Newsletter Archive
Listen to Our Podcast
Dear Aventine Readers,
Welcome to our first mid-month newsletter. In this issue we’re looking at quantum computing, an evolving method of computation that relies on subatomic particles like electrons and photons to perform calculations. Its proponents believe that it will one day regularly surpass the abilities of classical computing, an achievement that has been given the label, “quantum supremacy.” But this label has recently come under fire for reducing the potential value of quantum computing to a win/lose proposition that could put the field at risk. Five experts weigh in on how success in quantum computing should be measured.
Also in this issue: a better way to recycle used solar panels, a meltdown-proof nuclear reactor that could change the way we think about nuclear power and an emerging crop of low-tech solutions for energy storage that could fill in when and where batteries can’t.
Thanks for reading,
Danielle Mattoon
Executive Director, Aventine
Subscribe
Subscribe to our newsletter and be kept up to date on upcoming Aventine projects
Quantum Supremacy
When Google announced that it had achieved quantum supremacy in 2019, the headlines were thrilling.
The world of quantum computing had taken a remarkable step. Google, with its Sycamore quantum processor, had performed a calculation in 200 seconds that, the company claimed in the journal Nature, would take a supercomputer 10,000 years.
This feat, named quantum supremacy by John Preskill, a theoretical physicist, back in 2012, promised to usher in a new world of computing performance. It suggested that quantum computers could perform some very specific tasks — such as searching databases or modeling the behavior of atoms and molecules — with unprecedented speed, offering a tantalizing glimpse into a future in which the way we study chemistry, biology, material science, medicine and even finance would be turned on its head.
While classical computers are organized around 0s and 1s, called bits, quantum computing is organized around the properties of quantum particles such as electrons and photons, known as qubits. Qubits can take any value between 0 and 1 and — crucially — in a quantum computer made up of many qubits, all share that multiplicity of states. The aim of quantum computing software is to encourage qubits to interact in such a way that, collectively, they can perform calculations that a classical computer never could. Google’s ability to harness such power would have been transformative.
Only it didn’t play out the way Google hoped or expected.
The quantum supremacy announcement ended up descending into controversy. The problem: Even though the achievement of Google’s quantum computer was groundbreaking at the time, events proved that it is possible for researchers to come up with classical algorithms that can challenge and even surpass the success shown by a quantum device. Soon after the result was published, IBM — perhaps Google’s closest quantum computing rival — claimed that it was possible to build an algorithm that could perform the calculation in two and a half days or less on a classical computer. Three years later, researchers from the Chinese Academy of Sciences in Beijing achieved the feat on classical chips in just 15 hours — longer than the Sycamore chip, but nothing near 10,000 years. And then, earlier this summer, researchers from Shanghai Artificial Intelligence Laboratory in China completed the same task in just 14.22 seconds, driving a final stake through the heart of the Google quantum supremacy claim.
It’s not the only warning sign for the industry. Venture capital investment in the sector has fallen off a cliff, from $2.2 billion globally in 2022 to about $1.2 billion in 2023.
So quantum computing finds itself at somewhat of a crossroads. Have the decades of research, the billions of dollars of investment and the thousands of column inches written about the promise of quantum computing been worth it? Or is it just a matter of time before the industry starts seeing the kind of breakthroughs that could finally prove transformative? And finally, is comparing the abilities of a quantum computer to those of a classical computer the right way to evaluate its potential?
Five quantum computing researchers told Aventine they still believe that proving quantum computers are capable of more than regular computers is important. But they are split on whether “quantum supremacy” is the most accurate and useful way to describe the goals of this new kind of computer. Several researchers suggested that the phrase is mostly a tool for pitching quantum computers to the general public, who otherwise don’t understand what the computers’ value might be. And one researcher suggested that it might not be possible to achieve supremacy at all.
Those of us who do research in the subject have known from the very beginning that a quantum computer is only useful to the extent that it can beat a classical computer. The thing that makes it so exciting is that there are a few very special problems where we are confident that eventually a quantum computer will beat a classical computer. In some sense what we’ve been trying to do is get back to the scientific origins of the field. Is there any task where we can demonstrate that a quantum computer is going to beat the best that you can do with a classical computer? It doesn’t have to be a useful task, but you do have to do a fair comparison against classical.
Quantum supremacy can be achieved and then unachieved later. It’s a little bit of a moving target in that sense. But all expect that we’ll eventually get to a place where quantum computers are just routinely doing things that classical computers cannot replicate within thousands of years or millions of years, and at that point there’s no more arguing about it.”
— Scott Aaronson, chair of computer science at the University of Texas at Austin
Our way of communicating with the public is giving them sales pitches. One of the sales pitches, perhaps unfortunately named, was this quantum supremacy idea. The idea is really much less grandiose than the name would convey: Can a machine that we’ve built do something, anything, perhaps absolutely useless, but still better than the standard computers? It’s important to understand that this is a relatively modest question, phrased in this grandiose way.
Can we demonstrate that quantum computers could potentially be useful sometime in the future? That would buy us some time to make them better. I think I can speak for most of the scientists when I say, we all feel like we are constantly on borrowed time, so we are given a few years per idea, and then if that doesn’t work, either we fade away or need to come up with a completely different idea for what we might want to do.”
— Sergey Frolov, physics professor at the University of Pittsburgh
The term itself is something that different people use in different ways. These aren’t really scientifically very precise and defined terms, there’s a little bit of a marketing aspect to these terms that gets muddled up in the science.
It’s a low threshold, it’s just a benchmark designed to showcase the ability of a quantum computer to solve a very contrived problem.
The value is that it demonstrates the ability to maintain some kind of secret sauce, involving coherence and entanglement, which are truly quantum physics effects. When you’re doing the quantum supremacy experiment, you’re demonstrating the ability to maintain that magic over a large enough scale that you can do something that’s very hard for a classical computer.This is essentially like an experimental slash engineering feat to demonstrate that capability.”
— Joseph Emerson, associate professor at the University of Waterloo’s Institute of Quantum Computing
Quantum supremacy is important both in its own right and as a benchmark or step toward something further.
But my theory is that quantum supremacy cannot be achieved, and this is based on analysis of the stochastic behavior of samples coming from quantum computers in the intermediate scale.
It is a bit complicated, but if you take a quantum computer like the ones people build now all over the world, what they produce is a combination of something very sensitive to noise, which is useless for computation, and something stable to noise, which is a very primitive computational device. If you have this combination, you cannot achieve quantum supremacy. This is my theory.”
— Gil Kalai, a mathematician and computer scientist at Hebrew University
I’m a physicist, and I think for me there’s a somewhat different way of thinking about this, which is to say that what we are setting out to build are highly controllable quantum devices with a very high degree of control over how they can move in time. Quantum supremacy good enough for physics work would be that when this highly controllable quantum system is big enough that you just cannot predict its behavior in any reliable way using pen and paper or a classical computer, so that you have to deal with the device on its own terms, much as you deal with experimental systems.
That notion of quantum supremacy I personally find is the one that appeals to me, and absolutely a goal worth pursuing.”
— Shivaji Sondhi, physics professor at Princeton University
Listen To Our Podcast
Learn about the past, present and future of artificial intelligence on our latest podcast, Humans vs Machines with Gary Marcus.
Advances That Matter
A rendering of discarded solar panels, Killykoon/Adobe Stock
A better way to recycle old solar panels. At the industrial port of Marghera in Venice, there’s a shipping container with a grand ambition: to recycle the growing number of solar panels reaching the end of their working life each year. This tiny facility is a demonstration plant for 9-Tech, IEEE Spectrum reports, and it is using a variety of techniques to recover materials from crystalline silicon solar panels — which account for the vast majority of the global solar market — as completely, efficiently and greenly as possible so that they can be reused. Currently, dumping old solar panels in landfills is the cheapest and most commonly used option.There are approaches that recover 90 percent or more of a panel’s copper, silver, silicon, glass and aluminum, but they are expensive and use toxic chemicals. (By most reports only 10 percent of all solar panels are currently recycled this way.) As an alternative to this approach 9-Tech uses high temperatures, fume capture systems, high-intensity ultrasound, acid baths and other tricks to isolate and recover the various materials of the solar panels so that they can be repurposed. According to IEEE Spectrum, 9-Tech’s approach can recover 90 percent of the silver, 95 percent of the silicon and 99 percent or more of the copper and aluminum in highly pure forms, making the recovered materials excellent for reuse. The question is whether the approach can scale and be affordable. This will be tested in the next plant, which is being built over the coming 18 months, and will be capable of processing 800 solar modules a day compared to the current unit’s seven.
A meltdown-proof nuclear reactor. When a nuclear power plant’s reactor is left uncooled, it can get so hot that it reaches a point commonly referred to as meltdown — leading to catastrophic overheating or explosions that endanger or destroy the plant and its surroundings. Modern reactors avoid this with cooling systems, but their failure could lead to disaster. Now, in research published in the journal Joule, a new reactor design has been shown to cool down safely by itself without the need for any external cooling system. The system is based around a so-called pebble-bed reactor, which uses pebbles of uranium surrounded by graphite — rather than energy-dense rods of uranium — as the basis for the nuclear reactions. The pebble design makes it possible for the uranium to dissipate heat naturally, rather than requiring specialized cooling equipment. In an experiment where the full-scale demonstrator was switched off during full-power operation, the system cooled down naturally and safely over the course of 35 hours. This is the first time that a full-scale nuclear reactor has been shown to safely cool itself down, and suggests that it may be possible to build a new generation of fail-safe nuclear plants.
Physics and AI promise more efficient weather prediction. Most weather predictions over the past 50 years have been generated using so-called general circulation models that rely on complex physical equations to predict changes in the atmosphere. Those equations are highly accurate for long-term forecasts but require huge amounts of computational power, which makes them slow and expensive to run. On the other hand, modern AI-based weather prediction algorithms are highly efficient when trained on large amounts of data but struggle to predict long-term weather. Now Google has published research in Nature describing a new model called NeuralGCM which combines both approaches — using physics equations for macro trends and AI to provide smaller-scale predictions. Google researchers claim the results it produces are as accurate as 15-day forecasts from the European Centre for Medium-Range Weather Forecasts. But as MIT Technology Review reports, the true benefit of the advance may be felt in climate modeling, where it could allow easier, earlier prediction of cyclones, say, or help predict patterns that could be affected by climate change, like rainfall.
Magazine and Journal Articles Worthy of Your Time
Europe’s rushed attempt to set the rules for AI, from The Financial Times
2,500 words, or about 10 minutes
At the start of August, the European Union's landmark legislation around artificial intelligence swung into force. The AI Act, the first legislation of its kind, seeks to categorize AI systems by risk and gradually put in place rules around how they can be used. But as this story points out, the rise of generative AI models over the last two years, such as those on which ChatGPT are built, meant that large parts of the legislation needed to be reconsidered in a hurry. Some critics contend that the content of the legislation is now overly vague, lacking clear detail on issues such as intellectual property rights, and providing little detail on how companies should actually put the act’s laws into practice. As a result, there’s a sense in the tech community, especially among startups, that the legislation could cause confusion, create legal expenses and ultimately slow down innovation instead of bringing clarity to the way AI can and should be deployed.
Making fusion pay, from Science
3,100 words, or about 12 minutes
How do you fund a moonshot? For a company called SHINE Technologies, whose long-term vision is developing nuclear fusion as an energy source, the answer lies in monetizing the byproducts of innovation. Typically, nuclear fusion takes two forms of hydrogen — deuterium and tritium — and smashes them together to create helium and energetic neutrons. Those neutrons are where the immense energy potential of fusion lies — but they’re also useful in and of themselves. SHINE is performing fusion reactions to create neutrons that it then uses to break down uranium atoms, creating medical isotopes that can be used to kill cancer or perform complex medical imaging, or even make uranium from nuclear reactors less dangerous. There are huge markets for those products and — as this story explains in fascinating detail — SHINE is betting it can make enough money with them to fund its longer-term bet of building nuclear fusion power plants.
How incredibly simple tech can supercharge the race to net zero, from New Scientist
2,500 words, or about 10 minutes
Everyone knows the problem by now: Wind and solar energy are fantastic, but the sun doesn’t always shine, wind doesn’t always blow and the excess energy they produce is difficult to store. Arguably the best current option for storing electricity is in lithium-ion batteries, which are expensive and require difficult-to-mine metals that are in scant supply. But an emerging crop of low-tech solutions for energy storage is gaining steam. Two of the simplest are using weights, which can be raised during times of excess electricity production and released to generate electricity in times of demand; and a simple stack of bricks that can be heated to 1,500°C during times of energy surplus and slowly cooled to create electricity later or simply provide heat to industrial processes over time. None of the approaches is a silver bullet for the energy storage problem, but some combination of them could allow us to store far more energy from renewables than is currently possible.