Existential Engineer - Lux Capital

How to construct an optimistic existentialism

Emerging from vacation the past few weeks, it’s hard to feel any sort of respite. The layered bleakness — political, security, economic, social, technological, planetary — is profound and relentless. Pessimism, dark and brooding, abounds.

A supposed antidote to this is “optimism,” unearthing generic goodness from wherever it might be found. But I find seeking such sunny soothsaying to be a trying exercise, the adult version of the parental aphorism of “don’t worry, everything will soon be better.” Adults know what they never tell their children, that all will not necessarily be better, and everything we observe is in fact contingent on human agency.

I am not optimistic, but I can appreciate contingency and human agency, and that offers us the most hopeful path forward. At the heart of every negative event is the hand of human intellect and execution. Rebuffing that negativity requires the arduous optimism of work, the belief that we can engineer a better society, culture, and planet for human flourishing. We, collectively and individually, are the ultimate commanders of our own destiny.

A few weeks ago, I read Samuel C. Florman’s The Existential Pleasures of Engineering, a work that has mostly disappeared from the public eye while nonetheless offering a timeless appeal. He interrogates one of the key humanistic questions: why do we build? What’s with all the effort to expand the population, to build new cities, to pursue new scientific inventions? The obvious answer is that we can so we do, but Florman pushes us much farther than that, arguing that “At the heart of engineering lies existential joy.”

Florman excoriates the pontificating at the heart of the Western tradition. “In the broad view, however, it can be seen that the effect of our Greek and Christian heritage has been to convince us that materialism is a defect in human nature.” He argues that materialism is in fact what motivates humans to begin with. “We recognize that we cannot survive on meditation, poems and sunsets. We are restless. We have an irresistible urge to dip our hands into the stuff of the earth and to do something with it.”

Our heritage is interpreted as anti-materialism, but in fact, the great works of Western civilization are suffused with materialist energy. The Bible is exhaustive at times on details of buildings and castles, food and goods, and for good reason, since the creation of beautiful works is not just a benefit to humanity, but an offering to God as well. Some of these grand creations might have been a shock of novelty for pre-modern societies, but Florman argues that we can still equally enjoy that shock today. “We are not as naïve as we were, but we have not been stripped of all enthusiasm and capacity for wonder.”

Florman name checks Albert Camus and his essay, The Myth of Sisyphus, on the unrelenting struggle of Sisyphus pushing a boulder up a mountain only to watch it roll back down again and start all over. Camus argues that this repetition isn’t nihilism, but rather a form of empowerment and identity formation, since the constant struggle of the boulder offers Sisyphus existential meaning. Florman sees much the same with the engineering profession:

But we are beginning to realize that for mankind there will never be a time to rest at the top of the mountain. There will be no new arcadian age. There will always be new burdens, new problems, new failures, new beginnings. And the glory of man is to respond to his harsh fate with zest and ever-renewed effort.

This observation reminded me of a section from Leon Wieseltier’s essay from 2021 on American interventionism overseas (or lack thereof) in “Where are the Americans?”:

Those who forget history are sometimes condemned to repeat it and sometimes not; and those who remember history will know that it never slows down or stops, it offers no ellipses or time-outs, there is no interregnum between crisis and crisis in which we may calmly reflect and attend conferences before we act again.

(I would love an historical ellipsis right about now).

One key modification to Camus’s thesis is in order. While it is true that Sisyphus is repeatedly pushing a boulder up a mountain, it’s not at all clear that the work is identical from climb to climb. Maybe it’s a different boulder, a different route, a different mountain entirely. Not unlike a hiker who takes different courses but still reaches the same summit, we can see how scientists and engineers repeat the same stages of work (observation, experimenting, theorizing) even as they transition from one project to the next. Even as the boulder comes back down to the ground, something has been gained in the process — we never end up precisely where we started. Sisyphus is the accumulation of all previous struggles, what one might dub wisdom.

Florman acknowledges this in engineering:

The engineer today, for all his knowledge and accomplishment, can still look out on seas scarce charted and on coasts still dark. Each new achievement discloses new problems and new possibilities. The allure of these endless vistas bewitches the engineer of every era.

Solutions are not endpoints, but rather waypoints on the constant journey of human discovery. We obviously see this braided weave in software and science, where code or an experiment may offer us a feature or insight only to lead us to the next challenges to be solved. Those challenges were always lying in wait, and we just never witnessed them because we lacked the means to. Once we open our eyes, we quickly discover the frontiers again, and like Sisyphus, start rolling the boulder of imagination to once again push that frontier further out.

Florman argues that the existential pleasure of engineering isn’t just the utility of the creations, but also the aesthetic value of the inventions themselves. Art and engineering are not enemies, but rather profoundly intertwined:

For the engineer there is ample evidence both from men of letters and men of the fine arts that the machine, rather than cutting him off from the wellsprings of beauty, opens before him new vistas of truth, splendor, and elegance. The beauty of the machine is pure, like mathematics. It is also, paradoxically, imbued with the vitality of humanity, since it is exclusively man-made.

In here, I am reminded of Matthew Crawford’s books like Shop Class as Soulcraft and The World Beyond Your Head, which emphasize the spiritual power of physical creation. The satisfaction that comes from building — for finding the next stage of solutions in the course of the human struggle — is unlike anything offered elsewhere in the modern economy. In the latter book, Crawford discusses the repair of musical organs at extended length. Organs are repaired perhaps once a generation, which means that any maintenance conducted today won’t be evaluated or even witnessed by another person for decades. It’s a vocation answerable only to the quality of one’s personal skill.

All of which brings us back to our world, and the amplifying pessimism that radiates in all directions. When we carefully consider the crises and the maledictions, all of them are derivative of human designs and decisions, problems that originate in the solutions of yesteryear. Each problem is a palimpsest of the human impulse to fix, layers upon layers of solutions that couldn’t quite reach the finish line.

Take climate change. One engineering solution after another, from the use of oil to power our homes to the incredible engineering of our natural world to serve human interests through the likes of dams, has culminated in our present crisis. Some would propose degrowth, a return to that rustic arcadia of pre-modern civilization outside of the petro-capitalism that runs our world. Yet, no one of any analytical depth believes that 8 billion people approaching 10 billion by century end can survive on humanity’s prior primitive technology. So it’s not even a solution — it’s a death sentence. The only path forward isn’t to retrograde our world — it is to progressively engineer forward, undoing what doesn’t work but absolutely doubling down on what does.

Or take inequality. The “machine” at the heart of our economy — capitalism — is under increasing strain from yawning inequality gaps driven by market consolidation and technological network effects. Some critics would burn down the machine, hammering away with the hope of implementing a new engine capable of delivering a more equal and just world. Yet the solution is far simpler and closer, which is tuning the machine we have right before us. We haven’t even tried to ameliorate capitalism’s most ravaging aspects, even as we enjoy the bounties it offers.

These are two gargantuan challenges among dozens that beset us today. Florman and Camus both take an individualistic view to existentialism, of building machines or pushing boulders that in the course of the work, allow us to discover ourselves and the meanings of our existences. It’s an exhausting path, but that exhaustion doesn’t have to be solitary. Sisyphus may indeed be pushing a boulder up a mountain, but he is just one of millions pushing the same boulders up the same mountains. Florman acknowledges the engineer as a member of a profession, but under analyzes the work in the context of teams, a very typically Western intellectual blindness.

We face the greatest challenges humanity has faced in a generation. But we have a new generation of humans brimming with ideas and expertise ready to usher in the next set of solutions. Like a magnet, the positive ambitions of builders are attracted to the most negative of events — and want to bind with them to the very fiber of their existences. That’s not optimism, but merely the fundamental physics of human experience.

Lux Recommends

Our scientist-in-residence Sam Arbesman recommends Gemma Conroy’s look at how generative AI technologies like ChatGPT could transform scientific publishing in the decade ahead. “‘It’s never really the goal of anybody to write papers — it’s to do science,’ says Michael Eisen, a computational biologist at the University of California, Berkeley, who is also editor-in-chief of the journal eLife. He predicts that generative AI tools could even fundamentally transform the nature of the scientific paper.”
Shaq Vayda recommends two movies for your weekend watching pleasure. The first is Wes Anderson’s Asteroid City, a mid-century, colorful set piece of children and adults in the context of a school stargazing trip. He also recommends Matt Johnson’s movie BlackBerry, about the eponymous mobile device that changed the world but didn’t live to see its everlasting effects.
Tess Van Stekelenburg and Sam both recommend The MANIAC by Benjamin Labatut, the latest novel by the author of the critically-acclaimed When We Cease to Understand the World. In this story, Labatut follows famed polymath John von Neumann and explores his complex relationships with humans and the development of computing. And speaking of books, Sam also recommends Jeff Jarvis’s The Gutenberg Parenthesis: The Age of Print and Its Lessons for the Age of the Internet
Yes, yes, I am late, but if you haven’t caught up with Gideon Lewis-Kraus’s look at the academic fraud and replication crisis surrounding Dan Ariely and Francesca Gino, now’s the time. “Simmons told me, ‘We were, like, Holy shit, there are two different people independently faking data on the same paper. And it’s a paper about dishonesty.’”
Sam has a bundle of AI articles to recommend. Over at The New Yorker, James Somers has a great piece on "How Will A.I. Learn Next?.” Over at Ars Technica, Benj Edwards writes on “Telling AI model to ‘take a deep breath’ causes math scores to soar in study,” while a new Arxiv preprint from Ronen Eldan and Mark Russinovich explores techniques for helping large-language models to unlearn information (say from copyrighted sources) without having to expensively retrain them from scratch. Finally, Sam recommends Étienne Fortier-Dubois’s essay on “AI as Sparkly Magic.” “If AI becomes better at us at programming, at writing, at science, and especially at making new AIs, then it and its descendants will constantly create new technology that is incomprehensible to humans. Magic will flood the world, and for the first time it’ll be sufficiently advanced to be deserving the name. We’ll have cures for cancer that are, effectively, magic potions; we’ll have sources of energy that are the equivalent of shooting electric arcs with our hands.”
I’m excited to read Samuel W. Franklin’s The Cult of Creativity: A Surprisingly Recent History. From the review in The Wall Street Journal, “Despite its outsize importance in the workplace, creativity as a job qualification is a relatively new concept. The first-known written instance of the word didn’t appear in print until 1875, and before roughly 1950 there was nary an article, book or lecture on the topic.”
Finally, Sam recommends “How would we know whether there is life on Earth? This bold experiment found out” in Nature and Adam Frank’s “Humans Are Ready to Find Alien Life.” “The search for aliens is a project whose progress is probably going to be measured in decades. But that’s okay. A few decades of being careful and clever is nothing compared with the thousands of years it took to get us where we are today, standing on the threshold of discovery, about to step across.”

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?

Turn to China now, and the story is in a very different place. The Biden administration has placed a series of export controls on advanced computation and semiconductor fabrication to China, including blocking the export of Nvidia’s H100 and A100 chips. Nvidia responded in March by offering tweaked versions that comply with U.S. export controls (with what it dubs the H800 chip), but the general policy remains in force: prevent China from acquiring the best chips that Earth produces.

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.

A few weeks ago, Bloomberg had a great piece about the rising toll of air conditioning under the similarly scary headline, “A Billion New Air Conditioners Will Save Lives But Cook the Planet.” The numbers, as always, are staggering:

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.

And there doesn’t appear to be a way out. Scientists have determined that there is a zone of comfort for humans where we can function at peak performance. Much of the industrialized world happens to sit in these temperate zones, which is one argument for their long-term economic success compared to the tropics. But as climate change intensifies, the world’s temperate zones are expected to narrow dramatically, and some countries like India may have next to no temperate zones left to protect its people. Air conditioning is a necessity (with some even calling it a human right), but greener coolant alternatives are still in their infancy. In other words, cooling innovation needs to heat up in a big way.

Lux on the Farm

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
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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.”
In the happier news department of science, Ina Deljkic recommends “’Quite science fiction’: Brain-spine interface system helps man with paralysis walk again.”
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.”
Finally, Sam recommends Brick Technology’s video of “Making A Billion-Year Lego Clock.”

That’s it, folks. Have questions, comments, or ideas? This newsletter is sent from my email, so you can just click reply.

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October 21, 2023

Loose BRICS

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Reckless Regulators

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