★ Topics: In a structured order; from the most important to less critical topics!
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GANs: DCGAN, StyleGAN, BigGAN.
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Diffusion Models: DDPMs, Stable Diffusion.
2.1. Applications: Image Synthesis, Video Generation, Audio Generation.
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Transformers: GPT, DALL-E, T5.
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Text-to-Image Models: MidJourney, OpenAI's DALL-E.
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VAEs: Applications in Image Generation & Compression.
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Fine-Tuning & Custom Training: Domain-specific adaptations of pre-trained models.
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Audio & Music Generation: WaveNet, Jukebox, Riffusion.
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3D & Video Generation: NeRF for 3D Modeling, GAN-based Video generation & editing Tools.
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Ethics in Generative AI: Biases, Copyright, Safety Concerns.
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Applications of Generative AI: Gaming, Content Creation, Drug Discovery, Digital Twins for Simulations.
★ Math for Gen AI
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Linear Algebra: Matrices, Vectors, Eigenvalues, Eigenvectors.
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Optimization: Gradient Descent, Convex Optimization, Backpropagation.
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Probability & Statistics: Probability Distributions, Bayesian Inference, Hypothesis Testing.
Agentic AI mainly operates based on Four Foundational Pillars: Memory, Planning, Decision-Making and Autonomous Execution.
★ How to Get Started with Agentic AI?
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Reinforcement Learning (RL)
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Large Language Models (LLMs): Start with Hugging Face and OpenAI documentation.
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Autonomous Systems & Multi-Agent AI: Start with the book "Multi-Agent Systems" and explore open-source Autonomous AI projects.
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Memory & Planning Systems: Start with open-source projects like LangChain and AutoGPT.
Most Important and Practical Aspects:
- Core Algorithms in Agentic AI
• RL: DQN, Policy Gradient Methods (PPO, A3C), Actor-Critic Models.
• MAS: Collaboration and Competition between agents.
- Applications of Agentic AI
• Autonomous Vehicles: Self-driving cars and drones (Tesla, Waymo).
• Robotics: Robots for industrial automation (e.g., Boston Dynamics).
• Gaming AI: Adaptive NPC behavior (e.g., AlphaGo, AlphaStar).
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Planning & Decision Making: MDPs, MCTS.
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Human-Agent Interaction: Natural Language Communication (Alexa, Siri), Emotional Intelligence (but still emerging).
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Ethical Concerns: Safety in autonomous systems, Bias in AI decision-making.
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Tools to Start With
• OpenAI Gym: RL simulation.
• Unity ML-Agents: Game-based AI training.
• PyBullet: Robotics simulation.
★ Math for Agentic AI
• Linear Algebra: For state representation (matrices, vectors).
• Probability: For Markov processes and decision-making.
• Optimization: Gradient descent and policy optimization.