The dynamics of “watchwords” in the sweeping narratives of nation-states are peculiar and complex. “Democracy” and “equality” have a certain valence to Americans that’s unique, even to other democratic and equal places. This is to be expected after all: each community spins its own story, and thus the same political phrases can have radically different interpretations depending on who receives them.
I was thinking about this dynamic while reading two books this past week, one on developments in Russian military science and the other on Chinese leftism. The two works are mostly orthogonal to one another, but one nexus that linked the two together was an obsession about “color revolutions.” Once a core doctrine of democracy promotion, it’s a term that has subsided in the West, but was commonly used to describe popular revolts against authoritarian regimes in places like Georgia (Rose), Ukraine (Orange), Kyrgyzstan (Tulip) and the broader Arab Spring in 2011.
Yet, the specter of the color revolution has never quite left the minds of authoritarian leaders, and both Russia and China have made reducing their incidence core to their executive programs.
Oscar Jonsson, in The Russian Understanding of War, writes on the developments in Russian military theory in the post-Soviet era. With the likelihood of nuclear war reduced, the country’s theorists struggled to evolve their doctrines to encompass the increasingly complex security environment that arrived in the 1990s, namely around information systems. Russian military theories were deeply imprinted with Clausewitz’ definition of war as the use of armed force in the pursuit of politics, which worked well throughout the Cold War. In this new era however, it left open key questions. What happens though when a country like the United States uses financial sanctions to harm a nation? Or Europe subsidizes a civil society organization or media outfit exposing corruption at the highest echelons of government?
For the past two decades, Russia’s top military strategists have struggled with what to do with these activities. If such negative actions were to be considered “war,” then international rules on conflict would have to be entirely rewritten — and wars would be declared constantly, essentially making such declarations useless. Yet, it was clear that wars going forward wouldn’t involve nuclear weapons, and that such remote and contact-less tactics were going to be the new norm.
The rise of color revolutions on Russia’s periphery in the early 2000s jolted the country and its leaders. The result was an expansion of its definition of war to encompass far more than armed conflict, shredding the legacy of Clausewitz. While noting that it is hard to be definitive, Jonsson argues that the Russians finally came to the conclusion that “Information-psychological warfare is so effective that it should be considered violent, that it blurs the boundaries of war and peace, and that Russia considers itself to be engaged in large-scale information war. Furthermore, it is seen as a key enabler for the creation of color revolutions, the major threat from the West in the Russian view.”
Russia’s war strategy vividly expanded. Instead of just personnel and materiel, it grew to encompass countering foreign interference in domestic affairs, creating financial sovereignty, and developing independent national myths and narratives to counter Western views of the country.
This evolution was driven by strategists like General Makhmut Gareyev, the former president of the Russian Academy of Military Science. From Jonsson:
In January 2012, Gareyev wrote that there were two main ways to achieve policy objectives in the modern world. The first was ‘information, cyber, electronic, psychological, and other subversive activities, the creation of controlled chaos [the Russian term for color revolutions] to provoke in the opposing countries various kinds of unrest, overthrowing the unwanted power structures within and disturbing the internal stability of the state’ … The second way was through using armed force to unleash local conflicts…
For Russia, the focus on the power of information was realized during the first Gulf War, when the country saw that a relatively small international coalition of troops against Saddam Hussein used superior intelligence to achieve victory. In addition, the development of channels like CNN which covered the war live brought huge propaganda value to the U.S. As Jonsson writes, “The Gulf War was a wakeup call for the Russian military in terms of how vulnerable Soviet-era equipment could be against new equipment, concepts, and doctrine aided by information technology.”
The Pentagon’s chief planners seem headed in much the same direction today, albeit significantly later than their Russian counterparts. Given America’s overwhelmingly superior arsenal, there was sensitivity and concern about the diminishment of power projection compared to the Russians, and thus, a slower response to the changing nature of warfare characterizing the 21st century.
With Russia focused on preventing color revolutions across all layers of security and government, we see the apotheosis of Putin’s political goals. Despite a raging war in the Ukraine, laws banning the discussion of it have all but squelched dissent by citizens.
Simultaneous with the development of these theories in Russia, China was rebuilding its own political system to protect against the further encroachment of Western-style capitalism and liberalism on the mainland. In China’s New Red Guards, Jude D. Blanchette charts the intellectual journeys of China’s leftists, how they lose power in the 1980s and 1990s with the reform and opening period under Deng Xiaoping and Jiang Zemin, only to regain more substantive influence in the Xi Jinping era.
The Communist Party of China watched global popular revolutions and became deeply worried about color revolutions, and the left’s insistence on embracing China’s full history offered a potential narrative and antidote. As Blanchette writes about one leftist activist, “What the country needed, and now had, was a third group—a ‘new left’—that would oppose Deng-style economic reforms and embrace the Maoist legacy—all of it—including (indeed especially) the Cultural Revolution and its great innovations in ‘mass democracy.’ And this was relevant today, [he] concluded, because China was threatened by a wave of ‘color revolutions’ incited and supported by the United States.”
For much of the past decade under Xi, China has buttressed its founding myths, expanded the number of patriotic heroes in the country’s arc (and penalized besmirching them with lengthy jail sentences), and increasingly strengthened the Great Firewall to protect its prime place as chief censor for all media. Now, the government is focused on minimizing the valorization of capitalism, wealth and fame across media, with the long-range objective of reducing the appearance of inequality and reducing the risk of fomenting a color revolution.
We thus have two countries developing parallel strategies around this shared concern around the watchword of color revolutions, all while the U.S. and Western media have somewhat shrugged off the term. Russia’s approach may be more focused on military strategy and China’s on domestic “rectification,” but the planning and its purposes are the same.
The divergence is a matter of interpretation. For the West, color revolutions are a spark that bring an outpouring of popular power, creating political transparency for opinions that were once secretly expressed. Yet, for Russia and China, the meaning is inherent to the Russian translation of the term, which is “controlled chaos.” Color revolutions are moments of pure emotion, where a citizenry lose their rationality and destroy order and stability for next to no gains. It’s about anesthetizing that seething spasm, and ensuring that people come to their senses.
China and Russia have organized deep responses to this phenomenon, and yet, the originator of the concept has done little to double down. The United States is adrift on democracy and rights promotion following Iraq and Afghanistan, and while reflection on the disasters of those conflicts is warranted, going mute on democracy promotion is the wrong course of action.
The specter of color revolutions galvanized regimes worldwide to clamp down and close avenues for any impulse for change. That’s not surprising: in black-and-white, totalizing, Manichean systems, there’s no room for color. That doesn’t mean that America can’t retake the mantle of leadership though, and build its own doctrines. What’s the watchword of the United States today? The fact that I can’t really tell you is everything you need to know.
Then this morning, we had Sebastian Mallaby, senior fellow at the Council on Foreign Relations and the writer of The Power Law: Venture Capital and the Making of the New Future, talking with Josh Wolfe and I about the differences between VC and hedge funds, which was the subject of Mallaby’s earlier book More Money Than God. We also discussed the histories of VC firms, the rise of solo capitalists, why succession planning remains so hard, and what allows some investors to find enduring alpha in the industry. (Listen on Anchor, which has links to Apple Podcasts and Spotify as well)
A few notes on previous “Securities” issues
In “Fission today, fusion tomorrow,” I wrote about rapid optimistic developments in both nuclear fission and fusion. This week, we saw another news story, this time from Oxford University startup spinout First Light Fusion, which reached a new milestone for its projectile-focused fusion reactor. Fusion is still very far off, and scientists and engineers are still debating the particular reactor design that might work best. Still, it's another sign that scientist and investor interest remains keen on what has been a backwater field for decades.
I deplore the number of gambling outlets in “America’s gambling fetish," and one story that intrigued me at the end of the Saint Peter’s run in the NCAA March Madness tournament is how close sportsbooks came to a colossal loss just as the industry has massively expanded.
The first round of the French presidential election is tomorrow, and the next two weeks are likely to be an extraordinary time in one of Europe’s most important counties. As I wrote in “Consensus functions,” “What happens though when the information has been analyzed, the results are in, and yet consensus remains elusive? This has been the crisis of American politics.” It now looks like it's going to be the crisis of French politics, too.
Lux Recommends
Adam Kalish recommends this article in NBC News about the evolutionary pathways of dogs, and how a group of scientists are exploring whether dogs evolved to make themselves essentially cuter to humans while diverging from wolves. The new research builds up on previous work published in the Proceedings of the National Academies of Science that showed the facial muscle anatomy of dogs evolved to express a wider range of messages to their human owners.
Hypersonic weapons are the hot topic in DC today, and it’s important to follow developments. The latest is that the Biden administration has announced that it is going to work jointly with the UK and Australia to develop these technologies further.
Shaq Vayda sent this last week, but I unfortunately lost it in my inbox. We lost a legendary scientist with the passing of Arthur D. Riggs, who invented the technology for creating synthetic insulin. It was a development that transformed the lives of diabetes patients.
That’s it, folks. Have questions, comments, or ideas? This newsletter is sent from my email, so you can just click reply.
Forcing China’s AI researchers to strive for chip efficiency will ultimately shave America’s lead
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Right now, pathbreaking AI foundation models follow an inverse Moore’s law (sometimes quipped “Eroom’s Law”). Each new generation is becoming more and more expensive to train as researchers exponentially increase the number of parameters used and overall model complexity. Sam Altman of OpenAI said that the cost of training GPT-4 was over $100 million, and some AI computational specialists believe that the first $1 billion model is currently or will shortly be developed.
As semiconductor chips rise in complexity, costs come down because transistors are packed more densely on silicon, cutting the cost per transistor during fabrication as well as lowering operational costs for energy and heat dissipation. That miracle of performance is the inverse with AI today. To increase the complexity (and therefore hopefully quality) of an AI model, researchers have attempted to pack in more and more parameters, each one of which demands more computation both for training and for usage. A 1 million parameter model can be trained for a few bucks and run on a $15 Raspberry Pi Zero 2 W, but Google’s PaLM with 540 billion parameters requires full-scale data centers to operate and is estimated to have cost millions of dollars to train.
Admittedly, simply having more parameters isn’t a magic recipe for better AI end performance. One recalls Steve Jobs’s marketing of the so-called “Megahertz Myth” to attempt to persuade the public that headline megahertz numbers weren't the right way to judge the performance of a personal computer. Performance in most fields is a complicated problem to judge, and just adding more inputs doesn't necessarily translate into a better output.
And indeed, there is an efficiency curve underway in AI outside of the leading-edge foundation models from OpenAI and Google. Researchers over the past two years have discovered better training techniques (as well as recipes to bundle these techniques together), developed best practices for spending on reinforcement learning from human feedback (RLHF), and curated better training data to improve model quality even while shaving parameter counts. Far from surpassing $1 billion, training new models that are equally performant might well cost only tens or hundreds of thousands of dollars.
This AI performance envelope between dollars invested and quality of model trained is a huge area of debate for the trajectory of the field (and was the most important theme to emanate from our AI Summit). And it’s absolutely vital to understand, since where the efficiency story ends up will determine the sustained market structure of the AI industry.
If foundation models cost billions of dollars to train, all the value and leverage of AI will accrue and centralize to the big tech companies like Microsoft (through OpenAI), Google and others who have the means and teams to lavish. But if the performance envelope reaches a significantly better dollar-to-quality ratio in the future, that means the whole field opens up to startups and novel experiments, while the leverage of the big tech companies would be much reduced.
The U.S. right now is parallelizing both approaches toward AI. Big tech is hurling billions of dollars on the field, while startups are exploring and developing more efficient models given their relatively meagre resources and limited access to Nvidia’s flagship chip, the H100. Talent — on balance — is heading as it typically does to big tech. Why work on efficiency when a big tech behemoth has money to burn on theoretical ideas emanating from university AI labs?
Without access to the highest-performance chips, China is limited in the work it can do on the cutting-edge frontiers of AI development. Without more chips (and in the future, the next generations of GPUs), it won’t have the competitive compute power to push the AI field to its limits like American companies. That leaves China with the only other path available, which is to follow the parallel course for improving AI through efficiency.
For those looking to prevent the decline of American economic power, this is an alarming development. Model efficiency is what will ultimately allow foundation models to be preloaded onto our devices and open up the consumer market to cheap and rapid AI interactions. Whoever builds an advantage in model efficiency will open up a range of applications that remain impractical or too expensive for the most complex AI models.
Given U.S. export controls, China is now (by assumption, and yes, it’s a big assumption) putting its entire weight behind building the AI models it can, which are focused on efficiency. Which means that its resources are arrayed for building the platforms to capture end-user applications — the exact opposite goal of American policymakers. It’s a classic result: restricting access to technology forces engineers to be more creative in building their products, the exact intensified creativity that typically leads to the next great startup or scientific breakthrough.
If America was serious about slowing the growth of China’s still-nascent semiconductor market, it really should have taken a page from the Chinese industrial policy handbook and just dumped chips on the market, just as China has done for years from solar panel manufacturing to electronics. Cheaper chips, faster chips, chips so competitive that no domestic manufacturer — even under Beijing direction — could have effectively competed. Instead we are attempting to decouple from the second largest chips market in the world, turning a competitive field where America is the clear leader into a bountiful green field of opportunity for domestic national champions to usurp market share and profits.
There were of course other goals outside of economic growth for restricting China’s access to chips. America is deeply concerned about the country’s AI integration into its military, and it wants to slow the evolution of its autonomous weaponry and intelligence gathering. Export controls do that, but they are likely to come at an extremely exorbitant long-term cost: the loss of leadership in the most important technological development so far this decade. It’s not a trade off I would have built trade policy on.
The life and death of air conditioning
Photo by Ashkan Forouzani on Unsplash
Across six years of working at TechCrunch, no article triggered an avalanche of readership or inbox vitriol quite like Air conditioning is one of the greatest inventions of the 20th Century. It’s also killing the 21st. It was an interview with Eric Dean Wilson, the author of After Cooling, about the complex feedback loops between global climate disruption and the increasing need for air conditioning to sustain life on Earth. The article was read by millions and millions of people, and hundreds of people wrote in with hot air about the importance of their cold air.
Demand for air conditioners is surging in markets where both incomes and temperatures are rising, populous places like India, China, Indonesia and the Philippines. By one estimate, the world will add 1 billion ACs before the end of the decade. The market is projected to before 2040. That’s good for measures of public health and economic productivity; it’s unquestionably bad for the climate, and a global agreement to phase out the most harmful coolants could keep the appliances out of reach of many of the people who need them most.
This is a classic feedback loop, where the increasing temperatures of the planet, particularly in South Asia, lead to increased demand for climate resilience tools like air conditioning and climate-adapted housing, leading to further climate change ad infinitum.
Josh Wolfe speaking at Nvidia Auditorium at Stanford. Photo by Chris Gates.
Josh Wolfe gave a talk at Stanford this week as part of the school’s long-running Entrepreneurial Thought Leaders series, talking all things Lux, defense tech and scientific innovation. The .
Lux Recommends
As Henry Kissinger turns 100, Grace Isford recommends “Henry Kissinger explains how to avoid world war three.” “In his view, the fate of humanity depends on whether America and China can get along. He believes the rapid progress of AI, in particular, leaves them only five-to-ten years to find a way.”
Our scientist-in-residence Sam Arbesman recommends Blindsight by Peter Watts, a first contact, hard science fiction novel that made quite a splash when it was published back in 2006.
Mohammed bin Rashid Al Maktoum, and just how far he has been willing to go to keep his daughter tranquilized and imprisoned. “When the yacht was located, off the Goa coast, Sheikh Mohammed spoke with the Indian Prime Minister, Narendra Modi, and agreed to extradite a Dubai-based arms dealer in exchange for his daughter’s capture. The Indian government deployed boats, helicopters, and a team of armed commandos to storm Nostromo and carry Latifa away.”
Sam recommends Ada Palmer’s article for Microsoft’s AI Anthology, “We are an information revolution species.” “If we pour a precious new elixir into a leaky cup and it leaks, we need to fix the cup, not fear the elixir.”
I love complex international security stories, and few areas are as complex or wild as the international trade in exotic animals. Tad Friend, who generally covers Silicon Valley for The New Yorker, has a great story about an NGO focused on infiltrating and exposing the networks that allow the trade to continue in “Earth League International Hunts the Hunters.” "At times, rhino horn has been worth more than gold—so South African rhinos are often killed with Czech-made rifles sold by Portuguese arms dealers to poachers from Mozambique, who send the horns by courier to Qatar or Vietnam, or have them bundled with elephant ivory in Maputo or Mombasa or Lagos or Luanda and delivered to China via Malaysia or Hong Kong.”
