Liverpool have lost three games in a row in all competitions but can they get back on track against old rivals Manchester United on Sunday? This is a huge game for Arne Slot's side, said BBC Sport football expert Chris Sutton. United can definitely hurt Liverpool on the break, and that is clearly the way they will set up at Anfield. Sutton is making predictions for all 380 Premier League games this season, against AI, BBC Sport readers and a variety of guests. For week eight, he takes on Addison and Aya from CBBC football drama Jamie Johnson FC (JJFC), which is set in the world of an elite academy at fictional Premier League club Hawx United. Do you agree with their scores? You can make your own predictions below. The most popular scoreline selected for each game is used in the scoreboards and tables at the bottom of this page.

Training large foundation models costs hundreds of millions of dollars, making deployment optimization critical. Current approaches require machine learning engineers to manually craft training recipes through error-prone trial-and-error on expensive compute clusters. To enable efficient exploration of training configurations, researchers have developed performance modeling systems. However, these systems force users to translate their workloads into custom specification languages, introducing a fundamental semantic gap between the actual workload and its representation. This gap creates an inherent tradeoff: systems must either support a narrow set of workloads to maintain usability, require complex specifications that limit practical adoption, or compromise prediction accuracy with simplified models. We present Maya, a performance modeling system that eliminates these tradeoffs through transparent device emulation. By operating at the narrow interface between training frameworks and accelerator devices, Maya can capture complete workload behavior without requiring code modifications or translations. Maya intercepts device API calls from unmodified training code to directly observe low-level operations, enabling accurate performance prediction while maintaining both ease of use and generality. Our evaluation shows Maya achieves less than 5% prediction error across diverse models and optimization strategies, identifying configurations that reduce training costs by up to 56% compared to existing approaches.

Medication adherence is critical for the recovery of adolescents and young adults (AYAs) who have undergone hematopoietic cell transplantation (HCT). However, maintaining adherence is challenging for AYAs after hospital discharge, who experience both individual (e.g. physical and emotional symptoms) and interpersonal barriers (e.g., relational difficulties with their care partner, who is often involved in medication management). To optimize the effectiveness of a three-component digital intervention targeting both members of the dyad as well as their relationship, we propose a novel Multi-Agent Reinforcement Learning (MARL) approach to personalize the delivery of interventions. By incorporating the domain knowledge, the MARL framework, where each agent is responsible for the delivery of one intervention component, allows for faster learning compared with a flattened agent. Evaluation using a dyadic simulator environment, based on real clinical data, shows a significant improvement in medication adherence (approximately 3%) compared to purely random intervention delivery. The effectiveness of this approach will be further evaluated in an upcoming trial.

Magic Leap showed off a demo of Mica, a humanlike artificial intelligence that can be viewed in the company's augmented reality glasses, the Magic Leap One Creator Edition. I saw a demo of Mica, a short-haired woman who doesn't speak but still communicates in warm ways with the viewer. I put the AR glasses on my head and looked through prescription inserts to see the virtual overlays on the real world. I thought it was the best thing Magic Leap showed off. I walked into a physical room and sat in a chair.

Ubisoft's most-spotlighted (and most-leaked) game of E3 was definitely Assassin's Creed Odyssey, a new entry in the game that is…going back to making the series an annual franchise, even if Ubisoft said they were steering away from that. While Odyssey looks a lot like an Origins reskin, this time set in ancient Greece, it's going pretty hard into full-on RPG territory, complete with individual pieces of armor with different rarities, dialogue trees and even romance options for your character, where you can play as either the male Alexios or female Kassandra, both angling to become Spartan legends. What has been consistently weird about Assassin's Creed Odyssey is that other than looking like an Assassin's Creed game, there are almost no traces of…Assassins at all, at least as we've come to know them. There is an "assassin" skill tree, but that's a lower case "a" along with hunter and warrior skill trees. The only thing that seems remotely connected to the Assassin's Creed universe at all is that it seems pretty clear that your treasured weapon, the spear of Leonidas, is a Piece of Eden, giving you supernatural powers in combat.