Introduction - - - - - - - - - - - - - - - -
artificial intelligence (AI)It is now profoundly affecting our production and life, and even the future destiny of mankind, but what exactly is artificial intelligence? What is the principle behind artificial intelligence? What kind of historical changes has AI gone through from its inception to its evolution so far? Where are the boundaries of AI capabilities today? What is the difference between AI and human intelligence? What challenges and opportunities will AI face in the future? This book will reveal the answers to all these questions.
This book is the result of 10 years of thinking by Melanie Michel, author of the mega-bestseller Complexity and a cutting-edge scientist in complex systems, to clarify artificial intelligence and human intelligence. Drawing from Michelle's years of documenting the real state of development in the field of AI, the book reveals in five parts "what AIs can do now, and what we can expect from them in the coming decades". After describing the development history of AI, the author clarifies the relationship between AI and human intelligence by exploring the development status and limitations of popular applications in 4 major AI fields: visual recognition, games and reasoning, natural language processing, and common sense judgment, and the case studies in the book on face recognition, unmanned driving, and machine translation are full of great revelations! And these are all the dilemmas facing the development of artificial intelligence at the moment, and what must be rethought if artificial intelligence wants to make breakthrough progress. Read this book, you will have a panoramic perception of the field of artificial intelligence.
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
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
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