Lab-grown Babies - Lux Capital

For womb does the bell toll?

If we have lab-grown meats and lab-grown leathers, why shouldn’t we have lab-grown children?

That was the proposition of Aike Ho, an investor at ACME Capital, who joined a great Twitter Space discussion on the future of the family and technology this week hosted by our own Deena Shakir and Sahil Lavingia, the founder of Gumroad and angel investor.

How did we get to disrupting human-born humans and debating the intricacies and likelihood of lab-grown children? Well, welcome to Twitter in 2022.

Population growth is stalling across much of the Western world and East Asia. In China, briths fell to 10.6 million in 2021 compared to 12 million in 2020 based on new census data released by Beijing. With deaths estimated at 10.1 million, China is nearing a demographic peak. Across the sea, South Korea reported a net decline in population for the first time in its modern history, with its 2021 population dropping by 91,000, or roughly 0.18%.

Meanwhile in the United States, the Census Bureau noted that “The U.S. population grew at a slower rate in 2021 than in any other year since the founding of the nation,” caused by a rapid decline in birth rates as well as Covid-19 travel restrictions that have slowed immigration.

The reversal of decades of fast population growth has stunned demographers and also Elon Musk, who tweeted his concerns:

https://twitter.com/elonmusk/status/1483486559336910850?s=21

I must admit that my list of human concerns tend to the terrestrial than martian, or as one VC might put it, the future population of Mars is “below my line.” Nonetheless, Musk’s tweet led to wide discussions about whether and how tech might solve the crisis of the family. Lavingia replied to Musk which prompted … let’s call it a conversation that led to this week’s Twitter Space.

We had nine speakers, so it was a bounty of thought about the future of children, pregnancy, fertility, child care, and global population growth.

Dina Radenkovic of Lux-backed ovarian aging startup Gameto pointed out that women constantly have to make tradeoffs between career and family, and artificial wombs could remove not just physical barriers to pregnancy, but also give families much more flexibility to choose when to have kids.

Now, artificial wombs might sound like science fiction, mostly because they are. But Leslie Schrock, author of a book on pregnancy titled Bumpin’, noted that the end goal might not even be an artificial womb anyway. New tech “could take question marks away from women who have children,” she said, arguing that we still don’t know everything we need to when it comes to pregnancy and embryonic development. An artificial womb moonshot could blaze a trail of knowledge that’s ultimately more useful for human-grown humans.

Moonshots are enrapturing, but it’s often the daily concerns of women that most affect birth rates. Sara Mauskopf, CEO and co-founder of child-care startup Winnie, emphasized repeatedly that much of the problem was driven by lack of access to child care and other systems of support that can help mothers in the postpartum period. I might dub it “child inflation,” but the costs to have a child are increasingly burdening families up and down the income scale, and more families are choosing to settle for less kids or no kids at all to compensate. Elana Berkowitz, founding partner of Springbank Collective, noted that 44% of births are Medicaid eligible.

Alyssa Jaffee, a partner at 7wireVentures, made the argument that birth rates are decreasing for an even more simple reason: lack of information. From fertility options to child care, schooling and everything in between, moms rely on informal social networks to glean what’s best for their situation, without organized societal support to ensure that there is comprehensive counseling as issues arise. Parents are more aware of the risks around all aspects of family than ever before, but they lack the tools to mitigate those, and that can delay decisions that might otherwise be made.

In short, what seems like a crisis that requires a single moonshot invention actually is composed of dozens of intricately connected problems, each that have their own tech and policy solutions. That’s why Lux has backed companies across the family lifecycle, from securing birth control (Adyn) and reducing ovarian aging (Gameto) to using AI to improve in vitro fertilization (Alife Health) and delivering women’s virtual care (Maven Clinic).

But ultimately, the most Luxian investment would be artificial wombs (a category we have explored before), but how likely are lab-grown babies? I heard a mix of views on the panel when Deena asked, including that they will be the norm by 2050 (a mere three decades away). While fantastical today, we’ve seen incredible advances in previously unfathomable medtech, including the first xenotransplantation, which we covered last week in the newsletter (and which there have since been even more developments). That said, the consensus was that artificial wombs are still very far out, so expect lab-grown meats well before your dry-aged lab-grown children.

Before we move on though, I do want to make one other point on the so-called demographic crisis. Population decline is causing serious consternation among global policymakers, particularly in China, where pro-natalist policies have been quickly enacted in the past year to aggressively ameliorate the country’s trajectory. The country’s notorious “one child” policy has been quite literally supplanted by a “three child” policy.

Far from decline as crisis, it’s growth that is causing a worldwide crisis. Earth’s population is expected to grow from about 7.8 billion to more than 10 billion by the end of the century, driven by the Middle East, Africa and Southeast Asia. The very idea that we are running out of humans per Musk is laughable.

Far from worrying about sheer quantity of births, we must direct our attention to quality — how do we improve human development globally to ensure that every birth, mother and family gets the support and resources they need for stability and success. If the conversation this week had any overarching theme, it is that even the most basic care is unavailable to a majority of people on this planet — and even large swaths of the United States as well. This is a gargantuan problem — and one that deserves its own earthshot, if you will.

Speaking of going into labor…

For decades, there have been shrill claims that robots are going to seize all the jobs. That’s demonstrably false, but it is true that even more of the economy is going to be automated in the years ahead. While robotic technologies were once the barrier to adoption, the current challenge is bridging the gap between the upfront costs of a robot and the limited budgets of most businesses to buy them.

Lux announced a $26.5 million Series A into Formic led by Shahin Farshchi this week, and if you are curious about the increasing financialization of robotics and how that will pave the way for our new robot overlords, definitely check out my piece on “The robot revolution will be banked" as well as Will Knight's piece in Wired titled “Now You Can Rent a Robot Worker—for Less Than Paying a Human.” As I wrote:

So the next generation of robotics companies are learning from their predecessors and fixing finance first. The formula? Pay-as-you-go financing with limited to no upfront cost and economic models that are incentive aligned with customers based on realized workplace productivity.

Biotech’s blues and billions

Biotech has been Peloton’d the past year, in one of the longest downturns in the industry’s trading history. Using the SPDR S&P Biotech ETF (XBI) as a benchmark, the index closed at a record high of $173.99 on February 8, 2021. Today, just shy of a year later, it closed at $90.03, or down roughly 48.3% (Ok, so maybe it was half Peloton’d).

Biotech’s descent predates the broader market pullback seen in SaaS and software over the past few weeks, a new correlation that has only accelerated declines: in the past month, XBI lost about 25%.

It’s demoralizing at a time when biotech has really become a mainstream business concern gracing the front covers of major newspapers, but there are some important considerations.

First, today’s closing price was last seen in mid-April 2020. Investor ecstasy around biotech came in the immediate aftermath of Covid-19’s initial global spread, which sent biotech shares soaring on beliefs (rightfully held, for the most part) that there would be intense efforts to expand access and fund research in therapies and diagnostics both directly connected to the pandemic and also more broadly. In other words, we’re seeing a very short cycle in sentiment, one that isn’t erasing years worth of gains.

Second, unlike software stocks, which have seen a combination of revenue growth and persistent multiples expansion that has led to recent record prices before the pullback, biotech has always had far more market gyrations. That’s forced all investors (including our own Adam Goulburn and Zavain Dar) and company founders to focus on resilience during good times and bad, since there are always bad periods in biotech sentiment.

Finally, if you thought the pullback in bio is making investors more leery, think again. This week saw what was described as the largest biotech investment in history with the $3 billion funding announcement for Altos Labs, a fusion research and commercial organization designed to investigate “cell health and resilience” to “reverse disease.”

It’s a colossal bet not only on the potential for huge advances in cellular science this decade, but also that new models of organizing scientific innovation can lead to huge commercial outcomes. As our scientist-in-residence Sam Arbesman has talked about, it’s precisely these new models that are needed to propel the next-generation of scientific advances into our hands. Reorganizing science is a story that even garnered a story by Derek Thompson in The Atlantic this week highlighting Arc Institute, Arcadia Science and New Science.

Maybe you can escape the stock market in the metaverse

Finally in bigger notes, I enjoyed this piece by Ben Klemens in Wired on what his “hundreds” of hours of work experience in the metaverse might indicate about our future virtual workselves:

Rumor has it that some people use their VR headsets for games, but working from the vacuum of space has its thrills. Can I blindly feel around for the mug of tea on the table and bring it to my lips without knocking the whole thing onto my laptop? The stakes are high, and every successful sip is a victory. One day about three months after I started working from VR, my podcast cohost came by, so I had to jack out after several hours with this headset strapped to my face. My forehead was numb. She said, “You look like you’ve been punched in the face.” What fighting game can achieve this level of realism?

Etc.

Bilal Zuberi recommended this piece by The Economist on modern timber-construction methods. Huge advances have been made in wood-supported structures, including a 750-foot tall demonstration building underway in Chicago called the River Beech Tower. Further research and design work could rapidly change the construction-materials industry, particularly around reinforced concrete.
If you enjoy James Scott and his famous work Seeing Like a State, then you will hate this. “Indonesia names new capital that will replace Jakarta.” Indonesia doesn't have much choice: “Jakarta has become crowded, polluted and is sinking at an alarming rate due to the over-extraction of groundwater. Home to more than 10 million people, it sits on swampy land on the large island of Java.” Let's hope the outcome is better than Brasilia.
Sam Arbesman recommends “Where Aliens Could Be Watching Us” from Nautilus, describing the 1,700 stars that could witness life on Earth.
Joe Hicks offers an extensive deep dive into the financial death of a small town in “Why Galesburg Has No Money.” In short: spiraling infrastructure maintenance costs and declining tax revenues are crushing the town’s finances, and there is nothing but decline straight to the asymptote.
Finally, the mystery around Havana Syndrome continues: “Havana Syndrome Unlikely Caused by U.S. Foes, CIA Says.” This remains one of the most fascinating — and frightening — puzzles out there.

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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January 15, 2022

American Civil War 2.0

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January 29, 2022

Defense Fordism

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