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LLMs

Large Language Models (LLMs) are Transformer-architecture deep learning systems (e.g., GPT-4, Llama 3) trained on massive text corpora to generate, summarize, and reason over human language at scale.

LLMs are advanced deep learning models, specifically Generative Pre-trained Transformers (GPTs), designed to process and generate human-like text. They are trained on vast, multi-trillion-token datasets, giving them billions of parameters to learn complex linguistic patterns (syntax, semantics). This scale enables emergent capabilities: few-shot learning, code generation, and complex reasoning. Key examples include OpenAI's GPT-4, Google's Gemini, and Meta's Llama 3. LLMs power applications from conversational AI (ChatGPT) to automated content creation, fundamentally shifting how machines handle unstructured language.

https://en.wikipedia.org/wiki/Large_language_model
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Human-Centered AI: Design & Lean
Bogotá
GPT-4 ChatGPT
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GPT-4 LangChain
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LLMs OpenRouter
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Rust CLI
CircleCI: Production AI Agent Architecture
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LLMs LangChain
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Next SQL
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Julep AI LLMs
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LLMs LangChain
Meta-Agents: Building, Testing, Scoring
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LangChain LLMs
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OpenAI API Anthropic API
Compar:IA French Chatbot Dataset
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Hugging Face Python
CareCompanion AI: Virtual Caregiver
Singapore Jun 20
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San Francisco Jun 18
LLMs Code Interpretation
Maestro: Planning-Based AI Architecture
New York City May 19
AI21 Maestro Python
Benchmarking LLMs with Knowledge Graphs
Paris May 19
LLMs NetworkX