America has a problem with unspeakable evil: it, quite literally, can’t speak about it.
Evils plague American society, of course. A modern census of American evil would include police brutality against people of color; a culture of sexual assault and misogyny that denigrates the rights of women; business executives and a consulting class pushing highly-addictive opioids to millions of Americans; and really, dozens of other major scandals from industrial environmental catastrophes to widespread public corruption and larceny.
It’s a list of evils that’s long and horrific but speakable, comprehendible. Indeed, we constantly discuss many of these evils in the press and in our daily lives, and the systems of justice are moving ever so slowly yet ever forward to extirpate them.
Yet, American society is mostly removed from the unspeakable evils that still beset our world. Systematic torture, arbitrary execution, death squads, genocide — systems of capricious violence designed to massacre humans abound across our continents. It’s unspeakable in both the literal and metaphorical sense of the word — horrifying until we’re mute.
This week, my only surprise has been the emotion of surprise that’s coursed through so many DC policy folks about the events in Ukraine. As one foreign policy friend texted his reaction, “Like this is irrational from Russia’s standpoint.” There has been clear signaling from the Biden administration that war was Vladimir Putin’s ultimate aim in Ukraine, but when the strikes came, a frisson of surprise still struck too. Who really believed that a 1940s-style land war in Europe was still on the menu in the 2020s?
Everyone should have, of course. There is incredible evil in the world, people who don’t want to just gain power, but want to use their power to dominate, enslave, maim, and kill those who they think deserve it. History and the literary cultures of all societies are suffused with stories of megalomaniacs, demagogues, and narcissists who are a risk to all if not contained. We’ve been warned so many times, and yet with each new generation, those warnings once again go unheeded.
The feelings of surprise this week quickly curdled into anguish. “How are we supposed to fight climate change when we have to fight Putin,” one friend asked. Europeans in particular are confronting the existentialism that comes when defending wealth and comfort against an enemy with little regard for human life or misery. ‘We just want to be left alone’ is the refrain of so many people in the West — why can’t we just enjoy our luxuries and friends? Why are we potentially being asked to die in a senseless war started by a dictator I never asked to exist in the first place?
That attitude persists, even as the darkness closes in. Democracy on every metric is in retreat across the globe. Conflicts — most of which get scant press coverage — continue to rage and cost hundreds of thousands of lives per year. Resource scarcity is exacerbating these conflagrations, throwing more humans into the maelstrom of evil every single day. Many will never escape.
We should have anguish, but we should also have anger, anger that instead of investing in the future or progress or peace, we’re instead going to have to mobilize counter-attacks and use precious resources to fight one man’s obsession with possession. We didn’t ask for this mission, but we are called to respond to it nevertheless.
Last week, I ran out to grab a new translated collection of Albert Camus' speeches titled Speaking Out, which includes his heralded American address The Crisis of Man delivered at Columbia University in 1946 as he surveyed the postwar situation. In it, he describes how a generation came to terms with the brutal world they witnessed:
I think I can safely say that we shall always refuse to worship events, facts, wealth, power, History as it is made and the world as it goes. We wish to see the human condition as it is. And what it is, we know. It is that terrible condition which demands truckloads of blood and centuries of history to achieve an imperceptible modification in the fate of man. Such is the law. […] We French of the twentieth century know that terrible law only too well. There was the war, the occupation, the massacres, thousands of prison walls, a Europe frantic with pain — and all that in order for some of us finally to gain the two or three slight differences which will help them despair less. It is optimism which would be the outrage here.
What it is, we (now should) know. The time for surprise at the acts of unspeakable evil is over.
Rebuilding the arsenal of democracy will take time. We need to build more resilient societies, immunized from overseas disinformation and propaganda, to create the kind of broad consensus needed to fight across all planes of battle. We need to build up our defenses, and as depicted in books like Paul Kennedy’s Engineers of Victory, create the infrastructure that offers a strong defense for all free nations. And we need to inculcate the values of patience and sacrifice that these conflicts will inevitably demand for victory.
To the people of Ukraine: we stand united in solidarity in your struggle as you fend off the worst offensive military assault in Europe in 80 years. Unspeakable evil has a name today, and it’s Vladimir Putin. And for the first time in years, America is finally starting to speak about the very deep evils that pervade our global home. It’s a terrible condition to find — one that might unfortunately take truckloads of blood and centuries of history — but one that America has never shirked when it’s finally made up its mind to fight.
In line with ”Deextinction of taste” a few weeks ago, Shaq Vayda recommends this paper in Genome Biology which shows that the most accurate bioinformatic software comes from sustainable software practices, and not number of citations or journal ranking.
A meditation on productivity and time, Mary Harrington writes a great piece on “The curse of sliced bread.”
In, “The Rare Gift of Seeing Extra Colors,” science documentarian Jackie Higgins explores people who express tetrachromacy, a gene that allows people to see more colors than others, with implications for artists and culture.
Vannevar Labs co-founder Brett Granberg pens an excellent introduction on “How to Invent Defense Products”. We're going to be needing a whole heck of a lot more of these in the years to come.
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
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 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.”