Project Aria (Engel et al., 2023), Meta's all-day These models exhibit an unprecedented ability wearable AR glasses developed as data collection to understand and generate human-like language, tools for spatial computing. While Project Aria process visual and auditory information, and interpret aims to shift computing paradigms by blending digital 3D spatial environments (Zhao et al., 2023; interactions into the 3D world through spatial Yin et al., 2023; Engel et al., 2023). However, computing, Lucia extends these ideas by emphasizing as we push the boundaries of AI, a new frontier the temporal dimension. It prioritizes the emerges: Temporal Computing--the understanding continuous capture and intelligent interpretation of and utilization of time to construct contextual user activities over time while enhancing practical memory that enhances human cognition. This evolution usability: Lucia creates a device that not only has paved the way for devices that are not records but also understands and provides insightful only intelligent but also temporally aware, deeply responses based on the user's temporal expe-1

Context: Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability and effectiveness. Therefore, researchers have been proposing automated, heuristic-based techniques to detect them. However, the performance of such detectors is still limited and dependent on thresholds to be tuned. Objective: We propose the design and experimentation of a novel test smell detection approach based on machine learning to detect four test smells. Method: We plan to develop the largest dataset of manually-validated test smells. This dataset will be leveraged to train six machine learners and assess their capabilities in within- and cross-project scenarios. Finally, we plan to compare our approach with state-of-the-art heuristic-based techniques.

When NVIDIA purchased mobile-chip designer Arm Holdings from SoftBank last year, NVIDIA CEO Jensen Huang made the bold prediction that in the years ahead, there will be trillions of artificial intelligence (AI)-enabled Internet of Things (IoT) devices. Regardless of whether that holds true, it is safe to say the growth of IoT devices is exploding. All those devices will require power sources, and the way Josiah Hester sees it, that's problematic for the environment and society. "When I see the'trillion' number, I see a trillion dead batteries, basically," says Hester, an assistant professor of computer engineering at Northwestern University. "There's piles of batteries in landfills in China and elsewhere sitting there unrecycled; or they're put in furnaces and melted down, which is not a carbon-neutral event."

OXFORD, England, April 11 (Thomson Reuters Foundation) - When Nepal suffered devastating twin earthquakes in 2015 that killed nearly 9,000 people, the government provided help for families whose homes had collapsed to rebuild. But tens of thousands of others with damaged homes that were still standing faced a tougher decision: Was it safe to make repairs? Or were they better off building a new, often smaller home at their own cost? Artificial intelligence (AI), it turned out, could help, said Elizabeth Hausler, a U.S.-based engineer and builder who works on creating affordable, disaster-resilient housing. In Nepal, many homes are variations on a standard design - rectangular, multi-storey and with similar windows, she said.