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DLC518066: AGI Fundamentals for Business
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Lesson 1: The Context7 Topics
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Anchor Lecture: The Context (41 min video) - Core item
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Large Language Model (LLM) Explained (1 h Video) - Core item
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The Art of AI Maturity | Accenture (20 min read) - Core item
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The Age of AI has begun - Bill Gates (15 min read)
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Artificial Intelligent (AI) Impact and Our Responsibility (10 min read)
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Dr. Aya Soffer – AGI – Are We There Yet? (60 min video)
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AI Glossary (Dig in as much as you want)
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Anchor Lecture: The Context (41 min video) - Core item
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Lesson 2: AGI Tools6 Topics
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Anchor Lecture: AGI Tools (16 min video) - Core item
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Anchor Lecture: Q1 2024 - Developments (78 min video) - Core item
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There's An AI For That (♾️Dig in as much as you want)
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Advanced Midjourney V6 Guide (30 Min. Video)
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Generative AI Library, Prompts and Tools (♾️Dig in as much as you want)
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Hugging Face – The AI Community Building the Future (5 min video)
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Anchor Lecture: AGI Tools (16 min video) - Core item
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Lesson 3: Tips That Teach Us6 Topics
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Anchor Lecture: Tips That Teach Us 1 (25 min video) - Core Item
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Anchor lecture: Q2 2023 Developments - Tips That Teach Us 2 (86 min video) - Core Item
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How to Win in Generative Tech Right Now with James Currier (13 min video) - Core item
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How ChatGPT Works Technically For Beginners (33 min video)
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Learn Prompting (3 hours read)
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100 (Free) AI Courses To Help You Navigate the Future of Work (♾️Dig in as much as you want)
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Anchor Lecture: Tips That Teach Us 1 (25 min video) - Core Item
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Lesson 4: AI in The Organization - Potential and Case Studies7 Topics
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Andrew Ng: Opportunities in AI (37 min. Video) - Core item
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Work Shift: How to Create the AI-Powered Office of the Future (15 min. read) - Core item
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The Vertical AI Boom - Core Item (10 min read)
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Walmart Is Breaking Retail Boundaries - Core item (5 min read)
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Oracle AI Strategy (10 min. read)
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McKinsey - The Race to Deploy AI (30 min read)
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Inside Accenture’s AI Journey With CEO Julie Sweet (25 min. listen)
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Andrew Ng: Opportunities in AI (37 min. Video) - Core item
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Lesson 5: Diving Deeper7 Topics
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How Far is Too Far? | The Age of A.I (34 min video)
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Yuval Noah Harari – AI & the Future of Humanity (40 min video)
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The Impact of ChatGPT on Physics and Vice Versa – Stephen Wolfram (58 min video)
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Objective-Driven AI – Yann LeCun’s Vision for Cognitive Systems (1.15 hrs video)
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Children’s Common Sense and Learning AI Systems (9 min video)
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Mindfulness, AI and the Future of Life With Sam Altman (1 hour video)
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What Is ChatGPT Doing - Stephen Wolfram (3 hours video)
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How Far is Too Far? | The Age of A.I (34 min video)
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Lesson 6: Updates6 Topics
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NIST AI Risk Management Framework (1 hour read)
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OpenAI DevDay Nov-2023: Opening Keynote with Sam Altman on ChatGPT-4 (45 min. Video)
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How AI Was Stolen (3 hours video)
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Why Are Migrants Becoming AI Test Subjects (50 min listen) - Core item
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Insect-Inspired AI: “Natural Intelligence” Shapes the Third Wave
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Making Friends with Machine Learning: The Entire Course - Cassie Kozyrkov (♾️Dig in as much as you want)
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NIST AI Risk Management Framework (1 hour read)
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Setting a Test and Receiving a Certificate3 Topics|1 Quiz
Lesson 1,
Topic 7
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AI Glossary (Dig in as much as you want)
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An AI glossary by Andreessen Horowitz (AKA a16z), serves as a reference guide for understanding the terminology, concepts, and jargon used in AI research, development, and applications. This is a collection of terms and definitions related to the field of artificial intelligence (AI). It includes a wide range of terms that cover various subfields and aspects of Artificial Intelligence, such as machine learning, natural language processing, computational resources, technological terms, and cultural related definitions such as biases and regulation.
For example:
- Agents – Software that can perform certain tasks independently and proactively without the need for human intervention
- AGI (Artificial General Intelligence) – Microsoft researchers have defined AGI as artificial intelligence that is as capable as a human at any intellectual task.
- Bias – Assumptions made by an AI model about the data
- Chain of Thought -A term used to describe the sequence of reasoning steps an AI model uses to arrive at a decision.
- End-to-End Learning – A type of machine learning model that does not require hand-engineered features
- Explainable AI (XAI) – A subfield of AI focused on creating transparent models that provide clear and understandable explanations of their decisions.
- And many more.