According to Forbes, Google released a new instant messaging and voice chat program, ending months of speculation over whether the search giant would enter the heated IM market. The company hasn't said how it might generate revenue from these services, which have been offered for years by competitors. But Google�s new services hint at a much larger company strategy to launch headlong into telecommunications. In the future, Google's new IM service, called Google Talk, could go a step further than competing services, allowing users to make and receive calls to the public telephone network; it would not only set the program apart from rivals but provide new revenue streams for the company. Google could sell calling-minutes to customers, who would pay for the ability to make cheap calls over the Internet. Many of the company's recent moves support a major push by Google into telephony, including rumors that the company has already purchased unused fiber optic cables across the U.S. Google's kept quiet about whether it is buying fiber, but in January the company posted a job listing on its site looking for candidates with experience in "identification, selection and negotiation of dark fiber contracts both in metropolitan areas and over long distances as part of development of a global backbone network." In July, Current Communications Group announced that it had landed a $100 million investment from Google, Goldman Sachs and The Hearst Corporation to develop broadband over power-line technologies, which would deliver high-speed Internet connections to homes over electrical wires. Those investments would pay off if the company plans to handle large amounts of voice traffic. Google engineers have also been spotted attending a number of Internet telephony-centric conferences.
Enterprise AI adoption keeps running into the same wall: the moment sensitive data, model weights, or agent memory leave a tightly controlled environment, security teams lose visibility into what happens to them while the workload is actually running. Confidential computing exists to close that gap, and new research from ABI Research shows the technology has matured enough, across CPUs, GPUs, containers, and now agentic AI, to become a foundational requirement for enterprises building sovereign AI infrastructure: computing environments they control end to end rather than simply rent. Protection is Moving From CPUs to GPUs ABI Research finds that CPU-based confidential computing is closest to mass-market adoption, the product of years spent hardening chip-level isolation for general workloads. GPU-based confidential computing is now generating the strongest momentum, and for good reason. It addresses one of the largest unresolved gaps in AI security: protecting data and models while inf...