Earthly Buzzkill - Lux Capital

Buzzfeed News and the final gasp of the media attention economy

Like everyone else who has been a reporter or editor in journalism, the demise of Buzzfeed News this week offers the next regular opportunity to analyze the state of media and the business of news. And what a state it is in! Three stories this week exemplify where we sit today:

First, Buzzfeed News, whose Pulitzer seriousness was always overshadowed by the inane content that blanketed the rest of the Buzzfeed multiverse, has vanished. Journalism jobs have been axed in repeated waves this week (in fact, Buzzfeed’s announcement actually overshadowed Insider’s own 10% layoff). Then again, those layoff waves have happened repeatedly the past year, the past five years and really the past decades.

Second, there was the Fox Corporation-Dominion Voting Systems lawsuit, where Fox offered Dominion $787.5 million to settle defamation claims that the company’s Fox News channel repeated fraudulent claims about Dominion and America’s 2020 election.

Third, the Wall Street Journal reported this week via theCommittee to Protect Journalists (CPJ) that “There were 363 journalists detained in more than 30 countries last year, with the highest number of detainees held in Iran, China and Myanmar”. That number includes the WSJ’s own Evan Gershkovich in Russia, who was declared unlawfully detained by the U.S. government last week. The CPJ earlier this year estimated that 67 journalists were killed globally in 2022.

It’s not so much a Buzzfeed but a buzzkill in media these days, as most days.

Even as the industry has transitioned away from the attention-driven models of last decade’s digital media economy, there have been huge bumps in the path to the supposedly new world. Substack, which has somehow become everyone’s favorite newsletter platform, crowdfunded itself, which forced it to disclose partial financial results. Far from ushering in a new dawn of subscription-driven media, Substack actually had negative revenue in 2021 due to paying out more incentives to writers than those writers brought in as income. The “new economic engine for culture” seems to be just as much of a mirage as the old economic engine.

More journalists are getting killed today, and yet, readers are ever less willing to pay for their work. And that is peculiarly logical — the people doing the killings, the narcos and dictatorships, they’re in countries uninteresting to most American or Western readers. Mexico is particularly dangerous as a reporter — some 15 were killed in 2022 alone, and 151 since 1992. But how many Americans (and for that matter, how many Mexicans) actually want news from beyond the southern border?

As I wrote back in “Unblissful Ignorance”:

But insulation from the news is a form of deep privilege, an indication that financial resources can solve any arriving problems and that the savageries of life can be held at bay. News is ultimately a necessity to all but the lucky few. Think of the young men of Russia who received news that they would be imminently drafted into Vladimir Putin’s war and had mere hours to run before the government started banning their travel by plane and over land. Hope you had push notifications on.

The most successful news media tends to be the financial press, which both covers a high wealth demographic and is also critical for professional success. More broadly, trade publications tend toward better success, covering intricacies in industries that most non-practitioners have never heard of. Most of us (or at least, more of us) are willing to shell out money for our own advancement, for there is clearly a profit to be gained in our informational advantage.

What happens though when it is society we want to better? Who pays?

What’s never been reconciled in the discussion of journalism and society is that while there are a litany of (often valid) complaints about the profession of reporting, the ultimate job that a journalist does — to seek out original, well-sourced stories that offer distant readers a light on what’s happening in the world — must actually exist. All of us get our information from someone else, it’s just a question of quality. The specialization required to understand the world today is beyond the ken of any mortal, and someone, somewhere has to play the role of interpreter between a well-informed reader and an abstruse expert, or government records sitting in a dark hallway, or an informant whose trust needs to be earned to release secrets that deserve spreading.

Unlike most active areas of science, the question of news economics requires no invention and really no analysis. It’s ultimately about whether people will pay for information relevant to them. There are positive externalities to a free press in an open democracy. Do citizens independently but in droves come to the decision that it’s worth funding those positive externalities?

It’s getting harder to do so, since finding consensus is so elusive. Journalism could be — and should be — a profession of building new consensuses through reporting. It should be enlightening, and it should change minds because minds in a democracy should be malleable to new ideas and approaches to pursuing the best life. Journalism in its best rendition should be the consensus function I talked about in … “Consensus Functions”:

Society, meanwhile, doesn’t have all those layers of consensus to build upon for new decisions. There’s no algorithmic blockchain ensuring that the basic facts of reality are cross-validated, or the scientific method to ensure that evidence is considered with appropriate context. Consensus is recursive, and without better consensus functions around values and tradeoffs, it’s impossible for a nation to make decisions.

Buzzfeed’s burning pyre is a reminder that all the feverish attention experiments to get around the hard truth of news economics have failed. A new economic engine of culture needs a new culture of economics, one that sees the value of the work being produced and a wide agreement that a quality consensus function for society deserves funding.

Earth Day as Growth Day

Today is Earth Day, a celebration of the verdant blue dot that provides sustenance and enjoyment to all of us. It’s also a day that I like to think of as Growth Day, in the sense that with 8 billion people today trending toward 11 billion or so people by 2100, we likely need to triple global GDP this century while also creating several billion high-quality jobs across the continents in order to offer every person on Earth a decent livelihood and life.

Growth is a dirty word in environmental circles these days, with small-scale degrowth initiatives turning into wide-scale socialist movements. The idea is to extinguish capitalism’s obsession with growth for growth’s sake with alternative models of public distribution. Enough is enough’s sake, you could say.

But growth is intrinsic to nature just as much as it is to capitalism. Trees expand their canopies to the furthest extent that the soil’s nutrients and the sun’s rays will allow. Animals grow in size until they have assumed their ideal physical forms, and those animals will collectively give birth until the territory they inhabit can’t sustain any further beings. Growth is the motive force of the natural world, just as it is for capitalism.

Of course, nature’s beauty is also brutal. Species prey on each other, limiting unchecked growth of any group outside of Homo sapiens. Climate shifts before the Anthropocene eliminated entire species who couldn’t readily adapt. When species gave birth to too many kin, nature has a way of just letting the weakest suffer.

The complex contradiction for humanity this century is how to grow and even accelerate growth without (further) triggering nature’s brutal responses. And triggering them we are, given that we are now expected to reach critical heating thresholds by the end of the decade (a topic I last discussed in “Warming Hyperthreat”). Just this week came news that Europe’s glaciers have receded by record amounts in 2022. From the Wall Street Journal:

The World Meteorological Organization, a scientific arm of the United Nations, said Friday that glaciers across Europe shrank from a combination of little winter snow and heat waves between May and September. In addition, dust blown from the Sahara in March 2022 landed on the snow, absorbing the sun’s rays and increasing the amount of melting, the report said. “Europe actually got hit hard both ways last year,” said Blair Trewin, a climate scientist at the WMO and an author of the new report. “They had an unusually dry winter, which meant that you didn’t have as much snow accumulating at high elevations as you normally would. But then they had a very hot summer as well.”

Going back to “Consensus Functions” from before, the next paragraph in my text was the following:

America and much of the West escaped that lack of deep consensus simply through abundance. Multiple values and tradeoffs could be supported by building institutions that allowed them all to coexist. Venture funds can’t make every investment and scientists can’t accept every contradictory result, but wealthy nations can support a wide range of consensuses, each underwritten in parallel.

Growth and climate can co-exist, but it won’t be the infinite abundance where tradeoffs are immaterial. Growth will require balancing competing priorities within the limits of Earth’s grace to humanity. Those limits are fixed, but thankfully, scientific progress can change the calculus of them. Agricultural invention has allowed us to grow more food with less land, inputs and labor than ever before. Such productivity can be found and newly discovered all across the capitalist web of our economy.

We can’t march forward by walking backwards. We can’t provide for billions of new souls by degrowth. Earth is our collective home, and it deserves to be celebrated for the full bounty it offers each of us. It’s time to find the productivity to make it everlasting and extend that bounty to everyone here and coming as soon as possible.

Lux Recommends

Peter Hébert throws the dice on a particularly fascinating caper from Kit Chellel in Bloomberg Businessweek in “The Gambler Who Beat Roulette.” Roulette is supposed to be impossible to beat, but not if you can estimate the physics in real-time while standing next to the table. “The Mirror reported that an unidentified high-tech gang had hit the casino with a ‘laser scam,’ pairing a device hidden in a mobile phone with a microcomputer to achieve the impossible. It was as good a theory as any. But closer observers weren’t so sure, and the case remained a mystery even to casino insiders almost two decades later. ‘We still lose sleep over that one,’ a gambling executive told me.”
Sam Arbesman recommends venerable Japanese novelist Haruki Murakami’s memoir-cum-how-to-guide Novelist as a Vocation, describing what he dubs the “mental chest of drawers” that writers need to imagine fictitious worlds.
Grace Isford has been swimming through the cutting edge of AI research, and she recommends a new paper from Wei Ping, principal research scientist at Nvidia, and a group of researchers entitled Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study. The answer is yes, retrieval methods enhance performance of AI language models.
I recommend recent “Securities” podcast guest Eliot Peper’s new speculative short story “Victory Condition”. In his own words, “I thought about what a city means, and what it means for a city to grow and change and become a better version of itself, always on the brink of something new. That’s what Victory Condition is about: reinventing the Bay Area.”
While we are on the subject of speculative stories, the Japanese animated film Suzume directed by Makoto Shinkai is an incredible tale of humanity’s response to catastrophe. Fantastical, moving, and a visual blast of fresh air — it’s made huge waves in Japan and is currently in reasonably wide release in the U.S. The IMAX experience was particularly breathtaking.
Sam enjoyed UNIX founder Brian Kernighan’s personal reflection, Unix: A History and a Memoir. UNIX transformed from a side project at Bell Labs into the basis for Linux servers and Apple’s iOS and macOS, underpinning a huge number of our devices today.
Finally, I recommend a short Bloomberg look at Brazil-China relations and how Brazil is pivoting away from the U.S.. The Western Hemisphere may well be the most contested geography in the decades ahead.

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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April 15, 2023

Forecasting Futureforming

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April 29, 2023

Miami Moments

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