Ideas to make Dad's day brighter and more memorable. Shopping for Father's Day can feel like a bit of a puzzle, right? Maybe yours is always glued to his laptop, loves keeping the pool spotless or enjoys pouring a fresh pint at home. If you want to skip the usual gifts and pick something that actually matches his personality, you're in the right place. From cool gadgets to smart tools and a few fun surprises, these ideas are all about making dad's day brighter and more memorable.

Breakthroughs, discoveries, and DIY tips sent every weekday. Our smartphones have transformed the way we take photos and videos and our relationship to these digital memories. Most of us will snap at least some pictures and clips every day with the gadget that's always close at hand. If you want to get more creative with photos on your phone, you can. Sometimes you're going to want to take a picture remotely, without your phone in your hand and your finger over the shutter button--maybe you're taking a wide shot of a large group, or you want to capture a lot of your surroundings.

E-BAR operates as a set of robotic handlebars that follow users. The demographic landscape in the U.S. is shifting rapidly, with the median age now at 38.9, almost a decade older than it was in 1980. By 2050, the population of adults over 65 is projected to surge from 58 million to 82 million, intensifying the already urgent challenge of eldercare. With falls remaining the top cause of injury among older adults, the need for innovative, tech-driven solutions has never been clearer. MIT engineers are stepping up to this challenge with E-BAR, a mobile robot designed to physically support seniors and prevent falls as they move around their homes.

If you've been wanting a pair of Ray-Ban Meta smartglasses, this is the best price I've seen since last year's Black Friday. Amazon has pairs as low as 239 right now, both with and without tinted lenses. They offer the classic Wayfarer style, so they look good on just about everyone. The sale is limited to what's in stock right now, so grab the color and the size you want before they sell out. When talking about the Ray-Ban Meta glasses, most people focus on the built-in camera.

Of all the egomaniacal lions who ruled Hollywood during the 20th century gatekeeper era, very few made a brilliant pivot to the internet. The exception is Barry Diller. After leading programming at ABC, running Paramount, and supercharging Fox by launching its broadcast network in the late 1980s, Diller no longer wanted to work for anyone else. Either you are or you aren't, he said of independence. As a free agent he quickly grasped the power of interactivity and built an empire that includes Expedia Group, almost the entire online dating sector (Tinder, Match, OkCupid), and an online media lineup that includes People, which wrote a hit piece on him early in his career titled "Failing Upwards."

What if you could turn your everyday snapshots into jaw-dropping works of art with just a few clicks? That's exactly what Luminar Neo does--and right now, you can get lifetime access to this award-winning photo-editing software for just 89.99 (regularly 682). Plus, you'll get a ton of exclusive add-ons that'll elevate your photography game from amateur to absolutely on point. It's AI-powered, intuitive, and packed with state-of-the-art tools that make even the most complex edits feel effortless. Whether you're a pro photographer, content creator, or just love tinkering with your travel pics, Luminar Neo's tools--like Sky for instant sky replacements and Relight to adjust lighting like a pro--make magic happen.

While at the park, the service members had the chance to explore attractions and participate in Disneyland's daily flag ceremony. Disney's Imagineers are working on a new animatronic of iconic American visionary Walt Disney, but some members of his family have opposing views about whether it celebrates his legacy or dehumanizes him. Disney's Main Street Opera House plans to unveil a new theme park attraction called Walt Disney – A Magical Life, featuring an audio-animatronic of the company's founder. But Joanna Miller, one of Disney's grandchildren, slammed the idea of an animatronic as "dehumanizing" in a viral Facebook post. Among her claims, she suggested that her grandfather had told early Imagineer Sam McKim he never wanted to be commemorated with an animatronic.

The progress of AI systems such as large language models (LLMs) raises increasingly pressing concerns about their safe deployment. This paper examines the value alignment problem for LLMs, arguing that current alignment strategies are fundamentally inadequate to prevent misuse. Despite ongoing efforts to instill norms such as helpfulness, honesty, and harmlessness in LLMs through fine-tuning based on human preferences, they remain vulnerable to adversarial attacks that exploit conflicts between these norms. I argue that this vulnerability reflects a fundamental limitation of existing alignment methods: they reinforce shallow behavioral dispositions rather than endowing LLMs with a genuine capacity for normative deliberation. Drawing from on research in moral psychology, I show how humans' ability to engage in deliberative reasoning enhances their resilience against similar adversarial tactics. LLMs, by contrast, lack a robust capacity to detect and rationally resolve normative conflicts, leaving them susceptible to manipulation; even recent advances in reasoning-focused LLMs have not addressed this vulnerability. This ``shallow alignment'' problem carries significant implications for AI safety and regulation, suggesting that current approaches are insufficient for mitigating potential harms posed by increasingly capable AI systems.

Automatic fact-checking has recently received more attention as a means of combating misinformation. Despite significant advancements, fact-checking systems based on retrieval-augmented language models still struggle to tackle adversarial claims, which are intentionally designed by humans to challenge fact-checking systems. To address these challenges, we propose a training-free method designed to rephrase the original claim, making it easier to locate supporting evidence. Our modular framework, SUCEA, decomposes the task into three steps: 1) Claim Segmentation and Decontextualization that segments adversarial claims into independent sub-claims; 2) Iterative Evidence Retrieval and Claim Editing that iteratively retrieves evidence and edits the subclaim based on the retrieved evidence; 3) Evidence Aggregation and Label Prediction that aggregates all retrieved evidence and predicts the entailment label. Experiments on two challenging fact-checking datasets demonstrate that our framework significantly improves on both retrieval and entailment label accuracy, outperforming four strong claim-decomposition-based baselines.

Misleading text detection on social media platforms is a critical research area, as these texts can lead to public misunderstanding, social panic and even economic losses. This paper proposes a novel framework - CL-ISR (Contrastive Learning and Implicit Stance Reasoning), which combines contrastive learning and implicit stance reasoning, to improve the detection accuracy of misleading texts on social media. First, we use the contrastive learning algorithm to improve the model's learning ability of semantic differences between truthful and misleading texts. Contrastive learning could help the model to better capture the distinguishing features between different categories by constructing positive and negative sample pairs. This approach enables the model to capture distinguishing features more effectively, particularly in linguistically complicated situations. Second, we introduce the implicit stance reasoning module, to explore the potential stance tendencies in the text and their relationships with related topics. This method is effective for identifying content that misleads through stance shifting or emotional manipulation, because it can capture the implicit information behind the text. Finally, we integrate these two algorithms together to form a new framework, CL-ISR, which leverages the discriminative power of contrastive learning and the interpretive depth of stance reasoning to significantly improve detection effect.