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.
@mattlynley
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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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RAG Dominates AI Discourse While Fine-tuning Costs Rise
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Did a deep dive into this yesterday! RAG is far and away the most-talked about subject in AI right now. Also important re: the costs for GPT-3.5 Turbo fine-tune which is… not cheap. https://
supervised.news/p/a-clever-way
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HuggingFace Model Creators vs Prompt Engineering Hackers
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To clarify, creators as in the developers posting models on HF, not the ones suggesting GPT hacks on whatever platforms
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Hugging Face Raises $4.5B: Enterprise Growth and Creator Support
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Got a chance to chat with Clement Delangue about Hugging Face’s new $4.5B valuation mega round. We talked spaces, breaking into enterprise, and ways to support AI “creators,” from outreach and communication to ideas for uses to support them via tips.
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Hugging Face balances free tools with enterprise adoption strategy
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HF's next act will be justifying that $4.5 billion valuation as it's still beholden to building a business (and its investors) to continue to grow. That means finding the right balance for its free tools remaining free while getting enterprises to adopt its model experience.
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Enterprise AI Security: Model Poisoning and Trust Challenges
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But there are a litany of other tasks in front of it. Security and trust has become a chief concern for enterprises—particularly model poisoning. There's the paradox of choice with those 1M models. Delangue sees HF as finding ways to help educate, not go full solutions architect.
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Hugging Face Balances Enterprise Growth With Community Model Sharing
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Part of the challenge for Hugging Face will be continuing to grow its enterprise core—an experience around models on Hugging Face with spaces and endpoints—while fostering its community that has uploaded more than 1 million models. As expected, GitHub is the model here.