Apple has confirmed reports [video link] of a software glitch causing some iPhone alarms to fail to play a sound.

Read more of this story at Slashdot.

情報元へのリンク

Apple has poached dozens of AI experts from Google and has created a secretive European laboratory in Zurich, as the tech giant builds a team to battle rivals in developing new AI models and products. From a report: According to a Financial Times analysis of hundreds of LinkedIn profiles as well as public job postings and research papers, the $2.7tn company has undertaken a hiring spree over recent years to expand its global AI and machine learning team. The iPhone maker has particularly targeted workers from Google, attracting at least 36 specialists from its rival since it poached John Giannandrea to be its top AI executive in 2018. While the majority of Apple's AI team work from offices in California and Seattle, the tech group has also expanded a significant outpost in Zurich. Professor Luc Van Gool from Swiss university ETH Zurich said Apple's acquisitions of two local AI start-ups -- virtual reality group FaceShift and image recognition company Fashwell -- led Apple to build a research laboratory, known as its "Vision Lab," in the city.

Read more of this story at Slashdot.

情報元へのリンク

An anonymous reader quotes a report from TechCrunch: Ahead of its annual GitHub Universe conference in San Francisco early this fall, GitHub announced Copilot Workspace, a dev environment that taps what GitHub describes as "Copilot-powered agents" to help developers brainstorm, plan, build, test and run code in natural language. Jonathan Carter, head of GitHub Next, GitHub's software R&D team, pitches Workspace as somewhat of an evolution of GitHub's AI-powered coding assistant Copilot into a more general tool, building on recently introduced capabilities like Copilot Chat, which lets developers ask questions about code in natural language. "Through research, we found that, for many tasks, the biggest point of friction for developers was in getting started, and in particular knowing how to approach a [coding] problem, knowing which files to edit and knowing how to consider multiple solutions and their trade-offs," Carter said. "So we wanted to build an AI assistant that could meet developers at the inception of an idea or task, reduce the activation energy needed to begin and then collaborate with them on making the necessary edits across the entire corebase." Given a GitHub repo or a specific bug within a repo, Workspace -- underpinned by OpenAI's GPT-4 Turbo model -- can build a plan to (attempt to) squash the bug or implement a new feature, drawing on an understanding of the repo's comments, issue replies and larger codebase. Developers get suggested code for the bug fix or new feature, along with a list of the things they need to validate and test that code, plus controls to edit, save, refactor or undo it. The suggested code can be run directly in Workspace and shared among team members via an external link. Those team members, once in Workspace, can refine and tinker with the code as they see fit. Perhaps the most obvious way to launch Workspace is from the new "Open in Workspace" button to the left of issues and pull requests in GitHub repos. Clicking on it opens a field to describe the software engineering task to be completed in natural language, like, "Add documentation for the changes in this pull request," which, once submitted, gets added to a list of "sessions" within the new dedicated Workspace view. Workspace executes requests systematically step by step, creating a specification, generating a plan and then implementing that plan. Developers can dive into any of these steps to get a granular view of the suggested code and changes and delete, re-run or re-order the steps as necessary. "Since developers spend a lot of their time working on [coding issues], we believe we can help empower developers every day through a 'thought partnership' with AI," Carter said. "You can think of Copilot Workspace as a companion experience and dev environment that complements existing tools and workflows and enables simplifying a class of developer tasks ... We believe there's a lot of value that can be delivered in an AI-native developer environment that isn't constrained by existing workflows."

Read more of this story at Slashdot.

情報元へのリンク

Richard Speed reports via The Register: NASA's optical communications demonstration has hit 25 Mbps in a test transmitting engineering data back to Earth from 140 million miles (226 million kilometers) away. The payload is riding aboard the Psyche probe, which is headed for an asteroid of the same name. On December 11, when the spacecraft was 19 million miles (30 million kilometers) away, it reached 267 Mbps, which NASA described as "comparable to broadband internet download speeds." However, as Psyche has continued on its trajectory, the distances have become greater, and the rate at which data can be transmitted and received has tumbled. At 140 million miles, the project's goal was to reach a lofty 1 Mbps. Instead, engineers managed to get 25 Mbps out of the demonstration. Earlier demonstrations tested the technology using preloaded data, such as a cat video. The latest experiment used a copy of engineering data also sent via Psyche's radio transmitter. "We downlinked about 10 minutes of duplicated spacecraft data during a pass on April 8," said Meera Srinivasan, the project's operations lead at NASA's Jet Propulsion Laboratory (JPL) in Southern California. "Until then, we'd been sending test and diagnostic data in our downlinks from Psyche. This represents a significant milestone for the project by showing how optical communications can interface with a spacecraft's radio frequency comms system." The demonstrator is only along for the ride -- Psyche uses conventional radio technology for its mission. However, the demonstration does point to the potential for higher-bandwidth communications in future projects.

Read more of this story at Slashdot.

情報元へのリンク