Skip to main content

A Quantum Error Correction Breakthrough?

1 month 1 week ago
The dream of quantum computers has been hampered by the challenge of error correction, writes the Harvard Gazette, since qubits "are inherently susceptible to slipping out of their quantum states and losing their encoded information." But in a newly-published paper, a research team "combined various methods to create complex circuits with dozens of error correction layers" that "suppresses errors below a critical threshold — the point where adding qubits further reduces errors rather than increasing them." "For the first time, we combined all essential elements for a scalable, error-corrected quantum computation in an integrated architecture," said Mikhail Lukin, co-director of the Quantum Science and Engineering Initiative, Joshua and Beth Friedman University Professor, and senior author of the new paper. "These experiments — by several measures the most advanced that have been done on any quantum platform to date — create the scientific foundation for practical large-scale quantum computation..." "There are still a lot of technical challenges remaining to get to very large-scale computer with millions of qubits, but this is the first time we have an architecture that is conceptually scalable," said lead author Dolev Bluvstein, Ph.D. '25, who did the research during his graduate studies at Harvard and is now an assistant professor at Caltech. "It's going to take a lot of effort and technical development, but it's becoming clear that we can build fault-tolerant quantum computers...." Hartmut Neven, vice president of engineering at the Google Quantum AI team, said the new paper came amid an "incredibly exciting" race between qubit platforms. "This work represents a significant advance toward our shared goal of building a large-scale, useful quantum computer," he said... With recent advances, Lukin believes the core elements for building quantum computers are falling into place. "This big dream that many of us had for several decades, for the first time, is really in direct sight," he said. "In theory, a system of 300 quantum bits can store more information than the number of particles in the known universe..." the article points out. "The new paper represents an important advance in a three-decade pursuit of quantum error correction." Thanks to long-time Slashdot reader schwit1 for sharing the article.

Read more of this story at Slashdot.

EditorDavid

Fear Drives the AI 'Cold War' Between America and China

1 month 1 week ago
A new "cold war" between America and China is "pushing leaders to sideline concerns about the dangers of powerful AI models," reports the Wall Street Journal, "including the spread of disinformation and other harmful content, and the development of superintelligent AI systems misaligned with human values..." "Both countries are driven as much by fear as by hope of progress. " In Washington and Silicon Valley, warnings abound that China's "authoritarian AI," left unchecked, will erode American tech supremacy. Beijing is gripped by the conviction that a failure to keep pace in AI will make it easier for the U.S. to cut short China's resurgence as a global power. Both countries believe market share for their companies across the world is up for grabs — and with it, the potential to influence large swaths of the global population. The U.S. still has a clear lead, producing the most powerful AI models. China can't match it in advanced chips and has no answer for the financial firepower of private American investors, who funded AI startups to the tune of $104 billion in the first half of 2025, and are gearing up for more. But it has a massive population of capable engineers, lower costs and a state-led development model that often moves faster than the U.S., all of which Beijing is working to harness to tip the contest in its direction. A new "whole of society" campaign looks to accelerate the construction of computing clusters in areas like Inner Mongolia, where vast solar and wind farms provide plentiful cheap energy, and connect hundreds of data centers to create a shared compute pool — some describe it as a "national cloud" — by 2028. China is also funneling hundreds of billions of dollars into its power grid to support AI training and adoption... "Our lead is probably in the 'months but not years' realm," said Chris McGuire, who helped design U.S. export controls on AI chips while serving on the National Security Council under the Biden administration. Chinese AI models currently rank at or near the top in every task from coding to video generation, with the exception of search, according to Chatbot Arena, a popular crowdsourced ranking platform. China's manufacturing sector, meanwhile, is rocketing past the U.S. in bringing AI into the physical world through robotaxis, autonomous drones and humanoid robots. Given China's progress, McGuire said, the U.S. is "very lucky" to have its advantage in chips... If AI surpasses human intelligence and acquires the ability to improve itself, it could confer unshakable scientific, economic and military superiority on the country that controls it. Short of that, AI's ability to automate tedious tasks and process vast amounts of data quickly promises to supercharge everything from cancer diagnoses to missile defense. With so much at stake, hacking and cyber espionage are likely to get worse, as AI gives hackers more powerful tools, while increasing incentives for state-backed groups to try to steal AI-related intellectual property. As distrust grows, Washington and Beijing will also find it hard, if not impossible, to cooperate in areas like preventing extremist groups from using AI in destructive ways, such as building bioweapons. "The costs of the AI Cold War are already high and will go much higher," said Paul Triolo, a former U.S. government analyst and current technology policy lead at business consulting firm DGA-Albright Stonebridge Group. "A U.S.-China AI arms race becomes a self-fulfilling prophecy, with neither side able to trust that the other would observe any restrictions on advanced AI capability development...." The article includes an interesting observation from Helen Toner, director of strategy for Georgetown's Center for Security and Emerging Technology and a former OpenAI board member. Toner points out "We don't actually know" if boosting computing power with better chips will continue producing more-powerful AI models. So "If performance plateaus," the Journal writes, "despite all the spending by OpenAI and others — a growing concern in Silicon Valley — China has a chance to compete."

Read more of this story at Slashdot.

EditorDavid