exploring the use of open source models, but don't have the resources (personnel or financial) to fine-tune or pre-train a model. It works right out of the box without any significantly advanced technical requirements.
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Adding Memory to Frozen LLM Models Reduces Costs
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It offers the ability to endow a kind of "memory" to models that are frozen in time, as well as lower the overall cost of LLM usage. Or as @bobvanluijt told me, a way to make a stateless tool more stateful.
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RAG: Retrieval Augmented Generation Explained for Enterprises
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RAG stands for retrieval augmented generation, which enables companies to fetch important data relative to a query in a prompt in order to improve its results.
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RAG Emerges as Developer Priority for Model Performance Optimization
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Among all the developers, experts, and sources I talk to, no subject comes up more than RAG. Developers are increasingly working with it as a precursor to fine-tuning to squeeze more performance out of less-powerful models.
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Google TextFX: Creative Writing Tools for Rappers and Writers
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Playing around with @Google
’s TextFX this morning, a suite of 10 creative writing tools that are designed for “rappers, writers and wordsmiths.” It’s an experiment in Google Labs (
@GoogleAI
), so don’t expect a finished product, but it’s fun to explore and consider the -
Implementing AI: accessibility and RLHF resources
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Still a great list. Today I would add to dive as soon as possible in implementing something yourself since recent AI developments have become so accessible. We still need more good book/ressources on RLHF, maybe @natolambert or @_lewtun will fill this gap soon 🙂
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LangChain releases chat loaders for Llama fine-tuning event
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If you are in SF tmrw… there is a great event happening tmrw around finetuning Llama In anticipation of that we released some new loaders to help load chat data into an easy-to-use format: https://
blog.langchain.dev/chat-loaders-f
inetune-a-chatmodel-in-your-voice/
… Join the event here: -
RAG Systems Evaluation: Noah Chatbot Lessons Learned
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We had a REALLY fun webinar on evaluating RAG systems yesterday For me, the highlight was Pedro from Tavrn talking about lessons learned when building Noah (their context-aware chatbot) Now on YouTube for some Friday afternoon viewing! https://
youtube.com/watch?v=fWC4Vx
olWAk
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RAG Pipeline Technical Overview and Implementation Guide
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A great overview of what's going on under the hood in a RAG pipeline Thanks for writing this @czue
!