Personal Assistant Systems
'Masked Men Burning Families Out of Their Homes': Belfast Protests Erupt After Knife Attack
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Why Having Too Much Money Can Be Bad for Your Mental Health
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How Steven Spielberg Convinced the Cast of Disclosure Day That Aliens Are Real
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Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation
Integrating large language models (LLMs) into recommender systems has created new opportunities for improving recommendation quality. However, a comprehensive benchmark is needed to thoroughly evaluate and compare the recommendation capabilities of LLMs with traditional recommender systems. In this paper, we introduce \recbench{}, which systematically investigates various item representation forms (including unique identifier, text, semantic embedding, and semantic identifier) and evaluates two primary recommendation tasks, i.e., click-through rate prediction (CTR) and sequential recommendation (SeqRec). Our extensive experiments cover up to 17 large models and are conducted across five diverse datasets from fashion, news, video, books, and music domains. Our findings indicate that LLM-based recommenders outperform conventional recommenders, achieving up to a 5% AUC improvement in CTR and up to a 170% NDCG@10 improvement in SeqRec. However, these substantial performance gains come at the expense of significantly reduced inference efficiency, rendering LLMs impractical as real-time recommenders. We have released our code and data to enable other researchers to reproduce and build upon our experimental results.
The Fight Over AI Is Really a Fight Over Who Governs
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What's In--and Not In--the Immigration Enforcement Funding Bill Congress Passed
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Bill Gates Is Set to Give an Interview in the House Epstein Probe. Here's What to Know About His Ties to Epstein
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Young People Don't Need Another Lecture About Phones
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The Top New Features in Apple's iOS 27 and iPadOS 27
Apple took the wraps off iOS 27 at its WWDC event, and the iPhone update is chock-full of smart upgrades, with a big focus on improvements to Siri. While the news coming out of WWDC 2026 is not as dramatic as last year's iOS 26 update, where the new Liquid Glass redesign caused a big stir, Apple's presentation still made waves. During the WWDC keynote, Apple walked through the changes coming to the next version of its mobile operating systems, iOS 27 and iPadOS 27. These updates will roll out to iPhones and iPads later this year, likely in September. There are several smaller quality-of-life improvements, but the big highlight is the Siri AI upgrade .
Siri AI first look: How Apple's rebuilt AI-powered assistant behaves across iPhone, iPad and Mac
Siri AI first look: How Apple's rebuilt AI-powered assistant behaves across iPhone, iPad and Mac Siri AI first look: How Apple's rebuilt AI-powered assistant behaves across iPhone, iPad and Mac A quick preview of what's to come this fall. The biggest news out of WWDC 2026 was, as widely rumored, the next generation of Siri. Called Siri AI, the AI-boosted assistant will be infused into lots of Apple products like the iPhone, iPad and Mac. You can sign up to get early access to the new Siri AI to get a feel for how it behaves. But since I've already had the opportunity to check out some demos here at Apple Park after the keynote ended, I figured I'd preview it for those of you who don't want to go through the hassle of beta software.