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first_img Google stated that the Willow chip reduces magical state errors by approximately 40 times

The Google Quantum AI team published a paper in Science, announcing that a technique called magic state cultivation reduces errors by about 40 times on the Willow processor, producing logical fidelity of 99.99% for T states. Magic states are one-time resources required to run useful quantum programs, consumed with each use; according to estimates cited by Google, the cost of producing magic states can account for up to 95% of a quantum computer's total capacity, leaving very limited space for actual computation.The previous standard approach was magic state distillation proposed by physicists Sergei Bravyi and Alexei Kitaev in 2004, which required a large number of qubit factories dedicated solely to this task. Google researchers proposed a cheaper cultivation route in 2024, which behaves more like a filter: injecting rough magic states into a small area of the chip, running a series of checks on them, discarding all attempts found to be defective, and allowing the passers to gradually expand. In the experiments, only about 8% of attempts passed all checks, meaning that more than 90% of attempts had to be discarded for each clean state retained.The cultivation technology is one of the supports for Gidney's 2025 estimate that RSA-2048 encryption could be broken by fewer than a million noisy qubits, a reduction of 20 times from the 20 million estimated in 2019. This experiment used up to 54 of the 105 qubits in Willow, with the paper noting that breaking the RSA-2048 key requires magic states with an error rate of about one in ten billion, which is about a million times cleaner than this result.

first_img OpenAI is facing a class-action lawsuit, accused of allowing outsourced personnel to read ChatGPT conversations

Two ChatGPT users from California filed a proposed class action lawsuit against OpenAI in the United States District Court for the Northern District of California this month, accusing the company of failing to adequately inform users that their real conversations were being handed over to external contractors for processing. The lawsuit was served to OpenAI on September 2, focusing on its internal initiative Project Lily. According to the complaint, "AI data reviewers" and "chatbot evaluators" recruited through a third-party staffing company read real ChatGPT prompts and complete conversations, summarize user intent, and score and comment on responses from four models on a scale of 1 to 7.This process is known in the industry as reinforcement learning from human feedback (RLHF), which is a fundamental method for enhancing chatbot capabilities. The complaint states that users were never explicitly informed that a person, rather than a machine, might be reading their conversations. OpenAI filters conversations through an automated system before human review, but the complaint alleges that the filters cannot intercept all content, and personal details sometimes still reach contractors. 404 Media first reported on the project on September 14 and found that the reviewers' dashboard included "user memory summaries," which could expose users' approximate locations, occupations, or private life information, even though usernames had been removed.OpenAI stated that such reviews aim to reduce two behaviors: chatbots behaving too much like humans and overly catering to users, referred to by researchers as "flattery." The complaint raises eight legal claims, including violations of California's Unfair Competition Law, Consumer Privacy Act, and common law claims for intrusion into private affairs, with the plaintiffs seeking damages, restitution of unjust enrichment, and punitive damages.
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