Image Credits: Edward Caldwell via Stanford University
Donating to elemental power
There’s just an incredible number of big news stories this week, and I am going to get to some of them. But I don’t want to overlook one of the most distinguished stories that sort of wafted past the attention of most of us as the markets vigorously gyrated this week.
John Doerr, the legendary head of Kleiner Perkins Caufield & Byers (now just Kleiner Perkins) whose investments in Amazon and Google made him one of the greatest VC investors of all time (a tale you can read extensively about in Sebastian Mallaby’s The Power Law by the way), announced a $1.1 billion dollar donation to Stanford University for a new School of Sustainability, which will be named after him and his wife.
Why the massive donation? In an interview with the New York Times, he said that “Climate and sustainability is going to be the new computer science [… and] this is what the young people want to work on with their lives, for all the right reasons.” It’s the second-largest donation to a university ever.
Across interviews and the university’s own press, the new school will cover an extensive amount of ground, aggregating many of Stanford’s disparate centers and institutes around climate and resilience under one strong banner. But as Josh Wolfe pointed out on Twitter though, what was notable was the lack of any mention of nuclear power as part of the program:
Now, it’s a bit of a jab at a massive and massively positive announcement. But the active discussion of nuclear in the context of any climate change conversation is a useful litmus test for how serious the discussants are about solving the looming death of our planet.
Nuclear is a topic we have discussed a few times before in Fission today, fusion tomorrow and briefly in The Manichaean rainbow. We’re obviously pro-nuclear or as Josh calls it, pro-elemental power. Yet, it’s not just a position statement: nuclear energy is a critical ingredient in the fight against climate change that can’t be ignored. As Bill Gates writes in his book How to Avoid a Climate Disaster from last year:
Here’s the one-sentence case for nuclear power: It’s the only carbon-free energy source that can reliably deliver power day and night, through every season, almost anywhere on earth, that has been proven to work on a large scale. No other clean energy source even comes close to what nuclear already provides today. […] And it’s hard to foresee a future where we decarbonize our power grid affordably without using more nuclear power.
Stanford isn’t a bastion of nuclear research compared to MIT and Berkeley across the bay, which can take advantage of some of the work of the nearby Lawrence Berkeley National Laboratory. But that’s all the more reason to ensure that this line of research isn’t ignored, but rather expanded. For the initial publicity, it’s a missed opportunity. If it’s forgotten entirely, it’d be a tragedy.
Podcast: WashU CIO Scott Wilson on LP strategies at a time of great macro turbulence
Speaking of the university / venture capital nexus, this week we published a deep dive discussion with Scott Wilson, the chief investment officer of Washington University in St. Louis, on the “Securities” podcast. Wilson joined WashU in 2017 and quickly shook things up: he redeemed $3.6 billion in assets in his first week on the job and jettisoned 36 of the 37 hedge fund managers the endowment had at the time (and ultimately dropped the last manager as well). The changes speak for themselves: WashU announced a 65% return last year on its managed assets, and the school announced that it will offer need-blind undergraduate admissions for the first time.
Wilson is joined by our very own Josh Wolfe and Alex Nguyen, and the trio discuss his origin story in rural Alaska, his migration to Wall Street during the heady days of the 1990s, what he learned at Grinnell College’s endowment and how he rebuilt the WashU asset management philosophy, direct investing alongside GPs, the current global macro environment, what his LP nightmare is, his approach to the crypto and healthcare industries, and finally to top it all off, some book and cultural recommendations. All in about 35 minutes thanks to our producer Chris Gates’s amazing editing.
Returning to the theme of climate change, this Wall Street Journal story titled “The Most-Hated Solar Company in America” has to be one of the most fascinating I have read in the past few weeks. Auxin Solar, a tiny panel manufacturer in San Jose, requested that the Commerce Department investigate its industry to evaluate whether Chinese panel manufacturers are evading American tariffs by repositioning parts of their manufacturing chains to Southeast Asia. The result has been chaos in the industry:
Power companies such as NextEra Energy Inc. and Xcel Energy Inc. said many of their solar projects are facing monthslong delays. The Solar Energy Industries Association, a U.S. trade group, warned that what it called the “Auxin tariff” could lower projected solar deployment by 48% this year.
While not discussed extensively in the story, the use of Commerce Department investigatory and regulatory powers through agencies like the Bureau of Industry and Security has been considerably expanded during the Trump administration and into the Biden administration as a way to crack down on China’s manufacturing and tech sectors. Now, the costs of those actions are starting to be realized, with this administration’s own investigation now blocking its own climate policy.
Abortion and a tale of two countries
One of my earliest “Securities” newsletters was called “American Civil War 2.0” and focused on a book by Stephen Marche that looked at social and political fractures in the United States and what could trigger a breakdown of the state. Ever since Supreme Court oral arguments were delivered on December 1 last year in Dobbs v. Jackson Women’s Health Organization, I have been reminding my partners here that the looming decision on abortion could be one of the largest exogenous macro factors affecting American markets this year.
Well, I never could have predicted just how much destruction a key U.S. institution would experience.
The leak of justice Samuel Alito’s draft opinion this past week was astonishing both for its gall and for its sheer rarity. And even if the final opinion is significantly less odious than the draft opinion (which I actually predict since I believe the leak came from a conservative who is lambasting the court for ultimately neutering Alito’s caustic stance on abortion), the damage to one of the few remaining pillars of the American republic can’t be ignored. Without a court that is widely accepted as impartial and fair by the American public, the last branch of government Americans widely had any faith in anymore will have been demolished.
As for the draft abortion decision itself, Deena Shakir offered a constructive approach on how to move forward on the matter with some notes on Twitter:
Those physical security challenges can bleed right over to health security, with women often struggling to acquire the unique health services they need. In the United States, women can find it difficult to access a range of services from obstetrics and gynecology to the comprehensive help needed to fight breast and ovarian cancers. But even outside of these specific health services, women encounter significant barriers to accessing all healthcare services. Outside of wealthy nations, the quality of health care can decline dramatically, with acute declines for women who are often overlooked by public health systems.
There’s not going to be any improvement to women’s health by making a key procedure illegal in almost two dozen states and possibly more. The final opinion of the court will be delivered in the next few weeks — it may well not just affect the fate of women and the men who support them, but also the wider sense that America can stand together as an undivided commonwealth.
Scrutinizing telehealth services
Speaking about access to healthcare, this week also saw the culmination of wide-scale concerns around some ADHD and other mental healthcare startups who have been accused of over-prescribing drugs like Vyvanse and Adderall. Cerebral and Truepill are among the companies that have halted their prescriptions for certain drugs in response.
Telehealth has been a lifeline for many patients in the Covid-19 era, who are far more comfortable — and safe — in receiving care virtually than going to an in-person clinic. However, that virtual element can quickly attract the wrong kind of growth hacking, and in the health world, that sort of growth mentality can cause serious harm.
Lux has been very interested in telehealth services for a while, and we have backed a portfolio of startups here. The truth though is that the hardest part of investing in this market is choosing the companies that place health integrity and patient lives first, often over immediate growth (Deena posted some thoughts on this subject). We believe in the long run that the winners in healthcare will always be those who earn the trust of patients and physicians, and that has meant that we have had to pass on a myriad of hot telehealth startups that see health just as another software industry waiting to be disrupted.
Expect more scrutiny by regulators of the most aggressive startups, and more attention from investors on the companies who are quiet but quality in the year ahead.
The thinning NFT market
Finally, I’d be remiss to fail to acknowledge the massive collapse in trade volumes going on in the NFT world. The Wall Street Journal notes that “The number of active wallets in the NFT market fell 88% to about 14,000 last week from a high of 119,000 in November.”
We’ve always been long crypto infrastructure here with Grace Isford and Brandon Reeves driving our strategy, and so we are pretty distant from the expensive buying of pixels that has electrified the crypto community the past year. Nonetheless, the rapid decompression of the NFT market is astonishing both for its scale and speed.
I wish I had more to say on the matter, but I actually think this is one of those market stories that will take several years to process and an author will come along with a great book on the fundamental forces that really drove the craze.
Lux Recommends
Will McCreadie recommends Bartosz Ciechanowski’s extensively animated and illustrated guide to the workings of mechanical watches. A delightful look at the human ingenuity that’s packed into a couple of millimeters of metal on our wrists.
Sam Arbesman recommends Wired founding executive editor Kevin Kelly’s 103 Bits of Advice I Wish I Had Known. My favorite: “Actual great opportunities do not have ‘Great Opportunities’ in the subject line.”
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.”