Generative AI

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7 GitHub Repos to Build Al Agents 👇 1/ AutoGPT — https://github.com/Significant-Gravitas/AutoGPT 2/ LangChain — https://github.com/langchain-ai/langchain 3/ Dify — https://github.com/langgenius/dify 4/ MetaGPT — https://github.com/FoundationAgents/MetaGPT 5/ AutoGen — https://github.com/microsoft/autogen 6/ CrewAI — https://github.com/crewAIInc/crewAI 7/ LangGraph — https://github.com/langchain-ai/langgraph

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• Kernel Methods: Algorithms that transform data into higher dimensions to make it more separable. L • Latent Space: A representation of compressed data capturing underlying features. • Langchain: A framework for developing applications powered by language models. • LLM: Large Language Model, trained on vast text data to understand and generate human-like language. M • Mixture of Experts: A model architecture where different "experts" handle different parts of the input. • Multimodal AI: AI systems that process and integrate multiple types of data, like text and images. N • Neural Radiance Fields: A technique for generating 3D scenes from 2D images using neural networks. O • Objective Function: The function that models aim to optimize during training. • One-Shot Learning: Learning from a single example to make accurate predictions. Double Tap ❤️ For More

🤖 Generative AI Terms You Should Know A • Agents: Autonomous programs that perform tasks or make decisions on behalf of users. • Attention: A mechanism in neural networks that allows models to focus on relevant parts of the input sequence. • Autoencoders: Neural networks used for unsupervised learning, primarily for dimensionality reduction and feature learning. B • Back Propagation: An algorithm for training neural networks by propagating the error backward to update weights. • BigGAN: A type of Generative Adversarial Network (GAN) designed for high-resolution image generation. • Bias: Systematic errors in AI models due to prejudiced training data or flawed algorithms. C • Capsule Network: A neural network architecture that models hierarchical relationships, improving recognition tasks. • Conditional GAN: A GAN variant where both generator and discriminator receive additional information, enabling controlled generation. • Chain of Thought: A prompting technique that encourages models to reason step-by-step, enhancing problem-solving capabilities. D • DataSpeed: Refers to the rate at which data is processed or transmitted in AI systems. • Double Descent: A phenomenon where increasi

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