Showing results for "llm"
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LLM Production Chain (Inference, Deployment, CI/CD)AI Bootcamp- Map the end-to-end LLM production chain: data, serving, latency, monitoring - Explore multi-tenant LLM APIs, vector databases, caching, rate limiting - Understand tradeoffs between hosting vs using APIs, and inference tuning - Plan a scalable serving stack (e.g., LLM + vector DB + API + orchestrator) - Learn about LLMOps roles, workflows, and production-level tooling
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From Theory to Practice — Building Your First LLM ApplicationAI Bootcamp- Understand how inference works in LLMs (prompt processing vs. autoregressive decoding) - Explore real-world AI applications: RAG, vertical models, agents, multimodal tools - Learn the five phases of the model lifecycle: pretraining to RLHF to evaluation - Compare architecture types: generic LLMs vs. ChatGPT vs. domain-specialized models - Work with tools like Hugging Face, Modal, and vector databases - Build a “Hello World” LLM inference API using OPT-125m on Modal
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Navigating the Landscape of LLM Projects & ModalitiesAI Bootcamp- Compare transformer-based LLMs vs diffusion models and their use cases - Understand the "lego blocks" of LLM-based systems: prompts, embeddings, generation, inference - Explore core LLM application types: RAG, vertical models, agents, and multimodal apps - Learn how LLMs are being used in different roles and industries (e.g., healthcare, finance, legal) - Discuss practical project scoping: what to build vs outsource, how to identify viable ideas - Identify limitations of LLMs: hallucinations, lack of reasoning, sensitivity to prompts - Highlight real-world startup examples (e.g., AutoShorts, HeadshotPro) and venture-backed tools
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LLMOps & Scalable ServingAI BootcampPlan a scalable serving stack (LLM + vector DB + API + orchestrator), learn LLMOps roles and workflows.
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LLM Production ChainAI BootcampMap the LLM production chain (data, serving, latency, monitoring), explore multi-tenant APIs, vector databases, caching.
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Building Your First LLM ApplicationAI BootcampCompare architecture types (generic LLMs, ChatGPT, domain-specialized), use tools like Hugging Face and Modal, and build a “Hello World” LLM inference API with OPT-125m.
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LLM Inference BasicsAI BootcampUnderstand inference (prompt processing vs autoregressive decoding), explore real-world AI applications, and learn the five phases of the model lifecycle (pretraining to RLHF to evaluation).
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Limitations of LLMsAI BootcampIdentify LLM limitations (hallucinations, lack of reasoning, prompt sensitivity) and learn from real-world startup examples (e.g., AutoShorts, HeadshotPro).
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LLM Use Cases Across IndustriesAI BootcampExplore LLM applications in healthcare, finance, legal, etc., and discuss project scoping (what to build vs outsource, viable ideas).
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Understanding LLM Projects and ModalitiesAI BootcampCompare transformer-based LLMs vs diffusion models, explore LLM components (prompts, embeddings, generation, inference), and understand application types (RAG, vertical models, agents, multimodal).
