The best webcam makes you look your best -- for less. Most laptops ship with a 720p webcam, so a 1080p webcam or even a 4K webcam can make you stand out by comparison. I haven't tested every one of these webcams, just most of them -- and I describe how I test under my recommendations. You can also refer to my separate story on the best Windows Hello webcams for recommendations that aid videoconferencing and log you into your PC. Two recommendations from that list -- a premium and budget option -- appear on this list. Why you should trust me: PCWorld has been testing PC hardware since the 1980s, and I've been a technology journalist for 30 years, with extensive experience in reviewing PC hardware. When it comes to webcams, my recommendations are based on hands-on testing in real-world scenarios. I also tap the expertise and published reviews of my counterparts in Sweden and Germany to offer a comprehensive view of the current webcam landscape. The Anker PowerConf C200 offers an affordable yet substantial upgrade from the 720p cameras found in most laptop webcams to a 1440p webcam, yet does so at an affordable price.

The keyword for the iPhone 16e seems to be "compromise." In this episode, Devindra chats with Cherlynn about her iPhone 16e review and try to figure out who this phone is actually for. Also, they dive into Amazon's Alexa event, where we finally learned more about the company's AI-powered voice assistant. Alexa seems useful, but can we trust it? Listen below or subscribe on your podcast app of choice. If you've got suggestions or topics you'd like covered on the show, be sure to email us or drop a note in the comments! And be sure to check out our other podcast, Engadget News! Framework unveils a cheap 2-in-1 laptop and a…modular desktop? Devindra: This week, it's the iPhone 16e, which Cherlynn has reviewed. We're going to get her full thoughts on that thing. And also, Amazon held an AI event this week. We expected a lot of devices, but they spent 75 minutes talking about Alexa plus, which is the AI powered Alexa. Cherlynn: we expected a lot of devices. Cherlynn: one, at least one it's been a while. Devindra: Mr. Panos Panay was there, the father of the service and no devices, just him talking about AI. Cherlynn: Oh, and stay tuned at the end of this episode. Uh, I, we included an interview that I did with, um, the vice president of Alexa to talk more about the new Alexa plus. Devindra: Anyway, folks, if you're enjoying the show, please be sure to subscribe to us on iTunes or your podcaster of choice, leave us a review on iTunes and drop us an email at podcast@engadget.com. You can also join us on our live [00:01:00] stream on Thursday mornings, typically around 11 a. m. Um, you'll see our faces. Sometimes we'll do Q& A and show off devices as well. This week, uh, Sherilyn has the iPhone 16e, which is the least, um, impressive thing to show off. It's just like, Hey, you have an iPhone from 10 years ago, five, a while ago, Devindra: last, was there a single camera back iPhone? Cherlynn: Oh God, before that was 11. So, you know, it's like a flashback. So let's talk about this thing, Sherlynn. And I checked out your review. First of all, you gave it a really, um, I think serviceable score. Your title is what's your acceptable compromise. And really when we were talking about it last week, it really was like compromise seemed like the key word. The thing we kept coming back to was like just one camera, no mag safe, no fast wireless charging. What are your overall thoughts on this thing? Cherlynn: I mean, so that headline is like all thanks to our EIC, Aaron [00:02:00]Souppouris, because I was like, where, where do I go from here? How do I, so, so he's right. It is like, instead of what's in your wallet, it's like, what are you willing to take out your wallet? I'll tell you the story. So yesterday I was at the Amazon devices and services event where there were no devices and A bunch of other reporters had gathered and we were all like, you know, the, like, review's going up soon, right?

If you want to know why Tyler Perry put an 800m ( 635m) expansion of his studio complex on hold, type "two people in a living room in the mountains" into OpenAI's video generation tool. The result from artificial intelligence-powered Sora, which was released in the UK and Europe on Friday, indicates why the US TV and film mogul paused his plans. Perry said last year after seeing previews of Sora that if he wanted to produce that mountain shot, he may not need to build sets on location or on his lot. "I can sit in an office and do this with a computer, which is shocking to me," he said. The result from a simple text prompt is only five seconds long – you can go to up to 20 seconds and also stitch together much longer videos from the tool – and the "actors" display telltale problems with their hands (a common problem with AI tools).

The last time someone groped Robert Pattinson aboard a spaceship, to the best of my knowledge, was in Claire Denis's 2018 movie, "High Life." The groper was a lowlife--a deranged doctor, bent on harvesting astronaut semen for pernicious procreative ends. Pattinson's character, a self-declared celibate, was unconscious and unconsenting. The assault took place on the grottiest of vessels, manned by violent criminals who had been banished into deep space. The movie was a hell of a dark trip, but Pattinson, among the most consistently adventurous actors of his generation, kept you tethered to the story with an almost gravitational force.

The'America's Got Talent' judge tells Fox News Digital why he doesn't like artificial intelligence technology in songwriting. Simon Cowell wants to see artists protected against AI. The "America's Got Talent" judge wrote commentary in The Daily Mail this week criticizing potential changes to U.K. law that would allow companies to use any online material to train AI models unless they explicitly opt out. Cowell warned that the livelihood of artists was at risk of "being wiped out." "The thought that anyone would believe they have the right to blindly give this country's creative ideas away – for nothing – is just wrong," he said.

San Francisco-based OpenAI is making Sora available to UK users who pay for ChatGPT. The tool stunned film-makers when it was revealed last year, with the film and TV mogul Tyler Perry pausing an 800m ( 634m) expansion of his Atlanta studio complex after saying the tool might make building sets or travelling to locations unnecessary. It was launched in the US publicly in December. Users are able to make videos on Sora by typing in simple prompts such as asking for a shot of people walking through "beautiful, snowy Tokyo city" where "gorgeous sakura petals are flying through the wind along with snowflakes". OpenAI announced the UK release as it released examples of Sora's use by artists from across the UK and mainland Europe, where the tool is also being released on Friday. Josephine Miller, a 25-year-old British digital artist, created a two-minute video of models wearing bioluminescent fauna and said the tool would "open a lot more doors for younger creatives".

While Large Language Models (LLMs) can amplify online misinformation, they also show promise in tackling misinformation. In this paper, we empirically study the capabilities of three LLMs -- ChatGPT, Gemini, and Claude -- in countering political misinformation. We implement a two-step, chain-of-thought prompting approach, where models first identify credible sources for a given claim and then generate persuasive responses. Our findings suggest that models struggle to ground their responses in real news sources, and tend to prefer citing left-leaning sources. We also observe varying degrees of response diversity among models. Our findings highlight concerns about using LLMs for fact-checking through only prompt-engineering, emphasizing the need for more robust guardrails. Our results have implications for both researchers and non-technical users.

The wide usage of LLMs raises critical requirements on detecting AI participation in texts. Existing studies investigate these detections in scattered contexts, leaving a systematic and unified approach unexplored. In this paper, we present HART, a hierarchical framework of AI risk levels, each corresponding to a detection task. To address these tasks, we propose a novel 2D Detection Method, decoupling a text into content and language expression. Our findings show that content is resistant to surface-level changes, which can serve as a key feature for detection. Experiments demonstrate that 2D method significantly outperforms existing detectors, achieving an AUROC improvement from 0.705 to 0.849 for level-2 detection and from 0.807 to 0.886 for RAID. We release our data and code at https://github.com/baoguangsheng/truth-mirror.

A key challenge in AI alignment is guiding large language models (LLMs) to follow desired behaviors at test time. Activation steering, which modifies internal model activations during inference, offers a potential solution. However, prior work in dense activation spaces struggles with superposition, wherein multiple features become entangled, limiting interpretability and precise control. In contrast, sparse representations provide an untapped opportunity for more interpretable behavior modulation. In this work, we introduce sparse activation steering (SAS), a method that leverages sparse autoencoders (SAEs) to steer LLM behavior in sparse spaces. By isolating behavior-specific features through a contrastive prompt-pairing approach, we define a set of features that can selectively reinforce or suppress behaviors. Experiments on Gemma 2 LLMs show that SAS vectors enable nuanced behavioral modulation and finer-grained control. Furthermore, scaling SAEs improves monosemanticity of SAS vectors, suggesting more reliable and interpretable interventions.

We introduce InspireMusic, a framework integrated super resolution and large language model for high-fidelity long-form music generation. A unified framework generates high-fidelity music, songs, and audio, which incorporates an autoregressive transformer with a super-resolution flow-matching model. This framework enables the controllable generation of high-fidelity long-form music at a higher sampling rate from both text and audio prompts. Our model differs from previous approaches, as we utilize an audio tokenizer with one codebook that contains richer semantic information, thereby reducing training costs and enhancing efficiency. This combination enables us to achieve high-quality audio generation with long-form coherence of up to $8$ minutes. Then, an autoregressive transformer model based on Qwen 2.5 predicts audio tokens. Next, we employ a super-resolution flow-matching model to generate high-sampling rate audio with fine-grained details learned from an acoustic codec model. Comprehensive experiments show that the InspireMusic-1.5B-Long model has a comparable performance to recent top-tier open-source systems, including MusicGen and Stable Audio 2.0, on subjective and objective evaluations. The code and pre-trained models are released at https://github.com/FunAudioLLM/InspireMusic.