RT @weights_biases: Looking to go beyond basic LLM experiments and build real, production-grade applications?. We have two free virtual cou….

RT @COLM_conf: 🏆🏆🏆🏆 Four papers at COLM were awarded outstanding paper awards. Congratulations to the authors!

RT @ParamBharat: The new @weights_biases RAG++ course uses the v2 API and the new command-r models. In addition to learning about nuanced R….

RT @soumikRakshit96: 📣 I am happy to announce that @weights_biases Weave is now integrated with Instructor (@jxnlco)!. 🧶 Weave will automat….

RT @weights_biases: Announcing our new RAG++ course, now available in collaboration with @CohereAI and @Weaviate_io. Created for engineers….

RT @morgymcg: Defining your grading criteria for LLM outputs is an organic process that evolves the more time you spend on it. In “Who Vali….

RT @capetorch: Today I gave @llama_index's workflows a go to tackle the NeurIPS AI hackercup competition. I created a Workflow to iterate….

RT @ParamBharat: I've been evaluating chunking mechanisms while prepping our RAG course's data ingestion lesson. Structured, semantic, an….

RT @morgymcg: ⚡️ AI Hacker Cup Lightning Comp. Today we're kicking off a ⚡️ 7-day competition to solve all 5 of the 2023 practice Hacker Cu….

RT @weights_biases: Join us on September 10 to learn how to build production-ready RAG systems. Learn from @ash0ts about optimizing pipelin….

RT @ParamBharat: Join me tomorrow. I'm presentimg a codegen agent featuring RAG-based episodic memory and reflexion. Whether you're aiming….

RT @morgymcg: Stoked to partner with the team to host 7 lectures, a lot of agents creativity needed . 📺 NeurIPS Me….

@GroqInc @e2b_dev @weights_biases Bonus tips for avoiding AI code hallucinations:. Curate your datasets carefully! Garbage in, garbage out. 🗑️.Watch out for those pesky imports in the outputs!.Don't forget unit testing & code reviews in your prompting! ✅.

Key takeaways from the @GroqInc webinar:. Iteration is key: Groq's speed lets you experiment with prompts super quickly!.Sandbox your code: Use @e2b_dev 's secure environments to test without risking production systems. 🧪.Track everything with @weights_biases Weave = figure out.

Had a super insightful webinar with @GroqInc on debugging AI-generated code! Their inference speed with Llama 3.1 is mind-blowing, making trial and error so much smoother.

RT @ayushthakur0: I will be talking tomorrow on-.- LLM landscape .- Need for structured output - function calling, json, constrained decodi….

RT @weights_biases: Hallucinations in AI-assisted coding are a significant challenge for developers. Join Daniel Loman from @GroqInc and @a….

RT @ayushthakur0: Evaluated Llama 3.1 70B (@FireworksAI_HQ) as well and is performant at the same level as Mistral Large 2 128B. - Llama i….

Check out the tool I use here called Weave @

Ran Chain of Density over the full 90 page Llama 3 paper. The user instruction was probably asking for too many things given the available output length. Any other questions I should ask to the paper?. Check out the Chain of Density process breakdown at: