C’anterbury Tales - Lux Capital

The United Kingdom is dead. Long live … nope, nope, it’s pretty much dead

As we celebrated Fourth of July this week, all I can say is: thank heavens the Founding Fathers fought to leave the United Kingdom.

Something is rotten in the state of Albion, and it probably starts with the sewage streams coursing through the country’s waterlogged landscape. The past two weeks have put a global klieg light on Thames Water, the private utility that supplies water to about 15 million Britons (out of a population of 67 million). The fecal stench doesn’t stop with the company’s negligent dumping of millions of gallons of raw sewage into the country’s rivers. If only.

The rot extends all the way to its looming financial collapse as one of the country’s most important and most indebted utilities, while simultaneously acting as a Rorschach ink blot test for every economic, political and social theory out there.

First, there are the “green” bonds, if by green we intended to mean the color of algal blooms. Thames Water sold $3 billion worth of green bonds in 2022 alone to ESG investors, all while dumping sewage that has killed marine wildlife and threatened the drinking water of thousands of people. That’s not very E or S or G, and more of an F and U. Who’s at fault? Is it the company that lied about its lack of awareness, or is it an ESG industry that’s hellbent on finding goodness without doing the precise data analysis required to make a judgement (see last year’s The ESG Mirage and related “Securities” podcast).

And those bonds, in addition to being the antipode of ESG, are also not really great bonds, if by bonds we mean financial instruments that will pay its holders … something, or anything. For Thames Water is also in deep financial distress following a prolific debt binge driven by its private equity consortium that has seen the company drowning under $17.7 billion of debt. That debt mostly didn’t pay for service or infrastructure upgrades, but were instead vehicles for extracting profits out of the company under the blind eyes of government regulators. Is privatization and Thatcherite politics to blame? Is it the typical willful incompetence of government officials? This ink blot offers a shape for everyone to identify.

Unfortunately, Thames Water, like much of the U.K.’s water utilities, has a maintenance backlog the length of the post-Brexit export lines to the European Union. As Bloomberg put it this week:

One fifth of all water supplies lost to leaks. Over 800 sewage spills on average every day in 2022. More than £60 billion ($76.4 billion) of debt built up by the water utilities. There is no shortage of numbers to help tell the story of Britain’s failing water industry. But there is only one that really matters: how much will it cost to fix the system.

Even partial estimates suggest hundreds of billions of pounds will be needed. And the bill will almost certainly fall at the feet of households in the form of higher prices or additional taxes.

With great leadership, Thames Water CEO Sarah Bentley resigned last week, nominally because of the sewage spills and the financial penalty the company received although the daunting task of salvaging Britain’s foremost water utility would seem to be a prime explanatory factor as well. One almost envies Andre de Ruyter, who suffered attempted cyanide poisoning and a firing as CEO of South African state energy giant Eskom as he attempted to improve that country’s regular blackouts (discussed further in “Elemental Capacities”). Sometimes the démission is the honorable exit out of the morass.

Thames Water is in a brutal position, but water is just the unfrozen tip of the iceberg for British infrastructure. The Financial Times ran a lengthy story this week on the post-Brexit and post-Covid financial difficulties of the high-speed rail and Chunnel-operator Eurostar that connects London and Paris:

Eurostar is struggling with staff shortages and train reliability issues, and has had to cancel significant numbers of trains over the past year. It has stopped running trains from London to the Disneyland resort near Paris, as well as its former summer direct services from London to Avignon, in southern France. In the UK, Eurostar has also abandoned its former stations at Ebbsfleet and Ashford in Kent and collects passengers only at St Pancras.

Coming only two years after it narrowly averted bankruptcy, the retrenchments have stoked fears that a pioneer of international high-speed rail services is in decline. In the UK media especially, they have been viewed as emblematic of the burdensome bureaucracy and crimped ambitions of the post-Brexit economy. More broadly, the operator’s troubles spell gloom for a key element of the effort to shift passenger journeys from air to rail as Europe attempts to decarbonise its economy.

The FT’s Robert Wright ultimately writes an optimistic story, and I for one wish the Eurostar my best. But the litany of challenges keep coming. There’s the aftermath of the Grenfell Tower cladding fire, with some estimates pegging a complete remediation of flammable British apartments at $67 billion. Britain’s National Health Service is suffering an exodus of doctors and a regular series of strikes that makes American medical burnout seem merely like a bad hangover. As The Observer noted this week:

Nearly 170,000 workers left their jobs in the NHS in England last year, in a record exodus of staff struggling to cope with some of the worst pressures ever seen in the country’s health system…

If Britain had a functioning industry, it was finance, but even there, competition from New York, Euro markets like Amsterdam and Frankfurt, and Singapore have pulled activity away from the City and Canary Wharf. That’s most notable with Arm, founded in Cambridge, UK but now readying an IPO in New York despite intense lobbying from British economic officials. The reason? Arm executives believe that the chip-design company will get a better valuation outside the sterile London Stock Exchange given the AI valuation craze in America. In addition, the war in Ukraine hasn’t done any favors for London finance either, with Russian money no longer passably being laundered through local trading houses, an economic flow that Oliver Bullough ably chronicles in his look at the industry last year in Butler to the World.

British malaise has been a decades-long phenomenon, which I personally date to the Suez Crisis of 1956 although plenty of other dates are reasonable (so many dates to choose from!). That malaise led to and was exacerbated by Brexit, and then was intensified by the Covid shutdowns from which the Isles are still struggling to recover from.

The latest figures published last week show the U.K. stagnating on GDP growth (although missing the technical definition of recession by a thin hair!) while inflation remains the worst among advanced economies (or as CNBC put it in a headline, “Britain is now the only major economy where inflation is still rising”).

The British Embassy to the United States posted a fun tweet using a Friends meme to joke about the Fourth of July, following up with another tweet saying that “We’ve remained the closest of allies and we love our Special Relationship with you.” That Special Relationship has been the bedrock of U.S. diplomacy since World War II, and helped usher in the post-war order from which so much of the globe’s progress and development took place.

But when does the Special Relationship transform into the kind of “special relationship” you have with a wayward uncle whose antics, self-destructive habits and hankering for the limelight finally force you to back away from family functions?

Britain lost its dominant place in the world decades ago. The only people who haven’t come to terms with that reality are the British themselves, plus Anglophiles in America who read Churchill biographies instead of grappling with the country’s present-day quagmire. Brexit was the last, great hope for a Britain that could escape the mollycoddling of Europe and strive for its own success. But that movement assumed that the British were ready to step up to the demands of global competition — Chinese working hours, Korean industrial prowess, and Taiwanese tenacity. The British never stood a chance.

It’s twilight for a country that was once the beacon of scientific and human progress. Newton, Cavendish, Darwin, Turing, Crick & Watson — the very fundamentals of fields like physics, chemistry, biology and computer science were invented across that dour land.

But that was then and now, here we are. The water is sewage, the apartments are a fire hazard, the physicians are on strike, the trains can’t go from there to, well, there. From the pinnacle of the imperial center to whatever peripheral malaise we are witnessing. The story of today’s Britain serves as a warning: here’s what happens when you don’t meet reality head on. The land of David Hume failed to find Enlightenment, to find truth. And now it tries to live in the falsehood that it’s still relevant in a century of great power conflict.

Thank heavens we left the United Kingdom. Can you even imagine if we hadn’t?

Video Podcast: Fertility Rules from wildfire sperm death and microplastics to the potential of AI with investor Leslie Schrock

The birds and the bees just don’t cut it anymore. With the rising age of first pregnancies in America, optimizing fertility has become the linchpin for potential parents embarking on the journey to childbearing. Even so, we remain beholden to dozens of myths driven by inadequate science, even while we ignore the vast new potential — and limits — of a bountiful set of advanced technologies that aim to make fertility a more understandable and approachable subject.

In our very first video “Securities” podcast, I was joined by Leslie Schrock, venture investor alonside Lux portfolio companies like Gameto and Alife Health as well as the author of the new book “Fertility Rules: The Definitive Guide to Male and Female Reproductive Health”. We discuss the complex intricacies of the new science of fertility and why we have so much more to do to bridge the gap between expert knowledge and popular understanding.

🔊 Listen to the podcast

🎬 Watch the podcast on YouTube

Lux Recommends

First up, a side project from our summer associate Siddharth Sharma: CambrianGPT allows you to run a semantic search across hundreds of thousands of machine learning and Arxiv papers. You can then chat with the search in order to, say, summarize a paper you’ve discovered or ask for similar papers. Amazing.
A sad day in the engineering writer community. Henry Petroski, the prolific civil engineer who published books on the engineering marvels of the pencil, the toothpick, major failures as well as wider looks at the meaning of engineering as a discipline itself, passed away last month. The New York Times has an obituary about his life’s work and mission.
With all the excitement around Meta’s new social media app Threads, one of my favorite critics, John Herrman, offers a concise depiction of the media industry's disintegration this year. He dubs next year’s presidential election as the first U.S. election without a “minimal viable media,” a concept that resonates with me.
Our summer associate Reha Mathur offers a new Nature study which indicates that responding to a survey question with “Do not know” may actually be correlated with underlying genetic factors. If so, it has important implications for population-wide biases in social science research.
It can’t be July 4th without Nathan’s Famous International Hot Dog Eating Contest and its champion of the century, Joey Chestnut. Peter Hébert points to Carson TerBush’s article in the Washington Post on how training for the event — like so many athletic competitions — has gone from amateur to professional. "The ‘belt of fat’ theory popularized by Major League Eating, the sport’s organizing body, claims that heavier competitors have a restrictive layer of fatty tissue that limits stomach expansion. Top eaters, rather, said they aim to stay fit leading up to a competition to maximize energy levels.”
Shaq Vayda enjoyed Ben Evans’s sobering analysis of the generative AI revolution. “There’s a huge difference between an amazing demo of a transformative technology and something that a big complicated company holding other people’s business can use.”
Tess Van Stekelenburg enjoyed the 'aerial view on AI’ from Eric Schmidt’s article in the MIT Technology Review on “This is how AI will transform the way science gets done”. "AI can also spread the search net for hypotheses wider and narrow the net more quickly.”
Our summer associate Koko Xu recommends Paul Graham’s latest essay, “How to Do Great Work”. “Boldly chase outlier ideas, even if other people aren't interested in them — in fact, especially if they aren't. If you're excited about some possibility that everyone else ignores, and you have enough expertise to say precisely what they're all overlooking, that's as good a bet as you'll find.”
Our “Securities” summer associate Ken Bui points to two developments in industrial policy: China’s curbs on gallium and germanium as well as Japan’s take-private of a key domestic semiconductor company through a state orchestrated consortium fund.
Koko and another Lux summer associate Alex Markey both enjoyed “Bidirectional chargers explained - V2G vs V2H vs V2L,” describing the technical details and limits of how electric vehicles and the power grid interact with each other.
Finally, I enjoyed this Michael M. Phillips's article in the WSJ on how “The U.S. Funds Shadow Police Units All Over the World”. "The global spread of U.S.-vetted foreign police units is little known and faces little public scrutiny. Some Kenyans who do know of the units’ existence bridle at the notion that foreigners wield so much influence in domestic law enforcement.“

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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