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Sutton's predictions v Royal Blood drummer Ben Thatcher

BBC News

Defending champions Arsenal made an impressive start to the season against newly promoted Coventry but face a tougher test against Aston Villa on Monday. But with the number of outgoings at Villa Park, will it be another eye-opener for Unai Emery's men after last week's heavy defeat by Brighton? BBC Sport football expert Chris Sutton thinks so. There's only one winner with this, he said. Aston Villa had a slow start last season, they have lost big players and I just think Arsenal are going to run all over teams this season. I think they are going to get better and better which is ominous for everybody else. Sutton is making predictions for all 380 Premier League games this season, against AI, BBC Sport readers and a variety of guests.


Why do mother bears kill cubs? The answer is complicated.

Popular Science

Why do mother bears kill cubs? Two bears at Brooks River in Alaska's Katmai National Park and Preserve recently killed cubs that weren't their own. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Scientists have several theories, but no definitive explanation for two recent attacks at Alaska's Katmai National Park and Preserve. Breakthroughs, discoveries, and DIY tips sent six days a week.


This European Social Enterprise Is Giving Gen Z Jobs They Actually Want--And Protecting Our Oceans

TIME - Tech

Follow this section to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Follow this tag to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW?


The US Built a Site to Ensure Fair Access to Public Lands. Then Everything Went Wrong

WIRED

The US Built a Site to Ensure Fair Access to Public Lands. Recreation.gov was supposed to make access to public lands more equitable and streamlined. It's a few minutes before 8 am Mountain Time on March 16, the day that river permit cancellations are released on Recreation.gov, the federal website for public land reservations. Rec.gov, as it's commonly called, administers everything from river permits and timed entrance fees at the most popular national parks to campground reservations on remote sites belonging to the Bureau of Land Management, and a lot of people are recreating on public land these days. There were 11 million reservations on the site in 2024, up significantly from 3.5 million reservations reported in 2019. At the center of it all is an unlikely player in the outdoor recreation space: The site is operated by the government contractor Booz Allen Hamilton, a corporation known more for cybersecurity than rafting trips. Early each year, outdoor enthusiasts gear up for Recreation.gov's annual lotteries for some of the most iconic experiences in the country: a river trip down Idaho's Middle Fork of the Salmon River, which flows through the Frank Church River of No Return Wilderness. Backcountry permits to hike into the Wave, an otherworldly rock formation in Arizona's Paria Canyon-Vermilion Cliffs Wilderness. Overnight stays in the rugged, lake-studded Enchantments, in Washington's Okanogan-Wenatchee National Forest. Odds of getting a desirable Middle Fork permit are around 2 percent.


Someone dies in a national park. Now what?

Popular Science

Someone dies in a national park. From "hasty searches" to helicopter extractions, rangers often face a difficult mission to recover remains. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. When someone is missing in a national park, a carefully coordinated process kicks into place--and in most cases, the family never sees a bill. Breakthroughs, discoveries, and DIY tips sent six days a week.



Learning to Play Sequential Games versus Unknown Opponents

Neural Information Processing Systems

To this end, we use kernel-based regularity assumptions to capture and exploit the structure in the opponent's response. We propose a novel algorithm for the learner when playing against an adversarial sequence of opponents.


Choosing Well Your Opponents: How to Guide the Synthesis of Programmatic Strategies

arXiv.org Artificial Intelligence

This paper introduces Local Learner (2L), an algorithm for providing a set of reference strategies to guide the search for programmatic strategies in two-player zero-sum games. Previous learning algorithms, such as Iterated Best Response (IBR), Fictitious Play (FP), and Double-Oracle (DO), can be computationally expensive or miss important information for guiding search algorithms. 2L actively selects a set of reference strategies to improve the search signal. We empirically demonstrate the advantages of our approach while guiding a local search algorithm for synthesizing strategies in three games, including MicroRTS, a challenging real-time strategy game. Results show that 2L learns reference strategies that provide a stronger search signal than IBR, FP, and DO. We also simulate a tournament of MicroRTS, where a synthesizer using 2L outperformed the winners of the two latest MicroRTS competitions, which were programmatic strategies written by human programmers.


Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation

arXiv.org Artificial Intelligence

In this paper, we introduce Ranger - a toolkit to facilitate the easy use of effect-size-based meta-analysis for multi-task evaluation in NLP and IR. We observed that our communities often face the challenge of aggregating results over incomparable metrics and scenarios, which makes conclusions and take-away messages less reliable. With Ranger, we aim to address this issue by providing a task-agnostic toolkit that combines the effect of a treatment on multiple tasks into one statistical evaluation, allowing for comparison of metrics and computation of an overall summary effect. Our toolkit produces publication-ready forest plots that enable clear communication of evaluation results over multiple tasks. Our goal with the ready-to-use Ranger toolkit is to promote robust, effect-size-based evaluation and improve evaluation standards in the community. We provide two case studies for common IR and NLP settings to highlight Ranger's benefits.


Can AI and Machine Learning Help Park Rangers Prevent Poaching?

#artificialintelligence

BRIAN KENNY: Artificial intelligence or AI for short is certainly creating a lot of buzz these days. And although it may seem like this amorphous thing that's somewhere off in our future, it's already very much in our midst. Navigation apps have turned printed maps into relics. Alexa, knows what you need from the grocery store before you do. Google Nest has the house at just the right temperature before you roll out from under the covers. And this is all great, but now you have to wonder if this intro is written by me or chat GPT. Which raises an important question.