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Here's my interview with CNBC on how Zuckerberg's vacuous talking points about AGI and open source exist to distract from how Meta burned $180bn in capex (and more off-balance-sheet) to make also-ran LLMs that don't deliver an iota of the promise of "personal superintelligence."

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Ed Zitron

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185,952 görüntüleme • 2 gün önce •via X (Twitter)

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How can we use small LLMs to shift more AI workloads onto our laptops and phones? In our paper and open-source code, we pair on-device LLMs (ollama) with frontier LLMs in the cloud (OpenAI, Together), to solve token-intensive workloads on your 💻 at 17.5% of the cloud cost while maintaining 97.9% of the accuracy. See Gru and the Minions in action below, 🔉on please (h/t )!
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How can we use small LLMs to shift more AI workloads onto our laptops and phones? In our paper and open-source code, we pair on-device LLMs (ollama) with frontier LLMs in the cloud (OpenAI, Together), to solve token-intensive workloads on your 💻 at 17.5% of the cloud cost while maintaining 97.9% of the accuracy. See Gru and the Minions in action below, 🔉on please (h/t )!

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The future of AI is open-source. And ollama is the easiest way to build AI applications with open-source LLMs. Here's how to build a free, private RAG app using open-source tools. We'll use: - Ollama for LLMs and embedding models - PostgreSQL for data storage and retrieval - pgai Vectorizer for embedding creation and sync (I use Nomic for embeddings and tinnyllama as my LLM but you can substitute them for any models on Ollama)

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New short course on Fine-tuning LLMs! Many developers are moving beyond only prompting, to also fine-tuning LLMs - that is, taking a pre-trained model and training it further on your own data, which can deliver superior results inexpensively. In this course, Sharon Zhou, CEO of Lamini (disclosure: I’m a minor shareholder) shows you how to recognize when fine-tuning can be help, and how to train an open-source LLM on your own data. I hope you enjoy the course!

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5 years ago, Sam Altman said OpenAI had no plan to make money. The promise to investors? Build AGI -- then ask it how to generate a return. “If AGI is on the table, we take 1/1000th of 1% of the value, return it to investors, and figure out how to share the rest with the world.”

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Everyone's talking about Clawd - the personal AI that lives in your favorite messaging apps. I asked Peter Steinberger 🦞 (Clawd's creator) how he uses it himself. Here's Peter explaining how Clawd can: → Control his lights and Sonos → Watch his security cameras for strangers → Roast Peter on command 😅 Honestly, I have a ton of respect that Peter is building this for free and making it fully open source. 📌 Subscribe to get our full interview later this week:

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