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Master building enterprise LLM apps with RAG using Llama-3 at 1,000 tokens/s on SambaNova's platform, covering full-stack deployment with LangChain and vector databases.
Discover how to augment apps with AI for classification, search, summarization, and outlier detection using Hypermode to reduce infrastructure overhead and iterate quickly.
Discover how to leverage LLMs beyond code generation to 10x your development productivity through design patterns, declarative programming, and meta-programming techniques.
Master prompt engineering with Claude through hands-on workshops, live editing, and practical troubleshooting techniques for better AI interactions.
Discover how to rapidly prototype and deploy generative AI applications using AI templates and GitHub, leveraging Azure OpenAI services for quick startup solutions.
Dive into LLM debugging, finetuning with Unsloth, and advanced technical deep-dives including hand-derived derivatives and SOTA tricks for optimizing large language model performance.
Discover practical insights from 6 experts who share strategic, operational, and tactical lessons learned from building real-world LLM applications over the past year.
Discover how Cognition AI built Devin, a state-of-the-art AI software agent that helps developers save time and achieve more, with insights from CEO Scott Wu.
Explore OpenAI's multimodal future with live demos of GPT-4o Omnimodel Voice, ChatGPT Desktop, Sora, and Voice Engine in this comprehensive overview of cutting-edge AI capabilities.
Explore cutting-edge AI engineering through keynotes on multimodal AI, LLM applications, agent development, and real-world implementations from industry leaders.
Explore key AI engineering challenges including local models, transparency, tool usage, and prompt injection with insights from Datasette creator Simon Willison.
Discover how to build viral multimodal AI apps that scale to millions using Vercel AI SDK and v0.dev, from RoomGPT creator Hassan El Mghari in this weekend engineering guide.
Explore domain adaptation methods from prompt engineering to fine-tuning for LLMs, including operational best practices, evaluation techniques, and cost-benefit analysis.
Explore advanced AI engineering patterns including RAG, function calling, agents, monitoring tools, and LLM evaluation techniques in this comprehensive bootcamp session.
Dive into advanced AI inference techniques, comparing proprietary vs open models, deployment strategies, GPU arithmetic, and containerization for production systems.
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