The new Siri AI is conversational, omnipresent, and actually helpful. I'm outside hiking and testing a developer beta of Siri AI, Apple's revamped voice assistant, when fog engulfs the Golden Gate Bridge behind me. So, I pull out my iPhone and ask this new Siri where I can grab some fluffy pancakes nearby. A translucent orb at the top of the smartphone screen spins around a few times, then the voice assistant responds with a recommendation: a spot called Eats in the Inner Richmond. This version of Siri--conversational, omnipresent, actually helpful--has been long delayed.

Apple has announced the latest version of macOS. It's all about the reintroduction of Siri, which is now accessible from anywhere on the Mac desktop. The official name of the Mac's operating system is macOS 27 Golden Gate, keeping the California naming scheme around. This year's update is focused on the relaunched Siri (now known as Siri AI), which really strives to transform into a proper AI chatbot along the lines of ChatGPT or Google Gemini--with a unique Apple twist. Is Your Mac Compatible With macOS Golden Gate?

Due to health and energy concerns, the California Legislature is considering bills to prohibit data centers from being exempted from the state's stringent environmental law and impose new tariffs on new major energy users that strain power supplies.

Steve Rose goes for a spin. Steve Rose goes for a spin. 'We don't tell the car what it should do': my ride in a self-driving taxi Driverless'robotaxis' will be accepting fares in Britain's biggest city by the end of next year. Can they deal with London's medieval roads, hordes of pedestrians and errant ebikers? 'I'm really excited to show you this," says Alex Kendall, the CEO of Wayve, as he gets behind the wheel of one of the company's electric Ford Mustangs. The car pulls up to a junction at a busy road in King's Cross, London, all by itself. "You can see that it's going to control the speed, steering, brake, indicators," he says to me - I'm in the passenger seat. "It's making decisions as it goes.

By introducing LLM-embedded textual timestamps, Auto-Times can utilize chronological information to align multivariate time series. Empirically, AutoTimes achieves state-of-the-art with 0.1% trainable parameters and

Lately, there has been a surge in interest surrounding generative modeling of time series data. Most existing approaches are designed either to process short sequences or to handle long-range sequences. This dichotomy can be attributed to gradient issues with recurrent networks, computational costs associated with transformers, and limited expressiveness of state space models. Towards a unified generative model for varying-length time series, we propose in this work to transform sequences into images.