Summary of Kai-Fu Lee's AI Superpowers

Everest Media

Description

Please note: This is a companion version & not the original book.
Sample Book Insights:
#1 In May 2017, a Chinese teenager named Ke Jie was pitted against one of the world’s most intelligent machines, AlphaGo, in a battle to save humanity.
#2 When the Soviet Union launched the first human-made satellite into orbit in October 1957, it had an instant and profound effect on the American psyche and government policy. The event sparked widespread U. S. public anxiety about perceived Soviet technological superiority, which led to the creation of the National Aeronautics and Space Administration.
#3 In China, the government issued a plan to build artificial intelligence capabilities. It called for greater funding, policy support, and national coordination for AI development. By 2017, Chinese venture-capital investors had already responded to that call, pouring record sums into artificial intelligence startups.
#4 The Ke Jie versus AlphaGo match was played within the constraints of a Go board, but it is intimately tied up with dramatic changes in the real world. Those changes include the Chinese AI frenzy that AlphaGo’s matches sparked.

Sujets

• Industrie

Informations

• Publié par: Everest Media LLC
• Date de parution: 24 mars 2022
• Nombre de lectures: 0
• EAN13: 9781669363774
• Langue: English
• Poids de l'ouvrage: 1 Mo

Extrait

Insights on Kai-Fu Lee's AI Superpowers
Contents Insights from Chapter 1 Insights from Chapter 2 Insights from Chapter 3 Insights from Chapter 4 Insights from Chapter 5 Insights from Chapter 6 Insights from Chapter 7 Insights from Chapter 8 Insights from Chapter 9
Insights from Chapter 1

#1

In May 2017, a Chinese teenager named Ke Jie was pitted against one of the world’s most intelligent machines, AlphaGo, in a battle to save humanity.

#2

When the Soviet Union launched the first human-made satellite into orbit in October 1957, it had an instant and profound effect on the American psyche and government policy. The event sparked widespread U. S. public anxiety about perceived Soviet technological superiority, which led to the creation of the National Aeronautics and Space Administration.

#3

In China, the government issued a plan to build artificial intelligence capabilities. It called for greater funding, policy support, and national coordination for AI development. By 2017, Chinese venture-capital investors had already responded to that call, pouring record sums into artificial intelligence startups.

#4

The Ke Jie versus AlphaGo match was played within the constraints of a Go board, but it is intimately tied up with dramatic changes in the real world. Those changes include the Chinese AI frenzy that AlphaGo’s matches sparked.

#5

The threat to jobs is coming far faster than most experts anticipated, and it will not discriminate by the color of one’s collar, instead striking the highly trained and poorly educated alike.

#6

I believe that the skillful application of artificial intelligence will be China’s greatest opportunity to catch up with and possibly surpass America. But more important, this shift will create an opportunity for all people to rediscover what makes us human.

#7

Artificial intelligence has undergone a number of boom-and-bust cycles. The field was dominated by the rule-based approach, which attempted to teach computers to think by encoding a series of logical rules. However, this approach fell apart when the universe of possible choices or moves expanded.

#8

The neural networks camp, which mimics the brain’s underlying architecture, attempts to reconstruct the human brain itself. They feed millions of examples of a given phenomenon into the networks and let the networks figure out patterns.

#9

Deep learning, a technique that uses neural networks to train the network, was developed in the mid-2000s. It allowed neural networks to outperform older models at a variety of tasks. But years of ingrained prejudice against the neural networks approach led many AI researchers to overlook this fringe group.

#10

Deep learning is a form of narrow AI, which takes data from a specific domain and applies it to optimizing one specific outcome. It is most commonly used in fields like insurance and making loans, and it has been used to power self-driving cars.

#11

The United States has long been able to attract and absorb talent from around the world, which has led to many American universities and technology companies reaping the benefits of this talent. But China is now catching up, and will be the biggest beneficiary of the heat the AI fire is generating.

#12

The age of implementation is when deep learning’s incredible powers of pattern recognition and prediction are applied to different spheres, such as diagnosing a disease, issuing an insurance policy, driving a car, or translating a Chinese sentence into readable English.

#13

The second major transition is from the age of expertise to the age of data. Successful AI algorithms require three things: big data, computing power, and the work of strong but not necessarily elite AI algorithm engineers.

#14

China’s strengths in the four categories of fossil fuels, entrepreneurs, electrical engineers, and a supportive government allow the country to develop the underlying public infrastructure needed to harness the power of AI.

#15

Chinese entrepreneurs have access to an abundance of data, which will be invaluable in developing AI-driven services. This data outstrips what Silicon Valley’s leading companies can decipher from your searches, likes, or occasional online purchases.

#16

China’s government is working hard to tip the scales in its favor, and it has the resources to do so. The country’s lightning-fast development of a sprawling high-speed rail network serves as a living example.

#17

AI will cause significant job losses, and as it becomes more advanced, it will be able to replace around 40 to 50 percent of jobs in the United States within 15 years. The disruption to job markets will be large and coming soon.

#18

Inequality will not be contained within national borders. China and the United States have already jumped out to an enormous lead over all other countries in artificial intelligence, setting the stage for a new kind of bipolar world order.
Insights from Chapter 2

#1

Wang Xing, a Chinese entrepreneur, made a copy of the popular social network Facebook in 2003. He did this twice, in 2005 and 2007, and both times he was met with great success. However, some Chinese entrepreneurs felt that his copycat entrepreneurship went too far.

#2

By late 2017, Groupon's market cap had shriveled to $2. 58 billion, with its stock trading at under one-fifth the price of its 2011 initial public offering. The former darling of the American startup world had been stagnant for years and slow to react when the group-buying craze faded.

#3

The internet has allowed companies to be copied incredibly quickly, which has forced companies to innovate and create new products. This cutthroat environment has created the most tenacious entrepreneurs on earth.

#4

Startups and the entrepreneurs who found them are not born in a vacuum. Their business models, products, and core values are an expression of the unique cultural time and place in which they come of age.