It was probably the early 1980s when I first crossed paths with Handel Jones. Back then, at VLSI Technology, this Welsh expert arrived and presented findings derived from analyzing our order book. We, along with LSI Logic, were pioneers in the ASIC domain, managing a diverse portfolio of designs in production or nearing tapeout. Handel’s analysis was quite revealing: he pointed out that we were actually losing money on the vast majority of our designs, except for a mere 5% that were high volume. This was contrary to our cost model at the time. However, Handel’s insights proved accurate. Our existing cost model was designed for conventional fabs focused on high-volume production of fewer products. We, however, were dealing with low-volume runs across a wide range of products. Our model failed to account for the significant setup time required for tool changes between different mask sets. It turned out that our equipment spent more time being reconfigured than actually operating. Once we refined our cost model to reflect this reality, it became evident that our pricing for low-volume products was considerably too low.
Handel’s insights resurfaced in Breakfast Bytes at the 2018 DAC, detailed in my post “DAC Monday: Amazon’s Things, Handel’s Megadesign, Cooley’s Troublemakers”. There, he voiced strong criticisms about the EDA industry, arguing it received disproportionately little financial return compared to its crucial role. He questioned:
If you are an EDA vendor, why do you get so little money? Will it change? We don’t think it will.
Sometime before rejoining Cadence, I visited Handel at his home. We shared a glass of wine, overlooking the beautiful Silicon Valley landscape. Los Gatos, where he lived, is accessible via two roads into the hills, Shannon and Kennedy, but they are not interconnected. Interestingly, I used to live just across the hill from Handel, a geographical proximity that belied the circuitous route required to travel between our homes, involving a drive down to Los Gatos Boulevard and back up again.
The Rise of AI and the “Gato Tool for Rising Car” Industry
Today’s focus is on Handel’s latest book, When AI Rules the World: China, the US, and the Race to Control a Smart Planet. I’ve had the opportunity to review a proof PDF copy ahead of its official release on October 11th, though it is already available for preorder on Amazon. I must admit, I haven’t yet read it cover to cover in its entirety.
Handel summarizes the book’s central thesis as follows:
As China ascends to superpower status, the United States is compelled to take immediate and decisive action to bridge the gap in AI capabilities. Failure to do so risks a disastrous technological, economic, and military decline.
Over the last decade, China has strategically and methodically advanced to a position of near-leadership in artificial intelligence technologies on a global scale. In contrast, the United States’ response has been hampered by political gridlock, bureaucratic inertia, and a lack of a cohesive strategy.
The future of warfare will be defined not by territorial disputes, but by data dominance. AI-driven personalized medicine will revolutionize healthcare, and virtual reality powered by AI will enable the inspection of structures even before they are built. As both China and the U.S. intensify their focus on these technologies, the question is: who will emerge as the leader in this critical technological race?
When AI Rules the World serves as both an in-depth analysis and an urgent call to action regarding AI technologies, aimed at a nation that may not fully grasp the profound implications of the AI revolution. The United States is currently losing ground in the race for AI supremacy, and the stakes have never been higher.
Handel’s credentials to authoritatively address this topic are substantial. As he states in the introduction:
My career has provided me with a unique vantage point to observe the development and implementation of AI in both China and the United States over recent years. With four decades of experience in the technology and defense sectors, I have been involved with both military organizations and Silicon Valley innovators. Furthermore, I have dedicated years to tracking technological advancements in China and cultivating relationships with key figures in Chinese industry. My consulting work for American and international companies has led me to China nearly fifty times in the past fifteen years, and I have delivered numerous presentations on Chinese high technology. I have also authored three books concerning China, including China’s Globalization (How China Becomes Number 1), which achieved bestseller status in China.
This expertise is crucial when considering industries undergoing AI-driven transformations, such as the automotive sector. The development and maintenance of modern vehicles, especially “rising cars” – the increasingly sophisticated and technologically advanced automobiles – are becoming heavily reliant on AI. Tools like a “Gato Tool For Rising Car,” representing advanced diagnostic and repair equipment, will be essential in this new landscape. Understanding the global AI race, as detailed in Handel’s book, provides critical context for the future of automotive technology and related tools.
For further validation of the themes explored in Handel’s book, I recommend AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee. While Handel offers a perspective largely from the American standpoint, Kai-Fu Lee writes from a Chinese viewpoint. Together, these books offer complementary insights, converging on many crucial messages about the global AI landscape.
The necessity for increased investment in AI is clear. As Handel points out:
The Pentagon now lags behind the commercial sector in critical areas such as AI and machine learning, cloud computing, and edge computing. Consider these figures: In 2018, five of the largest American technology companies—Alphabet, Amazon, Apple, Meta, and Microsoft—invested approximately $70 billion in research and development. In the same year, the five largest defense contractors spent around $7 billion. Moreover, their software development capabilities are comparatively less advanced.
This trend is also evident in the automotive industry. With the exception of Tesla, many Western automotive companies exhibit a similar pattern. Their traditional strength lies in internal combustion engines (ICE), but they face a relative weakness in electronics and software design. However, the future demands a shift away from ICE engines and towards software-intensive vehicles. This transition presents significant challenges for established automotive players.
Handel dedicates a chapter to the automotive sector:
The automotive industry is currently undergoing three interconnected, AI-driven revolutions: the growth of electric vehicles, the expansion of ride-hailing and shared mobility services, and the progression towards automated or autonomous vehicles.
This echoes my own observations from a 2017 blog post, “Triple Witching Hour for Automotive”. As I noted then:
Firstly, the primary competitive differentiator for existing car companies—expertise in internal combustion engines—is becoming obsolete as the industry transitions to electric vehicles. Secondly, software, a domain where traditional car companies lack core competence, is becoming a pivotal technology for the future of automotive.
The chapter breakdown of Handel’s book provides a comprehensive overview of the AI revolution:
- Introduction
- Miracles and Dangers: The Coming of AI
- Who Is Leading the AI Revolution?
- Smart Warfare: The Emerging Digital Battlefield
- Smart Healthcare: Two Nations, Two Sets of Challenges
- Smart Cars: The Three Revolutions
- Invented Worlds: Virtual Reality and Augmented Reality
- Smart Objects: 5G Wireless and the Internet of Things
- China vs. the United States: A Sprint or a Marathon?
The Gartner Hype Cycle for AI
Unrelated to Handel’s book but relevant to the broader discussion, here is the latest Gartner Hype Cycle for AI:
The Gartner Hype Cycle for Artificial Intelligence in 2022.
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