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Intel's stock jumped 7% after reports that the Trump administration is considering taking a stake in the struggling chipmaker to support U.S.-based manufacturing. CNBC reports: Intel is the only U.S. company with the capability to manufacture the fastest chips on U.S. shores, although rivals including Taiwan Semiconductor Manufacturing Company and Samsung also have U.S. factories. President Donald Trump has called for more chips and high technology to be manufactured in the U.S. The government's stake would help fund factories that Intel is currently building in Ohio, according to the report.

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DeepSeek's development of its next-gen R2 AI model was severely delayed after months of failed training attempts on Huawei's Ascend chips, which suffered from unstable hardware, slow interconnects, and immature software. The Register reports: Following the industry rattling launch of DeepSeek R1 earlier this year, the Chinese AI darling faced pressure from government authorities to train the model's successor on Huawei's homegrown silicon, three unnamed sources have told the Financial Times. But after months of work and the help of an entire team of Huawei engineers, unstable chips, glacial interconnects, and immature software proved insurmountable for DeepSeek, which was apparently unable to complete a single successful training run. The failure, along with challenges with data labeling, ultimately delayed the release of DeepSeek R2 as the company started anew, using Nvidia's H20 GPUs instead. The company has reportedly relegated Huawei's Ascend accelerators to inference duty.

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iBiz shifts data to iPhone in patent workaround

Apple will deliver a software update for recent US Apple Watch models to reimplement the ability to measure blood oxygen levels, a process known as pulse oximetry.…

Rising subscription costs, shrinking content libraries, and regional restrictions are pushing viewers back toward piracy. Once seen as nearly dead, piracy has resurged through illicit streaming platforms as the fractured, ad-laden streaming market struggles to deliver convenience and value. The Guardian reports: According to London-based piracy monitoring and content-protection firm MUSO, unlicensed streaming is the predominant source of TV and film piracy, accounting for 96% in 2023 (PDF). Piracy reached a low in 2020, with 130bn website visits. But by 2024 that number had risen to 216bn (PDF). In Sweden, 25% of people surveyed (PDF) reported pirating in 2024, a trend mostly driven by those aged 15 to 24. Piracy is back, just sailing under a different flag. "Piracy is not a pricing issue," Gabe Newell, the co-founder of Valve, the company behind the world's largest PC gaming platform, Steam, observed in 2011. "It's a service issue." Today, the crisis in streaming makes this clearer than ever. With titles scattered, prices on the rise, and bitrates throttled depending on your browser, it is little wonder some viewers are raising the jolly roger again. Studios carve out fiefdoms, build walls and levy tolls for those who wish to visit. The result is artificial scarcity in a digital world that promised abundance. Whether piracy today is rebellion or resignation is almost irrelevant; the sails are hoisted either way. As the streaming landscape fractures into feudal territories, more viewers are turning to the high seas. The Medici understood the value linked to access. [The 2016 historical drama series tells of the rise of the powerful Florentine banking dynasty, and with it, the story of the Renaissance.] A client could travel from Rome to London and still draw on their credit, thanks to a network built on trust and interoperability. If today's studios want to survive the storm, they may need to rediscover that truth.

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An anonymous reader quotes a report from Ars Technica: Google has announced a tiny version of its Gemma open model designed to run on local devices. Google says the new Gemma 3 270M can be tuned in a snap and maintains robust performance despite its small footprint. [...] Running an AI model locally has numerous benefits, including enhanced privacy and lower latency. Gemma 3 270M was designed with these kinds of use cases in mind. In testing with a Pixel 9 Pro, the new Gemma was able to run 25 conversations on the Tensor G4 chip and use just 0.75 percent of the device's battery. That makes it by far the most efficient Gemma model. Developers shouldn't expect the same performance level of a multi-billion-parameter model, but Gemma 3 270M has its uses. Google used the IFEval benchmark, which tests a model's ability to follow instructions, to show that its new model punches above its weight. Gemma 3 270M hits a score of 51.2 percent in this test, which is higher than other lightweight models that have more parameters. The new Gemma falls predictably short of 1 billion-plus models like Llama 3.2, but it gets closer than you might think for having just a fraction of the parameters. Google claims Gemma 3 270M is good at following instructions out of the box, but it expects developers to fine-tune the model for their specific use cases. Due to the small parameter count, that process is fast and low-cost, too. Google sees the new Gemma being used for tasks like text classification and data analysis, which it can accomplish quickly and without heavy computing requirements. You can download the new Gemma for free, and the model weights are available. There's no separate commercial licensing agreement, so developers can modify, publish, and deploy Gemma 3 270M derivatives in their tools. You can download Gemma 3 270M from Hugging Face and Kaggle in both pre-trained and instruction-tuned versions.

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Some custom malware, some legit software tools

At least a dozen ransomware gangs have incorporated kernel-level EDR killers into their malware arsenal, allowing them to bypass almost every major endpoint security tool on the market, escalate privileges, and ultimately steal and encrypt data before extorting victims into paying a ransom.…