Intro to Artificial General Intelligence (AGI): Future of AI

Intro to Artificial General Intelligence (AGI): Future of AI, available at $44.99, has an average rating of 4.6, with 38 lectures, based on 228 reviews, and has 807 subscribers.

You will learn about Understand the key components that make up an AGI system, such as knowledge representation, reasoning, learning, and goal-setting. Differentiate between narrow AI, artificial general intelligence (AGI), and artificial superintelligence (ASI), and identify examples of each. Analyze the major technical and ethical challenges involved in developing safe and beneficial AGI, such as value alignment, robustness, transparency, and contro Compare and contrast the main approaches being pursued to create AGI, including symbolic, connectionist, and hybrid methods. Identify the key enabling technologies accelerating AGI development, such as deep learning, reinforcement learning, meta-learning, and knowledge graphs. Assess the progress and contributions of major companies and institutions working on AGI, such as DeepMind, OpenAI, Google, MIT, and others. Examine recent breakthroughs and milestones in AGI research, like language models, multi-modal learning, and open-ended problem solving. Understand core principles of responsible AI development and identify key ethical issues raised by advanced AI systems. Recognize the vital role of AI governance frameworks and regulations for ensuring AGI is developed safely and equitably. Realistically evaluate expert forecasts and timelines for when we may achieve human-level AGI. Identify high-value skills and career paths that will be in demand in an AGI-transformed world. Anticipate and prepare for the profound economic, social and geopolitical impacts and risks of artificial general intelligence. This course is ideal for individuals who are AI researchers and graduate students seeking a comprehensive technical survey of AGI architectures, challenges, and frontiers. or Technology professionals who need to understand AGI's trajectory and implications to inform strategy and decision-making. or Learners with a solid foundation in computer science and AI who are comfortable engaging with complex technical concepts. or Individuals looking to apply AGI knowledge in contexts such as research, product development, policy, investment, or ethics. or Those who want to move beyond the hype to gain a realistic, evidence-based understanding of AGI from leading experts. or Learners seeking a balance of theoretical depth and real-world grounding, connecting AGI approaches to their societal impacts. or Students aiming to build AGI-relevant skills that will be valuable in the coming years, such as AI safety and robustness. or Anyone with a strong interest in the future of machine intelligence who wants a rigorous yet accessible overview of the AGI landscape. It is particularly useful for AI researchers and graduate students seeking a comprehensive technical survey of AGI architectures, challenges, and frontiers. or Technology professionals who need to understand AGI's trajectory and implications to inform strategy and decision-making. or Learners with a solid foundation in computer science and AI who are comfortable engaging with complex technical concepts. or Individuals looking to apply AGI knowledge in contexts such as research, product development, policy, investment, or ethics. or Those who want to move beyond the hype to gain a realistic, evidence-based understanding of AGI from leading experts. or Learners seeking a balance of theoretical depth and real-world grounding, connecting AGI approaches to their societal impacts. or Students aiming to build AGI-relevant skills that will be valuable in the coming years, such as AI safety and robustness. or Anyone with a strong interest in the future of machine intelligence who wants a rigorous yet accessible overview of the AGI landscape.

Enroll now: Intro to Artificial General Intelligence (AGI): Future of AI

Summary

Title: Intro to Artificial General Intelligence (AGI): Future of AI

Price: $44.99

Average Rating: 4.6

Number of Lectures: 38

Number of Published Lectures: 38

Number of Curriculum Items: 38

Number of Published Curriculum Objects: 38

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Understand the key components that make up an AGI system, such as knowledge representation, reasoning, learning, and goal-setting.
Differentiate between narrow AI, artificial general intelligence (AGI), and artificial superintelligence (ASI), and identify examples of each.
Analyze the major technical and ethical challenges involved in developing safe and beneficial AGI, such as value alignment, robustness, transparency, and contro
Compare and contrast the main approaches being pursued to create AGI, including symbolic, connectionist, and hybrid methods.
Identify the key enabling technologies accelerating AGI development, such as deep learning, reinforcement learning, meta-learning, and knowledge graphs.
Assess the progress and contributions of major companies and institutions working on AGI, such as DeepMind, OpenAI, Google, MIT, and others.
Examine recent breakthroughs and milestones in AGI research, like language models, multi-modal learning, and open-ended problem solving.
Understand core principles of responsible AI development and identify key ethical issues raised by advanced AI systems.
Recognize the vital role of AI governance frameworks and regulations for ensuring AGI is developed safely and equitably.
Realistically evaluate expert forecasts and timelines for when we may achieve human-level AGI.
Identify high-value skills and career paths that will be in demand in an AGI-transformed world.
Anticipate and prepare for the profound economic, social and geopolitical impacts and risks of artificial general intelligence.

Who Should Attend

AI researchers and graduate students seeking a comprehensive technical survey of AGI architectures, challenges, and frontiers.
Technology professionals who need to understand AGI's trajectory and implications to inform strategy and decision-making.
Learners with a solid foundation in computer science and AI who are comfortable engaging with complex technical concepts.
Individuals looking to apply AGI knowledge in contexts such as research, product development, policy, investment, or ethics.
Those who want to move beyond the hype to gain a realistic, evidence-based understanding of AGI from leading experts.
Learners seeking a balance of theoretical depth and real-world grounding, connecting AGI approaches to their societal impacts.
Students aiming to build AGI-relevant skills that will be valuable in the coming years, such as AI safety and robustness.
Anyone with a strong interest in the future of machine intelligence who wants a rigorous yet accessible overview of the AGI landscape.

Target Audiences

AI researchers and graduate students seeking a comprehensive technical survey of AGI architectures, challenges, and frontiers.
Technology professionals who need to understand AGI's trajectory and implications to inform strategy and decision-making.
Learners with a solid foundation in computer science and AI who are comfortable engaging with complex technical concepts.
Individuals looking to apply AGI knowledge in contexts such as research, product development, policy, investment, or ethics.
Those who want to move beyond the hype to gain a realistic, evidence-based understanding of AGI from leading experts.
Learners seeking a balance of theoretical depth and real-world grounding, connecting AGI approaches to their societal impacts.
Students aiming to build AGI-relevant skills that will be valuable in the coming years, such as AI safety and robustness.
Anyone with a strong interest in the future of machine intelligence who wants a rigorous yet accessible overview of the AGI landscape.

Unlock the secrets of Artificial General Intelligence (AGI) and explore the cutting-edge technologies shaping our future in this comprehensive course. Whether you’re an AI researcher, technology professional, or simply passionate about the future of machine intelligence, this in-depth program will equip you with the knowledge and skills to navigate the complex landscape of AGI.

Dive into the fundamentals of AGI, from its core components and levels to the key challenges researchers face in developing thinking machines. You’ll survey the major approaches driving AGI breakthroughs, including deep learning, reinforcement learning, and neuro-symbolic AI, and discover the companies at the forefront of this transformative field, like DeepMind, OpenAI, and Google.

But AGI is about more than just the technology – it also raises profound ethical questions and societal implications. That’s why this course places a strong emphasis on responsible AI development, exploring crucial topics like value alignment, transparency, and robustness. You’ll grapple with the key ethical issues surrounding AGI and understand the vital role of governance frameworks in ensuring this technology benefits humanity.

Throughout the course, you’ll learn from leading experts who will provide an evidence-based perspective on the current state and future trajectory of AGI. You’ll come away with a realistic understanding of how close we are to achieving human-level AI and the transformative impact it could have on our economy and society.

Whether you’re looking to advance your research, inform your business strategy, or simply satisfy your intellectual curiosity, this course will give you a solid foundation in the key concepts, technologies, and debates shaping the quest for artificial general intelligence. By the end, you’ll have the knowledge and skills to critically engage with one of the most important technological developments of our time.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Outline

Chapter 2: Basics of AGI – What is AGI, History, Evolution

Lecture 1: What is AGI?

Lecture 2: Evolution of AGI

Lecture 3: Components of AGI

Lecture 4: Approaches to build AGI

Chapter 3: Basics of AI

Lecture 1: Basics of AI

Lecture 2: What is AI?

Lecture 3: Machine Learning

Lecture 4: Unsupervised Learning

Lecture 5: Reinforcement Learning

Lecture 6: Supervised Learning

Lecture 7: Deep Learning

Lecture 8: Natural Language Processing (NLP)

Lecture 9: Computer Vision (CV)

Lecture 10: Expert Systems

Lecture 11: Neural Networks

Lecture 12: Robotics

Lecture 13: Generative AI

Lecture 14: Generative Adversial Networks (GANs)

Lecture 15: Variational Autoencoders (VAEs)

Lecture 16: Recurrent Neural Networks (RNNs)

Lecture 17: Transformers

Lecture 18: Types of AI – 1

Lecture 19: Types of AI – 2

Chapter 4: Levels of AGI

Lecture 1: Levels of AGI – 1

Lecture 2: Levels of AGI – 2

Lecture 3: Levels of AGI – 3

Chapter 5: Companies & Project spearheading AGI Development

Lecture 1: Companies working on AGI

Lecture 2: Promising AGI Projects

Chapter 6: Ethics & Regulations with AGI

Lecture 1: Responsible & Transparent Development

Lecture 2: AI Ethics & Frameworks

Lecture 3: Gov Policies & EU Framework

Chapter 7: AGI Predictions

Lecture 1: When will we realistically see AGI?

Lecture 2: What skills will matter Post-AGI?

Lecture 3: Post-AGI World Order: Job displacements, and more

Lecture 4: Post-AGI Economics: UBI, AI Tax and more

Chapter 8: Resource

Lecture 1: Please find the entire PPT of this course attached

Instructors

Yash Thakker
a lifelong learner 🙂

Rating Distribution

1 stars: 1 votes
2 stars: 4 votes
3 stars: 16 votes
4 stars: 68 votes
5 stars: 139 votes

Frequently Asked Questions

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