Fiscal Vespers - Lux Capital

America’s strategic goals teeter on the edge of a looming fiscal cliff

Capitalism gets a bad rap, some of it deserved. But the magic of capitalism — the kernel that consistently thwarts those who wish to overthrow it — is its ultimate truth-seeking nature. Dreams can defy economics for only so long before expenses, tradeoffs, risks, decisions and strategies have to be brought into balance. It’s an economic system that demands an accounting, a reckoning, with truth. It’s not always instant, and it certainly isn’t always pretty to watch, but the capitalistic asymptote heads toward unvarnished rationality.

America’s curse is that even as it piously prays to the priests of financial capital, it regularly engages in flights of fancy freighted with fiscal illogic. We’re a consumer society, and we drive a hard bargain. We want Sam’s Club superpower supremacy: in bulk, cheap, and with an affordable membership program coupled to a smiling greeter that checks our card. We want pathbreaking laboratories, world-class medical facilities and schools and top-notch public services, but at tax rates that feel like theft. Even as we lose more properties on the Monopoly board, we just want to accelerate our drive past Go and pause on Free Parking.

Our approach to governance is to always be shopping for that three-for-one special, and never quite finding it. But there are no specials, there are no deals, and the capitalistic reckoning is fast approaching.

This week, Fitch downgraded U.S. debt a notch from AAA, mirroring a similar downgrade made by S&P back in 2011 that remains in place to this day. Just like in 2011, the immediate cause of Fitch’s announcement was the high-wire act of lifting the debt ceiling earlier this summer. But unlike in 2011, there are now far greater concerns about the mathematics of America’s fiscal order, and not just the political logjam on Capitol Hill.

In the 2023 fiscal year, the federal government’s deficit is $1.4 trillion, an increase of 170% over the previous year according to the Treasury Department. The Congressional Budget Office’s analysis shows that these deficits are set to expand. The combination of higher borrowing costs and yawning government deficits is exponentially increasing the nation’s recurring interest costs, to say nothing of state and local governments that face their own extensive fiscal woes. In the third quarter of 2020, America’s annualized interest payments were $516 billion. Just three years later, that’s nearly doubled to $970 billion, overtaking the Department of Defense’s budget for the first time.

It’s not just Congress that’s been profligate, as American consumers have matched the government’s voracious appetite for debt with their own verve. American revolving debt (i.e. credit cards and similar products) expanded nearly 30% in the two years between April 2021 and May 2023 as measured by the Federal Reserve, increasing by $282 billion in the wake of three rounds of pandemic stimulus checks. On a nominal basis, it’s the highest credit card debt the country has ever reached.

The debt-addled spending has certainly fueled inflation (those eye-watering travel fares to Europe this summer didn’t come from the ether), but more importantly, it’s maintained growth in the American economy even as most financial indicators have pointed toward recession. Borrowing from the future to pay for present stability comes at a cost though, one that capitalism enjoys rectifying. The valuation of trillions of dollars of commercial and residential real estate have yet to reconcile with the new reality of high interest rates, a scale of value collapse that could still prove devastating.

The even greater reckoning to come though is America’s global position at the forefront of science, defense and development. U.S. competition with China is predicated on matching aggressive investment from Beijing that has allowed China to take the pole position across the Global South if not much of the industrialized world.

Just as America needs to strategically invest, it finds itself strangulated by crimson tides of red ink.

No domain has gotten more attention than the race at the frontiers of science, with strong echoes of America’s competition with the Soviet Union still very vivid among the Beltway set. Last year’s passage of the CHIPS and Science Act offered a headline investment of tens of billions of dollars into semiconductor research, fab construction and expanded funding for research institutions, most notably the National Science Foundation (NSF).

Yet, in this year’s budget negotiations, science funding is now recoiling from its heady highs. The House committee has proposed a 5.9% reduction to the National Institutes of Health (NIH), and the Senate’s counterpart countered with a paltry 2% increase last week (roughly matching President Biden’s recommendation). Final numbers will arrive as the House and Senate reconcile their different versions of the budget, but in an inflationary environment, such small numbers ultimately shrink the work of the NIH. Thankfully, the NSF is on course to fare better.

Compare that milquetoast commitment to scientific expansion to the authoritative vision of Xi Jinping, who has placed technological self-determination and scientific prowess as one of China’s top objectives. America of course remains the leading global home of science, but that leadership is predicated on long-horizon science investigations consistently funded by Congress. A reversal of our recent surge in investments could undo almost all of its value.

As we turn toward defense, there is growing awareness that America’s fiscal position and its strategic goals are no longer in alignment. In a breathtaking report published last week, RAND described an America chastened by what might be dubbed imperial overstretch in the Paul Kennedy sense:

Over time, the tasks borne by U.S. forces grew more numerous and more demanding as their capacity to accomplish these tasks stagnated. Ernest Hemingway observed that a person goes bankrupt in two ways: “Gradually, then suddenly.” The same could be said for U.S. military dominance and, more broadly, for the solvency of U.S. defense strategy.

Crisis after crisis has hit America (just this week, a coup in Niger has upended geopolitics in the Sahel – and we don’t even have the time to talk about it!), forcing defense planners to thin the military’s posture across more theaters, more types of combat and more adversaries than ever before. The situation is acutely tenuous:

Collectively, these trends have created a growing gap between the goals of U.S. national security strategy and the ways and means available to support those goals. Left unchecked, these trends will almost certainly lead to increased regional instability, reduced U.S. influence and security, and metastasizing challenges to U.S. and allied interests.

RAND argues for an adaptable posture that leverages allies and could cost the United States only tens or small hundreds of billions of incremental spending. That’s already asking for a lot, and America struggles to fund even high-leverage initiatives in defense. The Office of Strategic Capital, a much-ballyhooed initiative at Defense to connect trusted private investment into the defense industrial base, looks set to miss authorization for its loan program this year after the department failed to ask for authorities from Congress. We’ll try again next year, I guess.

The general crisis at Defense is equally matched at the State Department, where under-funding for Asia-Pacific has now yawned to historical proportions. A report from State to Congress obtained by Foreign Policy last week showed that the department is tens of billions of dollars short in countering China’s extensive diplomacy, investment and programming across the Pacific and around the world:

The Biden administration says matching China’s growing diplomatic and military muscle in the Indo-Pacific is one of its top priorities. Yet according to State Department budget documents, there is a $41.3 billion gap between what the Biden administration has given the State Department and the U.S. Agency for International Development (USAID) and what those departments anticipate needing to carry out that mission over the next five years.

That’s a nice segue from defense to development, where USAID was in the spotlight this week after Congressman Matt Gaetz called for the agency to be abolished. Gaetz knows how to pull a media stunt with the best of them (“USAID does not serve a meaningful purpose. It is used as a slush fund for international wokeism”), but his views align with a growing number of congressmen balancing domestic investment with overseas influence. Only one of those two blocs vote in elections.

The pullback on American aid echoes a similar retrenchment in the United Kingdom, where foreign aid budgets were cut under former Prime Minister Boris Johnson, leading to this week’s depressing report from the Foreign Office of what tighter budgets have meant for Britain’s influence and standing in the world.

Reckoning, accounting, atoning. The theology of capitalism is forcing America to confront its position in the world with renewed clarity, and the acuity isn’t pleasing. Reversions on science, defense and development are just a few of the myriad areas where retrenchment is being ushered in this year. And that’s still assuming America can hold on to an annual deficit of 6% of GDP while interest rates remain at recent historical highs. There isn’t an Ozempic for the federal budget, nor a Black Friday special that might match our desires with our checkbooks. Capitalism’s kernel of truth wins another day.

Lux Investment: Reflex

Grace Isford; Reflex co-founders Nikhil Rao and Alek Petuskey; and Brandon Reeves (L to R)

Summer has been busy here at Lux, and nowhere has it been busier than in the world of AI. Python over the last decade has become the programming language of choice in the AI community, building upon the language’s widespread usage in data science. Yet one of Python’s weaknesses is its limited support for building web applications, which have traditionally been the province of JavaScript. It’s a gap that we’re excited to finally see filled.

Lux led a $5 million seed round into Reflex (formerly Pynecone), a platform that allows developers to build frontend and backend web applications cohesively with just one language: Python. Lux partners Grace Isford and Brandon Reeves wrote up the company’s story and our thesis for the company, while TechCrunch’s Ron Miller wrote a great funding announcement on Reflex as well.

Podcast: We need to go deeper with the inception of deep geothermal energy

Historians survey the past and the Twitterati (X-erati?) process the events of the present day. But what does it mean to search the future for clues of what’s to come — and how much longer will we have to wait for it?

In this episode of "Securities", I welcome Lawrence Lundy-Bryan, research partner at Lunar Ventures and the publisher of "State of the Future”, a Deep Tech Tracker whose distinguishing feature is its extraordinarily wide remit to investigate the interstices of science and technology and find the morsels of innovative goodness that will power the planet in the years ahead. Also joining is Lux Capital’s own scientist-in-residence Sam Arbesman, who is certainly no stranger to the crazy ideas straddling science fiction and science fact.

Lawrence shares his unique approach to identifying and evaluating emerging technologies such as deep geothermal energy. We then pivot to exploring Lawrence’s approach of finding the future through the methodology of “horizontal scanning.” What’s to come? Listen and find out.

🔊 Listen to the episode
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Lux Recommends

Sam recommends an IEEE Spectrum piece on Gottfried Wilhelm Leibniz’s search for a machine of truth, part of a series on the history of natural language processing. “Leibniz’s central argument was that all human thoughts, no matter how complex, are combinations of basic and fundamental concepts, in much the same way that sentences are combinations of words, and words combinations of letters. He believed that if he could find a way to symbolically represent these fundamental concepts and develop a method by which to combine them logically, then he would be able to generate new thoughts on demand.”
Our summer associate Ken Bui has been looking into China and generative AI. He highlights two pieces, an article by Qiheng Chen in The China Project on “China sets restrictions on generative AI, but leaves room for innovation” and a paper by Matt Sheehan through the Carnegie Endowment on “China’s AI Regulations and How They Get Made.”
Not a long read, but I do think we should all take a gasp: Uber has finally turned a profit, after an estimated $31.5 billion in cumulative losses. It apparently takes a dollar to make, well, three dollars, given the company’s current $93 billion market cap. It has come a long ways from when I used to write about its frankenboard.
Our summer associate Koko Xu enjoyed this classic debate between Peter Thiel and Marc Andreessen at the Milken Institute. He also points to Sam Lessin’s latest column in The Information on “The End of Venture Capital as We Know It”. “You will know you are doing real venture capital when you aren’t competing with other investors to finance a deal but are instead offering to invest in people, industries and ideas that don’t yet have access to capital.”
Our Sam loved Riley Black’s question, “How Many Dinosaurs Remain Undiscovered?.” “Future finds are likely to be of small dinosaurs. Big dinosaurs were often found first because their remains were more resilient to scavenging, weathering and destruction than those of smaller animals, and museums liked having large, impressive dinosaurs to reconstruct for patrons.”
Finally, Ken, who has terrible taste, proffers Tammie Teclemariam’s screed against burrata in “A Big Fat Blob of Boring: Can we cool it with all the burrata balls?.” I’ll say this: You can take my (burrata) balls out of my cool, dead hands.

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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