While Google nailed the switch from R&D to deployment, it arguably still bet big on scaling up the wrong technology. In the early 2010s, the solar race looked like a tight competition between solar photovoltaic (PV) and utility-scale concentrated solar power (CSP), which uses sun-heated fluids to drive power turbines. Google quickly invested more than $1 billion in a slew of renewables companies and utilities, including big investments in CSP outfits BrightSource Energy and eSolar. A decade later, such choices aren’t looking promising, as CSP, too, has been losing out to PV’s continuing rapid cost declines.
Google is not alone in repeatedly misjudging the dropping price of solar cells over the last few decades and its impact on how we think about clean energy. Solar PV costs fell roughly by a factor of 10 in the past decade, on top of already impressive cost declines up to that point, for a total decline of around a factor of a hundred since US President Jimmy Carter unveiled solar panels on the White House in 1979. (Ronald Reagan took them down in 1986, during his second term as president.)
To put it in perspective, if gasoline had similarly dropped in price from 1979 levels, it would cost pennies a gallon today. Gasoline, of course, is a commodity, with prices fluctuating for a number of technological, economic, and political reasons. Solar PV prices are also driven by all these factors, but over the years, technology has clearly dominated. (This year, prices for solar PV modules have increased by around 18% because of a temporary crunch in the silicon supply chain.)
In its latest annual World Energy Outlook, the International Energy Agency declared solar PV to be “the cheapest source of electricity in history” for sunny locales with a low cost of financing. These two qualifications are important. Sun is obvious—solar is always going to be cheaper in Phoenix, Arizona, than in New York City—but the report concluded that solar is now cheaper than coal and natural gas in many places.
Financing is key to why this is true. Solar PV and other renewables such as wind have low or close-to-zero operating expenses—upfront costs have always been the big hurdle, and financing has been a big reason why. Thanks in part to various government policies, solar investment has become much less risky over the last decade or so, freeing up cheap money.
As a result, solar PV deployment has increased rapidly; it’s now the fastest-growing source of electricity globally, and figures to be for some time to come. It’s starting from a low base of installed capacity, however, far behind coal, gas, hydro, nuclear—even wind, which has been cheap for longer. And therein lies one of the biggest problems for solar PV. It might be the cheapest form of electricity for many, but that on its own doesn’t make the clean-energy transition nearly quick enough.
We need ever further technological advances. Why stop at grid parity, the point where it’s as cheap to build and operate solar PV as to supply electricity via fossil energy sources? Why not 10% cheaper? Why not strive to slash costs by another factor of 10 within a decade? Such drops are needed because the hallowed grid-parity goal is misleading—the real question is at what point utilities will actually abandon existing coal plants and switch to solar, rather than merely avoid adding new coal capacity. Solar needs to be so cheap it makes financial sense to build new solar capacity and shutter working coal and gas plants still making money for their owners.
All that calls for policy to both push existing solar technology and support R&D in new technologies. The entire package includes technology research, development, demonstration, deployment, and diffusion. Every step along this chain deserves direct government support, keeping in mind that it also gets increasingly more expensive the further down the chain one moves.
How to get cheaper
To better optimize investments to get to even cheaper solar, it’s worthwhile to understand what factors have driven down the cost of renewable power over the last few decades.
MIT energy systems scientist Jessika Trancik and her group find that the dramatic cost declines in solar cells over the course of three decades can largely be attributed to three factors: R&D leading directly to improvements in module efficiency (how much of the sunlight is converted into electricity) and other fundamental technological advances; economies of scale attributed to the size of solar-cell manufacturing plants and the increasing volume of inputs such as silicon; and improvements achieved through learning by doing.
None of that is too surprising, but what is less obvious is that the relative contribution of each varies greatly over time. From 1980 to 2000, R&D accounted for around 60% of cost declines, with economies of scale coming in at 20%, and learning by doing a distant third at around 5%; other largely unattributable factors account for the balance. That makes sense; it was a period of impressive advances in the efficiencies of solar cells but not a time of significant manufacturing and deployment. Since then, the pendulum has swung from R&D and fundamental technological improvements toward economies of scale in manufacturing, now accounting for over 40% of cost declines. It’s worth noting, however, that research advances still account for some 40% of declines.
The lesson for future investments that aim to make solar even cheaper: there should be direct support for all three, skewed toward economies-of-scale factors. Trancik’s findings only consider the solar PV module itself. That still leaves installation, connection to the grid, and other factors that make up total system costs. These are areas that will likely be improved as technicians and companies become more experienced. While the results of subsidies for increasing solar PV installations appear to be mixed at best, policies such as feed-in tariffs, which offer favorable long-term contracts to solar PV producers, and renewable portfolio or clean energy standards, which set quantity targets for renewables, show clear results in driving overall deployment.
No free lunch
Despite the dropping price of solar, the transition to renewables will still be costly. The big question, of course, is how expensive compared with what—climate change, too, comes with costs. Cheap solar gets even more financially attractive to developers if the social and environmental costs of carbon emissions from fossil fuels are considered.
A lot here hinges on the social cost of carbon (SCC), a tally of the financial damage each metric ton of carbon dioxide emitted today causes to the economy, society, and the environment—and, by extension, how much each ton of CO2 emitted should cost. It’s a number that says a lot about the true cost of coal and other fossil fuels—and about the appropriate support for solar PV and other renewables.
This startup’s AI is smart enough to drive different types of vehicles
Jay Gierak at Ghost, which is based in Mountain View, California, is impressed by Wayve’s demonstrations and agrees with the company’s overall viewpoint. “The robotics approach is not the right way to do this,” says Gierak.
But he’s not sold on Wayve’s total commitment to deep learning. Instead of a single large model, Ghost trains many hundreds of smaller models, each with a specialism. It then hand codes simple rules that tell the self-driving system which models to use in which situations. (Ghost’s approach is similar to that taken by another AV2.0 firm, Autobrains, based in Israel. But Autobrains uses yet another layer of neural networks to learn the rules.)
According to Volkmar Uhlig, Ghost’s co-founder and CTO, splitting the AI into many smaller pieces, each with specific functions, makes it easier to establish that an autonomous vehicle is safe. “At some point, something will happen,” he says. “And a judge will ask you to point to the code that says: ‘If there’s a person in front of you, you have to brake.’ That piece of code needs to exist.” The code can still be learned, but in a large model like Wayve’s it would be hard to find, says Uhlig.
Still, the two companies are chasing complementary goals: Ghost wants to make consumer vehicles that can drive themselves on freeways; Wayve wants to be the first company to put driverless cars in 100 cities. Wayve is now working with UK grocery giants Asda and Ocado, collecting data from their urban delivery vehicles.
Yet, by many measures, both firms are far behind the market leaders. Cruise and Waymo have racked up hundreds of hours of driving without a human in their cars and already offer robotaxi services to the public in a small number of locations.
“I don’t want to diminish the scale of the challenge ahead of us,” says Hawke. “The AV industry teaches you humility.”
Russia’s battle to convince people to join its war is being waged on Telegram
Just minutes after Putin announced conscription, the administrators of the anti-Kremlin Rospartizan group announced its own “mobilization,” gearing up its supporters to bomb military enlistment officers and the Ministry of Defense with Molotov cocktails. “Ordinary Russians are invited to die for nothing in a foreign land,” they wrote. “Agitate, incite, spread the truth, but do not be the ones who legitimize the Russian government.”
The Rospartizan Telegram group—which has more than 28,000 subscribers—has posted photos and videos purporting to show early action against the military mobilization, including burned-out offices and broken windows at local government buildings.
Other Telegram channels are offering citizens opportunities for less direct, though far more self-interested, action—namely, how to flee the country even as the government has instituted a nationwide ban on selling plane tickets to men aged 18 to 65. Groups advising Russians on how to escape into neighboring countries sprung up almost as soon as Putin finished talking, and some groups already on the platform adjusted their message.
One group, which offers advice and tips on how to cross from Russia to Georgia, is rapidly closing in on 100,000 members. The group dates back to at least November 2020, according to previously pinned messages; since then, it has offered information for potential travelers about how to book spots on minibuses crossing the border and how to travel with pets.
After Putin’s declaration, the channel was co-opted by young men giving supposed firsthand accounts of crossing the border this week. Users are sharing their age, when and where they crossed the border, and what resistance they encountered from border guards, if any.
For those who haven’t decided to escape Russia, there are still other messages about how to duck army call-ups. Another channel, set up shortly after Putin’s conscription drive, crowdsources information about where police and other authorities in Moscow are signing up men of military age. It gained 52,000 subscribers in just two days, and they are keeping track of photos, videos, and maps showing where people are being handed conscription orders. The group is one of many: another Moscow-based Telegram channel doing the same thing has more than 115,000 subscribers. Half that audience joined in 18 hours overnight on September 22.
“You will not see many calls or advice on established media on how to avoid mobilization,” says Golovchenko. “You will see this on Telegram.”
The Kremlin is trying hard to gain supremacy on Telegram because of its current position as a rich seam of subterfuge for those opposed to Putin and his regime, Golovchenko adds. “What is at stake is the extent to which Telegram can amplify the idea that war is now part of Russia’s everyday life,” he says. “If Russians begin to realize their neighbors and friends and fathers are being killed en masse, that will be crucial.”
The Download: YouTube’s deadly crafts, and DeepMind’s new chatbot
Ann Reardon is probably the last person whose content you’d expect to be banned from YouTube. A former Australian youth worker and a mother of three, she’s been teaching millions of loyal subscribers how to bake since 2011. But the removal email was referring to a video that was not Reardon’s typical sugar-paste fare.
Since 2018, Reardon has used her platform to warn viewers about dangerous new “craft hacks” that are sweeping YouTube, tackling unsafe activities such as poaching eggs in a microwave, bleaching strawberries, and using a Coke can and a flame to pop popcorn.
The most serious is “fractal wood burning”, which involves shooting a high-voltage electrical current across dampened wood to burn a twisting, turning branch-like pattern in its surface. The practice has killed at least 33 people since 2016.
On this occasion, Reardon had been caught up in the inconsistent and messy moderation policies that have long plagued the platform and in doing so, exposed a failing in the system: How can a warning about harmful hacks be deemed dangerous when the hack videos themselves are not? Read the full story.
DeepMind’s new chatbot uses Google searches plus humans to give better answers
The news: The trick to making a good AI-powered chatbot might be to have humans tell it how to behave—and force the model to back up its claims using the internet, according to a new paper by Alphabet-owned AI lab DeepMind.
How it works: The chatbot, named Sparrow, is trained on DeepMind’s large language model Chinchilla. It’s designed to talk with humans and answer questions, using a live Google search or information to inform those answers. Based on how useful people find those answers, it’s then trained using a reinforcement learning algorithm, which learns by trial and error to achieve a specific objective. Read the full story.
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