Google has set a target of migrating all its internal systems to post-quantum cryptography (PQC) by 2029 to protect against future quantum attacks. This indicates that the feared 'Q-Day,' when powerful quantum computers could break current internet encryption, is no longer a distant hypothesis but a concrete threat.

Current digital security relies on mathematical problems that are extremely difficult for traditional computers to solve, but quantum computers could potentially solve these problems much faster. Consequently, Google is implementing a broad transition, including integrating quantum-resistant signature algorithms into Android 17.

This initiative suggests that Google aims to lead the industry, as Microsoft, U.S. federal agencies, and the European Commission are also pursuing similar migration plans. The objective is to have new defensive infrastructure ready before quantum computers can break existing cryptography, emphasizing the need for preparation rather than panic.

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Researchers at IBM have successfully simulated the behavior of a real magnetic material, KCuF3, with high precision using a quantum computer. This achievement marks a significant step for quantum computing, moving it from abstract theory to a practical scientific tool whose results can be directly compared with experimental data.

Previously, quantum computing faced challenges in producing results that matched real-world experiments, despite its impressive theoretical potential. However, IBM's breakthrough was made possible by low-error-rate two-qubit gates, highlighting the critical importance of error reduction for quantum computation to achieve practical value.

This technology not only promises a deeper understanding of existing materials but also holds the potential to predict the physical properties of materials that have not yet been measured or even manufactured. This is expected to accelerate discoveries in a wide range of applied fields, including batteries, superconductors, advanced chemistry, and pharmaceutical development.

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Victims of the Jeffrey Epstein case have filed a class-action lawsuit against Google, alleging that the company's AI Mode feature exposed their personal information. The lawsuit claims that evidence released by the Department of Justice in the Epstein case improperly disclosed the identities of some victims, and Google's AI Mode continued to republish this information.

The plaintiff states that when searching their own name and those of other victims they represent, Google's AI Mode displayed their "full name, contact information, cities of residence, and association with Jeffrey Epstein," and in the plaintiff's case, even generated a hyperlink allowing direct email. The victims claim they repeatedly requested Google to remove the information, but without success.

The lawsuit argues that Google's AI Mode is "not a neutral search index; it is an active recommender and content generator," and could be pleaded as "actionable doxxing." This lawsuit adds a new dimension to the ongoing debate about whether Section 230, which grants tech companies immunity from liability for third-party content, applies to AI.

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