Xiaomi has created a 150-yuan AI hardware device, aiming to enable everyday users to easily get started with Vibe Coding.
Even ordinary people can use natural language to create their own custom AI hardware.
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AI “doppelgängers” in subway ads are collectively bullying humans.
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Taking on NVIDIA head-on to challenge Apple—Microsoft’s high-end AI PC gamble
Microsoft is courting local AI developers and high-end creators with the Surface Laptop Ultra, which features NVIDIA RTX Spark. The hardware brings large-capacity unified memory, CUDA, and RTX graphics capabilities to a portable device, but whether it can sustain competition against Macs will still depend on app optimization, agent-based experiences, and real-world workflows.
Why it matters：Ultimately, this competition comes down to whether on-device AI can genuinely boost creativity and development efficiency, and whether the associated costs—hardware, software, and migration—are justified. Hardware opens up new possibilities, but the ecosystem and real-world user experience determine how many users those possibilities can reach.
The PHP “Meltdown” incident reveals how AI can amplify the threat of legacy vulnerabilities.
Security researchers, using AI tools, have turned a PHP vulnerability—known collectively as PHP2Shell—that has existed for years and was once considered difficult to exploit—into a real-world exploitable attack surface. Within hours of the vulnerability being made public, it was already targeted in millions of exploitation attempts, yet no successful intrusions have been reported to date.
Why it matters：This incident clearly demonstrates for the first time that AI does not create new vulnerabilities out of thin air; rather, it significantly lowers the barrier to exploiting existing vulnerabilities, highlighting AI’s dual role in accelerating both offensive and defensive security dynamics. Moreover, all valid findings rely on human–machine collaboration.
Meta was ordered by a court to disclose the list of executives who approved the use of pirated downloads to train its AI.
In several copyright infringement lawsuits targeting Meta over AI training, courts have ruled that Meta must explicitly identify the executives who authorized the downloading of pirated books from shadow libraries such as Anna’s Archive and LibGen. Previously, Meta had shifted responsibility to frontline employees, claiming that its early AI data collection was an “informal process” and that no one had “formally decided” to carry out the downloads.
Meta Muse’s sharing feature has a privacy vulnerability: the generated conversation links are easily enumerable, leading to the leakage of personal and business secrets.
Security firm Clarot discovered that Meta’s newly launched AI agent, Muse, generates URLs with insufficient randomness when the conversation-sharing feature is enabled, allowing attackers to obtain 6,800 user-shared links through simple enumeration; among these, hundreds of links exposed non-public personal and business-sensitive information. Meta has suspended this sharing feature and initiated a review.