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Generative-AI-and-Agentic-AI-Development-The-Next-Frontier

A Generative AI course teaches you how to build and apply AI models that can create text, images, code, and more using technologies like large language models and diffusion models. Youu2019ll gain hands-on experience with tools such as GPT, prompt engineering, and real-world AI applications across industries.

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Generative-AI-and-Agentic-AI-Development-The-Next-Frontier

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  1. Generative AI & Agentic AI Development: The Next Frontier Exploring the technologies reshaping creation, automation, and human-AI collaboration

  2. FOUNDATIONS What is Generative AI? Creating the Future AI systems that generate new content across multiple formats: • Text, images, code, audio, and video • Powered by GPT, diffusion models, and LLMs • ChatGPT hit 1M users in 5 days—faster than Instagram

  3. TECHNOLOGY DEEP DIVE Core Technologies Behind Generative AI Large Language Models Diffusion Models Autoencoders & Flow Models Generate images by progressively denoising random noise (e.g., Stable Diffusion) Predict next words to generate coherent, contextual text at scale Encode and decode data with latent noise for sophisticated generation

  4. Agentic AI: Beyond Generation to Autonomous Action Autonomous Goal Achievement Agentic AI systems act independently to achieve objectives, not just generate content Planning & Reasoning AI agents that plan, reason, and interact in complex environments like games and research automation Simulating Complexity Recent research shows LLMs can simulate social dynamics and automate scientific experiments

  5. GROWTH Dramatic Growth & Investment in Generative AI Investment Surge AI-related job postings quadrupled from 2022 to 2023 Generative AI startups raised 600% more capital in 2022 than in 2020 Microsoft, Google, Meta investing billions in AI platforms and copilot tools

  6. IMPACT Real-World Applications Transforming Industries Code Generation Creative Arts Business Productivity GitHub Copilot assists over 1 million developers by generating functional code in real-time Midjourney and DALL·E create stunning visuals from simple text prompts AI copilots in Microsoft Azure and Google Workspace enhance workflows and efficiency

  7. Challenges & Ethical Considerations 1 Computational Demands AI models require massive GPU resources and significant energy consumption 2 Bias & Misinformation Models can perpetuate harmful stereotypes or generate false, misleading content 3 Responsible AI Emphasis on transparency, fairness, and human oversight in deployment practices

  8. FUTURE VISION The Future: Toward General Purpose, Aligned AI Agents Generative Capabilities Creative content and reasoning Key Developments • Model alignment ensuring AI acts according to human values and preferences • Accelerating scientific discovery through autonomous research • Automating complex tasks while augmenting human creativity • Building trustworthy AI that benefits society Versatile AI Assistants Goal-Directed Autonomy Alignment & Safety Behaves per human values Plans and acts toward objectives Combining creation with autonomous action for unprecedented capabilities

  9. Visualizing the AI Agentic Evolution The journey from content generation to autonomous decision-making and complex interaction Early Generative Models Large Language Models Agentic AI Systems

  10. Conclusion: Embracing the AI Revolution Responsibly The Opportunity The Responsibility Harness AI's power to unlock innovations and efficiencies across all domains Develop and deploy AI ethically to benefit all humanity Building Together Let's shape the future of AI collaboratively and thoughtfully Generative and agentic AI are reshaping how we create, work, and solve problems—join the revolution.

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