AI 3.0

1,977 0 0

A must-read in the field of Artificial Intelligence, it will take you through the mysteries of Artificial Intelligence and trigger your infinite imagination of future technology.

author
[U.S.] Melanie Mitchell.
original author's name
Artificial Intelligence: A Guide for Thinking Humans
publishers
Sichuan Science and Technology Press-Zhanlu
Issue date
2021-2
AI 3.0

Introduction - - - - - - - - - - - - - - - -

作者简介  · · · · · ·

Melanie Mitchell, Professor of Computer Science at Portland State University, has worked at the Santa Fe Institute and Los Alamos National Laboratory, with primary research interests in analogical reasoning, complex systems, Genetic Algorithms. While at the Santa Fe Institute, Michelle led research in the area of complex systems and taught related online courses. Her online course Introduction to Complexity has been taken by nearly 30,000 students and is one of the top 50 online courses on Coursera.

Catalog - - - - - - - - - - - - - - - - - - - - - -

The creation of machines with human intelligence is a major intellectual adventure.
Part I. If you want to bet on the future, it's important to understand why artificial intelligence still can't outperform human intelligence.
01 From its origins to its encounter with winter, mindfulness has been a bulwark that AI has been unable to overcome
02 From Neural Networks to Machine Learning, No One Is the Final Antidote
03 From the Turing test to the singularity debate, we can't predict where intelligence will lead us.
Part II Visual Identity: Always Easy to See, Hard to Do
04 Who, what, when, where, why
05 ConvNets and ImageNet, the cornerstones of modern artificial intelligence
06 Key gaps between human and machine learning
07 Ensuring Values Alignment to Build Trustworthy, Ethical AI
Part III Game and Reasoning: Developing Machines with Closer to Human-Level Learning and Reasoning Abilities
08 Reinforcing Learning, and Most Importantly, Learning to Reward the Robot
09 Learning to play games and where intelligence really comes from
10 Gaming is a means to an end, generalized AI is the goal
Part IV. Natural language: making the computer understand what it "reads"
11 Words, and the words that go with them
12 Machine translation, still not able to understand images and text in terms of human understanding
13 Virtual Assistant - Ask Me Anything!
Part 5 Common Sense - The Key to Breaking the Meaning Barrier with Artificial Intelligence
14 Artificial intelligence that is learning to "understand"
15 Knowledge, Abstraction, and Analogy to Give AI Core Common Sense
Conclusion Thinking about 6 key questions to unlock the ultimate potential of AI

Related Books

Toward the AGI Era: A Methodology for AI Product Managers

This course bridges the gap between understanding AI technology and gaining insights into user needs, model evaluation, and product design. It is ideal for product managers and cross-functional teams responsible for implementing AI solutions.

machine learning

Zhou Zhihua’s introductory textbook on machine learning—covering topics from model evaluation to classic algorithms—is ideal for learners who want to solidify their theoretical foundation and understand the logic behind model selection.

The Era of Collective Intelligence: How to Coexist with AI

Drawing on the perspectives of work, learning, and creativity, this book explains how to collaborate with AI, verify results, and maintain human judgment. It is ideal for readers who want to incorporate AI into their daily work without blindly relying on it.

Large-Scale Language Models: From Theory to Practice (2nd Edition)

This book integrates data, training, fine-tuning, reinforcement learning, agents, RAG, efficiency optimization, and evaluation of large language models within a Chinese-language framework, making it suitable for technically advanced readers with a background in programming.

No comments

none
No comments...