Nuclear is having its media moment. Perhaps that’s what happens when a Democratic president visits the home of James Murdoch, the younger son of conservative media magnate Rupert Murdoch, and starts talking about “Armageddon.”
Details from the political fundraiser in New York City have heightened tensions across the world. “We have not faced the prospect of Armageddon since Kennedy and the Cuban Missile Crisis,” pool reporters quoted the president. It’s the “first time since the Cuban Missile Crisis, we have a direct threat of the use (of a) nuclear weapon if in fact things continue down the path they are going.”
One analyst called the comments “bone chilling” although I am pretty sure bones heat up in a nuclear catastrophe.
For weeks now, DC analysts have been hotly (chillingly?) debating whether Russian President Vladimir Putin, whose forces in Ukraine seem to be increasingly tattered and on the run, might consider using a “tactical nuclear weapon” to push back advancing Ukrainian troops. President Joe Biden had strict words for his Russian counterpart: “I don’t think there’s any such thing as the ability to easily (use) a tactical nuclear weapon and not end up with Armageddon.”
There’s been so much chatter about tactical nuclear weapons, but not nearly enough analysis on exactly how and why Russia might use such weapons. Even if you remove the risk of triggering global thermonuclear war, the battlefield utility of small nuclear weapons is limited. The Ukrainians, attempting to evade bombardment from Russian forces for months now, have decentralized its military operations, presenting relatively few valuable targets for a stronger bomb to strike. Any nuclear attack — small or large — would generate fallout, presenting a hazardous zone for friendly and enemy forces alike. And yes, while that could be the objective in and of itself, such an attack would be a tacit admission of surrender on the part of the Russians.
Even so, some analysts have placed the risk of a Russian nuclear attack at 10-20%. Some have it higher. Supposedly the White House has it even higher. Those sobering assessments have forced the president’s national security advisor Jake Sullivan to say that “catastrophic consequences” would result from such an attack, and also led to the president’s grave comments this week.
Of course, nuclear fallout in Ukraine doesn’t just have to be triggered by a weapon. Russia took over the Zaporizhzhia nuclear plant in March and has been operating it with its original Ukrainian engineering staff ever since. Now, Russia wants the staff to sign new employee contracts, endangering the workforce of one of Europe’s largest nuclear facilities, even while Russian missiles strike just outside of the plant’s walls.
Nuclear’s media moment isn’t just limited to the Old Continent. As we have talked intermittently across “Securities” newsletters, North Korea seems hell-bent on diverting attention from Russia’s potential nuclear attacks to its own.
A month ago, Kim Jong Un declared that the Democratic People’s Republic of Korea (DPRK) is a nuclear weapons state and that it would never give up its nuclear arsenal. That arsenal — and the country’s increasing number of delivery vehicles — is getting a serious workout in 2022. This week, the country fired an intermediate-range ballistic missile over Japan, leading to emergency disruptions across the islands. At 2,850 miles, it’s the farthest a DPRK missile has flown and it was its most aggressive test this year, a year in which the country has so far fired a record 43 missiles in tests. There are now concerns that North Korea is preparing for a new nuclear test, which would be its first since 2017.
While war and strategic threats have certainly dominated the headlines recently, nuclear’s media moment isn’t exclusive to the complete destruction of all life on Earth. In fact, a number of stories this week and over the past month showed that the path remains open for nuclear to be the savior of life on Earth as we confront the climate emergency.
The biggest news on this front came from Pittsburgh a week ago where Department of Energy officials announced that they were committing $50 million for commercialization of fusion technology — what one industry advocate described to CNBC as “the first substantial investment by the U.S. government into private sector fusion-energy companies.”
We covered some of the developments and milestones in the fusion world back in “Fission today, fusion tomorrow” as well as critiques in “Vaporware skepticism.”Large questions about the viability of fusion technologies remain, not to mention the timeline for developing a net-positive energy reactor. One positive development occurred last month when researchers at South Korea's Seoul National University successfully maintained a 100 million°C reaction for 30 seconds. As Matthew Sparkes wrote in New Scientist:
Lee Margetts at the University of Manchester, UK, says that the physics of fusion reactors is becoming well understood, but that there are technical hurdles to overcome before a working power plant can be built. Part of that will be developing methods to withdraw heat from the reactor and use it to generate electrical current. “It’s not physics, it’s engineering,” he says. “If you just think about this from the point of view of a gas-fired or a coal-fired power station, if you didn’t have anything to take the heat away, then the people operating it would say ‘we have to switch it off because it gets too hot and it will melt the power station’, and that’s exactly the situation here.”
(That’s a nice analogy, although I am pretty sure coal-fired power stations don’t reach 100 million degrees centigrade).
It’s probably worth remaining skeptical of fusion’s immediate prospects, but at least it’s having an impact. Fashion designer Gabriela Hearst of Chloé has triggered reactions with her new collection of fusion-inspired clothing. Vanessa Friedman’s amusing and digressive analysis in The New York Times:
She created a set in the circular shape of a tokamak, the name for the reactor that scientists hope to use to produce thermonuclear fusion. Commissioned an installation from the artist Paolo Montiel-Coppa involving zipping beams of light and giant glowing rings. Invited scientists from the various fusion energy companies to sit front row (you could tell them by their ties). And featured the hydrogen isotope as her aesthetic throughline. The hydrogen isotope!
Nuclear is having its media moments, from the glitzy runways of Paris to the gritty runways of Russia and North Korea. One just hopes we are looking at Atoms for Peace, and not atoms smashing us into pieces.
“It seems end demand has likely deteriorated markedly in recent weeks, and end customers appear to be aggressively draining inventory,” Bernstein’s Stacy Rasgon said. The cut in AMD’s client-revenue “is admittedly a bit breathtaking.”
That decision will likely exacerbate geopolitical tensions, which happens to be the subject of our “Securities” podcast this week. Fletcher School professor Chris Miller is the author of “Chip War: The Fight for the World’s Most Critical Technology,” which was just released this week and is already shortlisted for FT’s best business book of the year. It’s a panoramic global view on one of the world’s most important industries, and Chris and I talked about the layers of intricacies here.
Miller is a scholar of Russia, and perhaps the most interesting bit of the conversation (and one I knew next to nothing about) was the Soviet race for the transistor and integrated circuit. Much like the race for nuclear missiles (we’re not escaping that theme today, are we?) and the space race, the USSR was equally focused on catching up with American advances in electronics. And they did, if a few years tardy. So why don’t we talk today about Russia’s semiconductor industry?
The challenge, according to Miller, is that the Soviets never developed a consumer market for their products in the way that the U.S. had both corporate clients who needed computing for accounting and consumers buying electronics like pocket calculators (which he dubbed “the iPhone of the 1960s”). Without demand, there was no forcing function for improving and competing, and as Taiwan, Japan, Korea and China vied for a share in the global industry, Russia was left behind.
We also talked about the transition from human computers to chips, the transition from Hong Kong to Taiwan in outsourcing assembly, how TSMC became the leader in lead edge fabrication, free trade and its centrality to the industry, and finally, whether interlinkages help or ultimately hurt national security for countries like the U.S. and China — particularly apropos given the White House’s announcement today.
Our scientist-in-residence Sam Arbesman has been having fun playing with a new machine learning model from Google dubbed the Nonsense Laboratory, which combines data on phonetics and language with physical mouth movements to create new words and transform existing ones.
On the other side of nuclear energy is oil, and the big news this week was that OPEC+ decided to cut crude production in a bid to increase energy prices. The realignment of the cartel, which includes both Saudi Arabia and Russia, is one of the most interesting geopolitical changes in some time, and portends a tough period ahead for Europe.
The New York Times had a flashpoint article this week about New York University firing a chemistry lecturer due to student complaints that his organic chemistry class was too hard. It struck a nerve, but honestly, I found the whole situation overblown: large-lecture, weed-out courses in the sciences have absolutely done more harm than good for America’s competitiveness in STEM. The faster the fields move to more individualized and experiential learning, the better.
Last week, I wrote about “Sisyphean maintenance”, and somehow missed Alex Vucolo’s beautiful piece in Noema on “The Disappearing Art Of Maintenance”. "If you start talking with engineers about maintenance, somebody always brings up Incan rope bridges.”
Finally, a number of journalists have been investigating exactly what happened to the CIA’s top overseas sources in the early 2010s, many of whom were discovered and killed in rapid succession across multiple countries. Joel Schectman and Bozorgmehr Sharafedin wrote an update in the chronicle in Reuters, focusing on interviews with six former Iranian informants for the CIA. Their simple thesis is in the headline, “America’s Throwaway Spies.”
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.”
