Google unveiled Gemini 2.0 yesterday, almost exactly one year after Google's initial Gemini launch. The new release offers enhanced multimodal capabilities like native image and audio output, real-time tool use, and advanced reasoning to enable agentic experiences, such as acting as a universal assistant or research companion. VentureBeat reports: During a recent press conference, Tulsee Doshi, director of product management for Gemini, outlined the system's enhanced capabilities while demonstrating real-time image generation and multilingual conversations. "Gemini 2.0 brings enhanced performance and new capabilities like native image and multilingual audio generation," Doshi explained. "It also has native intelligent tool use, which means that it can directly access Google products like search or even execute code." The initial release centers on Gemini 2.0 Flash, an experimental version that Google claims operates at twice the speed of its predecessor while surpassing the capabilities of more powerful models. This represents a significant technical achievement, as previous speed improvements typically came at the cost of reduced functionality. Perhaps most significantly, Google introduced three prototype AI agents built on Gemini 2.0's architecture that demonstrate the company's vision for AI's future. Project Astra, an updated universal AI assistant, showcased its ability to maintain complex conversations across multiple languages while accessing Google tools and maintaining contextual memory of previous interactions. [...] For developers and enterprise customers, Google introduced Project Mariner and Jules, two specialized AI agents designed to automate complex technical tasks. Project Mariner, demonstrated as a Chrome extension, achieved an impressive 83.5% success rate on the WebVoyager benchmark for real-world web tasks -- a significant improvement over previous attempts at autonomous web navigation. Supporting these advances is Trillium, Google's sixth-generation Tensor Processing Unit (TPU), which becomes generally available to cloud customers today. The custom AI accelerator represents a massive investment in computational infrastructure, with Google deploying over 100,000 Trillium chips in a single network fabric.

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An anonymous reader quotes a report from Tom's Hardware, written by Avram Piltch: Microsoft's Recall feature recently made its way back to Windows Insiders after having been pulled from test builds back in June, due to security and privacy concerns. The new version of Recall encrypts the screens it captures and, by default, it has a "Filter sensitive information," setting enabled, which is supposed to prevent it from recording any app or website that is showing credit card numbers, social security numbers, or other important financial / personal info. In my tests, however, this filter only worked in some situations (on two e-commerce sites), leaving a gaping hole in the protection it promises. When I entered a credit card number and a random username / password into a Windows Notepad window, Recall captured it, despite the fact that I had text such as "Capital One Visa" right next to the numbers. Similarly, when I filled out a loan application PDF in Microsoft Edge, entering a social security number, name and DOB, Recall captured that. (Note that all info in these screenshots is made up). I also created my own HTML page with a web form that said, explicitly, "enter your credit card number below." The form had fields for Credit card type, number, CVC and expiration date. I thought this might trigger Recall to block it, but the software captured an image of my form filled out, complete with the credit card data. Recall did refuse to capture the credit card fields on the payment pages of Pimoroni and Adafruit. "So, when it came to real-world commerce sites that I visited, Recall got it right," adds Piltch. "However, what my experiment proves is that it's pretty much impossible for Microsoft's AI filter to identify every situation where sensitive information is on screen and avoid capturing it."

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