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Artificial General Intelligence: (The MIT Press Essential Knowledge series)

1 การให้คะแนน

5

ระยะเวลา
4H 24นาที
ภาษา
ภาษาอังกฤษ
Format
หมวดหมู่

นอนฟิกชั่น

Artificial intelligence surrounds us. More and more of the systems and services you interact with every day are based on AI technology. Most AI is narrowly specific; that is, it can only do a single thing, in a single context. For example, your spellchecker can't do mathematics, and the world's best chess-playing program can’t play Tetris. Human intelligence is different. We can solve a variety of tasks, including those we have not seen before. In Artificial General Intelligence, Julian Togelius explores technical approaches to developing more general artificial intelligence and asks what general AI would mean for human civilization.

Togelius starts by giving examples of narrow AI that have superhuman performance in some way. He then discusses what it would mean to have general intelligence, by looking at definitions from psychology, ethology, and computer science. Next, he explores the two main families of technical approaches to developing more general artificial intelligence: foundation models through self-supervised learning, and open-ended learning in virtual environments. The final chapters of the book investigate potential artificial general intelligence beyond the strictly technical aspects. The questions discussed here investigate whether such general AI would be conscious, whether it would pose a risk to humanity, and how it might alter society.

© 2024 Ascent Audio (หนังสือเสียง ): 9781663736260

วันที่วางจำหน่าย

หนังสือเสียง : 13 สิงหาคม 2567

คนอื่นก็สนุก...

  1. When Machines Learn: AI and the Transformation of Society Lars Meyer
  2. Hardware for LLM AI: A Comprehensive Guide to Hardware Infrastructure for Large Language Models AI Et Tu Code
  3. Hacking AI: Big and Complete Guide to Hacking, Security, AI and Big Data. Hans Weber
  4. OpenAI Developer's Handbook: Mastering Text, Images and Code Generation using OpenAI APIs for developing intelligent Apps Et Tu Code
  5. Artificial Intelligence: The Complete Beginner’s Guide to the Future of A.I. John Adamssen
  6. LLM Universe: Building LLMs, OpenAI & Llama 2: Building LLMs, OpenAI & Llama 2: A Comprehensive Guide to Large Language Model Development, OpenAI and Meta Llama 2 Et Tu Code
  7. Big Brain Revolution: Artificial Intelligence – Spy or Saviour? Dr Michelle Tempest
  8. The AI Revolution: Preparing for Tomorrow's Workforce Arlo Voss
  9. ChatGPT Income Streams 2024: Discover 85+ AI Side Hustles to Boost Passive Earnings, Generate Cash Flow, and Stay Ahead in the Digital Age Jack Thompson
  10. AI and Robotics: The Revolution of Tomorrow: Exploring the Future of Technology and Automation Alex Johnson
  11. Machine learning - The Dark Side Of AI: the genie is out of the lamp - and he's not going back Devon Zander
  12. Docker Unveiled: The Comprehensive Handbook to Streamlined Development William Drake
  13. Mastering Complexity: A Comprehensive Guide to Big O Complexity and DSA Problem Solving DSA Shots
  14. Artificial Intelligence Fundamentals: A Journey through the Heart of Machine Intelligence Brandon Scott
  15. Computer Science: The Complete Guide to Principles and Informatics Jonathan Rigdon
  16. Machine Learning: Unlocking Patterns and Insights with Advanced Algorithms Victor Sage
  17. Reinforcement Learning: Machine Learning, Gamma, and Inventory Management David Feldspar
  18. Deep Learning: Guide for Machine Learning, Neural Networks, and Data Analytics David Feldspar
  19. Natural language Processing: Discover Potential of Natural Language Processing and Artificial Intelligence Daniel Garfield
  20. Information Theory for Beginners: Demystifying Information Theory. A Beginner's Guide James Ferry
  21. Machine Learning For Beginners: A Comprehensive, Step-by-Step Guide to Learning and Understanding Machine Learning Concepts, Technology and Principles for Beginners Peter Bradley
  22. Artificial Intelligence: What You Need to Know About Machine Learning, Robotics, Deep Learning, Recommender Systems, Internet of Things, Neural Networks, Reinforcement Learning, and Our Future Neil Wilkins
  23. Effective Machine Learning Teams: Best Practices for ML Practitioners David Colls
  24. Cloud-Native Architectures: Building Scalable, Resilient, and Agile Systems James Ferry
  25. Machine Learning in Python: Hands on Machine Learning with Python Tools, Concepts and Techniques Bob Mather
  26. Internet of Things for Beginners: A Comprehensive Guide to Understanding, Building, and Leveraging Connected Devices and Systems James Ferry
  27. Data Analysis for Beginners: The ABCs of Data Analysis. An Easy-to-Understand Guide for Beginners Brian Murray
  28. Data Science on AWS: Unleashing the Power of Cloud Computing for Innovative Data Insights Saimon Carrie
  29. Edge Computing: Revolutionizing Data Processing at the Fringe of Connectivity Steve Abrams
  30. Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs Mike Taylor
  31. Data Science and Analytics Essentials: The Revolution of Decision-Making: Leveraging Data in the Digital Age Daniel Richards
  32. Kubernetes Unleashed: Navigating the World of Automated Deployment and Scaling Rebecca Park
  33. Algorithms: Practical Guide to Learn Algorithms For Beginners Andy Vickler
  34. Kubernetes Demystified: Your Roadmap to Mastering Container Orchestration Bennett Drake
  35. Androids: The Team that Built the Android Operating System Chet Haase
  36. Data and Databases: Learn Data Analytics, Data Mining, and Operating Systems (2 in 1) Jonathan Rigdon
  37. Computer Science: Learn about Algorithms, Cybersecurity, Databases, Operating Systems, and Web Design Jonathan Rigdon
  38. Agile Project Management with Scrum: Advanced Strategies for Agile Project Management with Scrum Jacob Richardson
  39. Kubernetes Unlocked: Building and Managing Modern Cloud-Native Applications Marcus Brooks
  40. Tech Giants: The Companies Shaping the Future Craig Dames
  41. Blockchain Success Stories: Case Studies from the Leading Edge of Business John Hargrave
  42. Text Analytics: Practical Steps to Sort Data David Feldspar
  43. Extreme Programming for Beginners: Embracing Agility, Quality, and Collaboration in Software Development Daniel Green
  44. Grokking Algorithms: A Complete Beginner’s Guide for the Effective Learning of Algorithms Dylan Christian
  45. Kubernetes Essentials: Orchestrating Containers for Scalable Solutions Thaddeus Clarke
  46. Blockchain: The New Internet? How You Can Benefit from Blockchain Technology Beyond Bitcoin, Cryptocurrency, and Ethereum Phillip Rawson
  47. Serverless Data Engineering: Streamlining Big Data Workflows in the Cloud Chuck Sherman

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