Copilot Vision Lets AI See Your Windows 11 Screen and Guide You in Real Time
Microsoft has released Copilot Vision on Windows, a new AI tool that lets you share what's visible on your screen with the AI and talk to it simultaneously. Copilot can analyze what you see on your screen, answer your questions, and guide you as you work with different apps and tasks.
The system lets you share up to two apps or windows at a time, so Copilot can gain context from multiple sources and help you connect information across different platforms.
With the new Highlights feature, you can ask Copilot to help you with tasks by saying, 'Show me how.' Copilot will then indicate where to click and what steps to follow in an app. This makes it easier to learn new software or finish tasks you're not familiar with. Imagine being a first-time Photoshop user or using some complex video-editing tool with this superpower.
Activating Copilot Vision is fully optional. The company said you're in control of which windows to share and can stop at any time.
Copilot Vision on Windows is currently available for US-based users. The company expects to soon bring it to quite a few non-European countries.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
12 minutes ago
- Yahoo
Sword Health Now Valued At $4 Billion, Announces Expansion Into Mental Health Services
Sword Health announced Tuesday that it had raised $40 million in a recent funding round, giving it a $4 billion valuation. Founded in 2015, the healthcare startup has focused on helping people manage chronic pain at home. Using AI tools, the platform connects users with expert clinicians who then provide patients with tools for digital physical therapy, pelvic health, and overall mobility health. However, the company says this new round of funding will largely go towards developing a mental health arm of its program called Mind. Don't Miss: Maker of the $60,000 foldable home has 3 factory buildings, 600+ houses built, and big plans to solve housing — Peter Thiel turned $1,700 into $5 billion—now accredited investors are eyeing this software company with similar breakout potential. Learn how you can "Today, nearly 1 billion people worldwide live with a mental health condition. Yet care remains fragmented, reactive, and inaccessible," Sword said in the announcement. "Mind redefines mental health care delivery with a proactive, 24/7 model that integrates cutting-edge AI with licensed, Ph.D-level mental health specialists. Together, they provide seamless, contextual, and responsive support any time people need it, not just when they have an appointment." Sword CEO Virgílio Bento told CNBC, "[Mind] really a breakthrough in terms of how we address mental health, and this is only possible because we have AI." Users will be equipped with a wearable device called an M-band, which will measure their environmental and physiological signals so that experts can reach out proactively as needed. The program will also offer access to services like traditional talk therapy. Bento told CNBC that a human is "always involved" in patients care in each of its programs, and that AI is not making any clinical decisions. Trending: Maximize saving for your retirement and cut down on taxes: . For example, if a Sword patient has an anxiety attack, AI will identify it through the wearable and bring it to the attention of a clinician, who can then provide an appropriate care plan. "You have an anxiety issue today, and the way you're going to manage is to talk about it one week from now? That just doesn't work," Bento told CNBC. "Mental health should be always on, where you have a problem now, and you can have immediate help in the moment." According to Bento, Sword Mind already has a waiting list, and is being tested by some of its partners who appreciate it's "personalized approach and convenience." "We believe that it is really the future of how mental health is going to be delivered in the future, by us and by other companies," he told CNBC. "AI plays a very important role, but the use of AI — and I think this is very important — needs to be used in a very smart way." The rest of the cash raised in the funding round, which was led by General Catalyst, will go towards acquisitions, global expansion, and AI development, Sword Health says. Read Next: Here's what Americans think you need to be considered Shutterstock UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? APPLE (AAPL): Free Stock Analysis Report TESLA (TSLA): Free Stock Analysis Report This article Sword Health Now Valued At $4 Billion, Announces Expansion Into Mental Health Services originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Tom's Guide
an hour ago
- Tom's Guide
Windows parental controls are crashing Chrome — here's the workaround
Windows 11's Family Safety feature is supposed to block certain websites from children, but apparently it's also been causing issues with Google's Chrome browser, a (vastly more popular) competitor to Microsoft's own Edge. The problem first surfaced on Windows on June 3, per The Verge, when several users started noticing they couldn't open Chrome or their browser would crash randomly. Restarting their computer or reinstalling Chrome didn't fix the issue, and other browsers like Firefox and Opera appeared unaffected. On Monday, a Google spokesperson posted in the company's community forum that it had investigated these reports and found the issues were linked to Microsoft's new Windows Family Safety feature. This optional feature is primarily used by parents and schools to manage children's screen time, filter their web browsing, and monitor their online activity. Curiously, the bug has been going on for weeks now, and Microsoft still hasn't issued a patch. 'We've not heard anything from Microsoft about a fix being rolled out,' wrote a Chromium engineer in a bug tracking thread on June 10. 'They have provided guidance to users who contact them about how to get Chrome working again, but I wouldn't think that would have a large effect.' While this issue could be an innocent bug, Microsoft has a history of placing annoying hurdles between Edge and Chrome to entice users to stick with its browser. So anytime a technical snafu makes Chrome run worse on Windows PCs, Microsoft understandably gets some serious side eye. Thankfully, there seem to be two ways to get around this bug while we wait for Microsoft to issue a fix, and they're both fairly simple. The most straightforward is to turn off the "Filter Inappropriate Websites" setting. Head to the Family Safety mobile app or Family Safety web portal, select a user's account, and choose to disable "Filter inappropriate websites" under the Edge tab. However, that'll remove the guardrails on Chrome and let your child access any website, including the ones you were trying to block in the first place. Get instant access to breaking news, the hottest reviews, great deals and helpful tips. If you want to keep the guardrails on and still use Chrome, some users reported that altering the name in your Chrome folder (to something like Chrome1, for example), got the browser to work again even with the Family Safety feature enabled.
Yahoo
an hour ago
- Yahoo
Why is AI halllucinating more frequently, and how can we stop it?
When you buy through links on our articles, Future and its syndication partners may earn a commission. The more advanced artificial intelligence (AI) gets, the more it "hallucinates" and provides incorrect and inaccurate information. Research conducted by OpenAI found that its latest and most powerful reasoning models, o3 and o4-mini, hallucinated 33% and 48% of the time, respectively, when tested by OpenAI's PersonQA benchmark. That's more than double the rate of the older o1 model. While o3 delivers more accurate information than its predecessor, it appears to come at the cost of more inaccurate hallucinations. This raises a concern over the accuracy and reliability of large language models (LLMs) such as AI chatbots, said Eleanor Watson, an Institute of Electrical and Electronics Engineers (IEEE) member and AI ethics engineer at Singularity University. "When a system outputs fabricated information — such as invented facts, citations or events — with the same fluency and coherence it uses for accurate content, it risks misleading users in subtle and consequential ways," Watson told Live Science. Related: Cutting-edge AI models from OpenAI and DeepSeek undergo 'complete collapse' when problems get too difficult, study reveals The issue of hallucination highlights the need to carefully assess and supervise the information AI systems produce when using LLMs and reasoning models, experts say. The crux of a reasoning model is that it can handle complex tasks by essentially breaking them down into individual components and coming up with solutions to tackle them. Rather than seeking to kick out answers based on statistical probability, reasoning models come up with strategies to solve a problem, much like how humans think. In order to develop creative, and potentially novel, solutions to problems, AI needs to hallucinate —otherwise it's limited by rigid data its LLM ingests. "It's important to note that hallucination is a feature, not a bug, of AI," Sohrob Kazerounian, an AI researcher at Vectra AI, told Live Science. "To paraphrase a colleague of mine, 'Everything an LLM outputs is a hallucination. It's just that some of those hallucinations are true.' If an AI only generated verbatim outputs that it had seen during training, all of AI would reduce to a massive search problem." "You would only be able to generate computer code that had been written before, find proteins and molecules whose properties had already been studied and described, and answer homework questions that had already previously been asked before. You would not, however, be able to ask the LLM to write the lyrics for a concept album focused on the AI singularity, blending the lyrical stylings of Snoop Dogg and Bob Dylan." In effect, LLMs and the AI systems they power need to hallucinate in order to create, rather than simply serve up existing information. It is similar, conceptually, to the way that humans dream or imagine scenarios when conjuring new ideas. However, AI hallucinations present a problem when it comes to delivering accurate and correct information, especially if users take the information at face value without any checks or oversight. "This is especially problematic in domains where decisions depend on factual precision, like medicine, law or finance," Watson said. "While more advanced models may reduce the frequency of obvious factual mistakes, the issue persists in more subtle forms. Over time, confabulation erodes the perception of AI systems as trustworthy instruments and can produce material harms when unverified content is acted upon." And this problem looks to be exacerbated as AI advances. "As model capabilities improve, errors often become less overt but more difficult to detect," Watson noted. "Fabricated content is increasingly embedded within plausible narratives and coherent reasoning chains. This introduces a particular risk: users may be unaware that errors are present and may treat outputs as definitive when they are not. The problem shifts from filtering out crude errors to identifying subtle distortions that may only reveal themselves under close scrutiny." Kazerounian backed this viewpoint up. "Despite the general belief that the problem of AI hallucination can and will get better over time, it appears that the most recent generation of advanced reasoning models may have actually begun to hallucinate more than their simpler counterparts — and there are no agreed-upon explanations for why this is," he said. The situation is further complicated because it can be very difficult to ascertain how LLMs come up with their answers; a parallel could be drawn here with how we still don't really know, comprehensively, how a human brain works. In a recent essay, Dario Amodei, the CEO of AI company Anthropic, highlighted a lack of understanding in how AIs come up with answers and information. "When a generative AI system does something, like summarize a financial document, we have no idea, at a specific or precise level, why it makes the choices it does — why it chooses certain words over others, or why it occasionally makes a mistake despite usually being accurate," he wrote. The problems caused by AI hallucinating inaccurate information are already very real, Kazerounian noted. "There is no universal, verifiable, way to get an LLM to correctly answer questions being asked about some corpus of data it has access to," he said. "The examples of non-existent hallucinated references, customer-facing chatbots making up company policy, and so on, are now all too common." Both Kazerounian and Watson told Live Science that, ultimately, AI hallucinations may be difficult to eliminate. But there could be ways to mitigate the issue. Watson suggested that "retrieval-augmented generation," which grounds a model's outputs in curated external knowledge sources, could help ensure that AI-produced information is anchored by verifiable data. "Another approach involves introducing structure into the model's reasoning. By prompting it to check its own outputs, compare different perspectives, or follow logical steps, scaffolded reasoning frameworks reduce the risk of unconstrained speculation and improve consistency," Watson, noting this could be aided by training to shape a model to prioritize accuracy, and reinforcement training from human or AI evaluators to encourage an LLM to deliver more disciplined, grounded responses. RELATED STORIES —AI benchmarking platform is helping top companies rig their model performances, study claims —AI can handle tasks twice as complex every few months. What does this exponential growth mean for how we use it? —What is the Turing test? How the rise of generative AI may have broken the famous imitation game "Finally, systems can be designed to recognise their own uncertainty. Rather than defaulting to confident answers, models can be taught to flag when they're unsure or to defer to human judgement when appropriate," Watson added. "While these strategies don't eliminate the risk of confabulation entirely, they offer a practical path forward to make AI outputs more reliable." Given that AI hallucination may be nearly impossible to eliminate, especially in advanced models, Kazerounian concluded that ultimately the information that LLMs produce will need to be treated with the "same skepticism we reserve for human counterparts."
