Microsoft rolls out smarter semantic search and new Copilot home to insiders
The biggest new feature is the semantic file search which will be available on Copilot PCs. Unlike regular search, this feature lets you search for the files using a natural language. You can now type commands like 'find images of my pet on my PC' or 'find my CV' to locate the relevant files without needing to remember the exact name of the file or the location.
The search understands the file content and descriptions, making it convenient to find the documents or image files just by describing the content of them. Users can control what Copilot can see or cannot see on the PC from the permission settings.
The update also brings a new Coliot home screen experience that displays your recent apps, files and conversation right there when you open the Copilot app. It is also easier to get help, clicking the recent app starters a guided Vision session and clicking the recent file uploads it to the Copilot automatically and it can quickly summarize or analyse the content for you.
Copilot only shows files from your Windows 'Recent' folder, the files that you have recently accessed using apps like Word or Photos. It does not automatically scan your entire PC or upload any files automatically. Files will only appear on the home screen if they are compatible with the Copilot and recently used. You need to give permission if you want to share a file with Copilot for processing.
Users can use vision to get live help based on what's on the screen currently. Files can be uploaded to the chat for quick summaries, insights or assistance. This makes Copilot a versatile assistant for planning and catching up on work. If you want to try these new Copilot features right now then you need to signup for the Windows Insider and install the latest Insider build.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Hindustan Times
25 minutes ago
- Hindustan Times
AI-powered robots can take your phone apart
THE WORLD'S rubbish heaps are filling up with valuable electronics. According to the UN, some 62m tonnes of e-waste were produced in 2022, enough to fill a line of lorries parked bumper-to-bumper around the equator. Only 22% is recycled. Most of the rest ends up in landfills or incinerators, where in 2024 recoverable raw materials worth $63bn went to waste. That figure is expected to grow to more than $80bn by 2030. Getting those materials out of the rubbish is a challenge. Many are contaminated when e-waste is crushed during recycling, which can limit the effectiveness of specialist extraction techniques. The process is made more straightforward if products are disassembled and their components sorted by composition before crushing. Copper can then be recovered from wiring. Gold, silver and other precious metals can be leached from circuit boards, along with cobalt, lithium, manganese and nickel from batteries. Rare-earth magnets can be pulled from electric motors. The trouble is that disassembly is labour-intensive and costly. Automation is also tricky: robots are good at putting together a specific item but struggle to recognise and take apart the thousands of different devices that end up in the rubbish. A new generation of robots powered by artificial-intelligence (AI) models, however, looks to be up to the job. Some of these AI-assisted robots are being developed for in-house recycling schemes run by manufacturers, who have an intimate knowledge of how their products are put together. Apple, for example, uses a system called Daisy. A decade ago, an early version could dismantle only one type of iPhone; now, with the help of AI, Daisy can handle more than 20. Microsoft is developing a robot to disassemble computer hard drives. These are usually crushed whole to destroy any sensitive data, but if the drives are dismantled, only the platters containing data need be crushed. ABB, a Swedish-Swiss electrical-engineering group, is working with Molg, an American recycler, on a network of robotic 'minifactories' to dismantle and recover material from the electronics used in vast data centres. José Saenz and his team at the Fraunhofer Institute for Factory Operation and Automation in Magdeburg, Germany have a still more ambitious goal. They are developing a robotic system that can be used in a general recycling centre, where it would need to be flexible enough to dismantle a wide variety of e-waste, ranging from phones to electric-vehicle batteries, LED screens and solar panels. Their starting point is an AI-assisted robot that can disassemble old desktop PCs, many of which are more than a decade old. The first thing the team's robot does is identify any product it is offered. A camera photographs the item and compares the snap with pictures of different PCs. The robot also scans any labels and product codes to check whether service manuals or other disassembly tips are available online. It can search for other clues, in much the same way ChatGPT might, when asked a similar question, turn up videos posted online by people who have done the job before. All this information is analysed and stored in the robot's memory, where it can be updated and used for reference the next time such a product comes into the recycling centre. Once the identification is complete, the AI system then determines which components are worth removing, either in the form of raw materials or as complete parts to be refurbished and used again. It also checks the integrity of rivets, screws and other fasteners, because years of wear, tear and repair mean some parts may need to be cut out. Analysis done, the AI generates a disassembly sequence to operate the robot's arms. These are equipped with a selection of tools, such as drills, grippers and screwdrivers, to remove and sort items. So far, the team has got each stage in the disassembly process working in separate machines. They are now linking these together into a single robotic device able to complete the whole process. Once dismantling PCs has been mastered the team will train robots to tackle other products. The learning process will take time. Dr Saenz thinks it could be five years until they develop a commercial disassembly robot that could usefully work at a recycling centre taking apart anything from PCs to white goods and televisions. Firms that want to recycle their own, limited range of products could probably put together something more quickly. A multi-purpose robot would probably be popular, since companies are under increasingly fierce legislative pressure to take responsibility for the end-of-life management of their products, either directly or by employing specialists to recycle for them. The rise of smarter spanner-wielding robots, therefore, should encourage more firms to ensure their products are useful in death, as they were in life.
Economic Times
4 hours ago
- Economic Times
$30 billion down the drain? MIT says 95% of companies see no returns from Generative AI
AI return on investment: Despite significant investments in generative AI, a recent MIT study reveals that 95% of companies have seen no measurable profit gains. While firms are exploring tools like ChatGPT, their use is primarily limited to individual productivity enhancements. The study suggests AI's impact will initially focus on reducing outsourcing costs rather than causing job losses. Tired of too many ads? Remove Ads Widespread Use of AI Tools Hasn't Boosted Profits AI Models Still Can't Think or Learn Like Humans Tired of too many ads? Remove Ads AI Might Cut Outsourcing, Not Jobs False Expectations Are Driving AI Failures in Business Tired of too many ads? Remove Ads Where AI Works Best? FAQs : Since the last three years, companies around the world have invested between $30 billion and $40 billion into generative AI projects, but according to a new study from the Massachusetts Institute of Technology, 95% of the companies part of the study reported zero measurable gains from adopting AI tools, as per a MIT report revealed that only about 5% of integrated AI pilots have delivered millions in value, but for the vast majority, there has been no impact on revenue or earnings, according to The Daily Adda companies quickly began testing programs like ChatGPT, Copilot, and other large language models, and surveys show that over 80% of major firms have explored or piloted these tools, with nearly 40% deploying them to some degree, as per the report. Yet most of this use has been limited to helping individuals work faster rather than improving overall company profits, as reported by The Daily READ: Can ChatGPT help you get out of debt? What experts and users say about AI chatbots' financial advice One key problem is that generative AI tools often don't fit well with real work processes, according to the report. The MIT study described that the AI tools have 'brittle workflows, lack of contextual learning, and poor alignment with day-to-day operations,' according to The Daily generative AI models, unlike human beings, can't retain past feedback or build reasoning skills over time, and they also struggle to adapt to new contexts or apply lessons across different tasks, as per the MIT study highlighted that, 'Most GenAI systems do not retain feedback, adapt to context, or improve over time,' and without these traits, long-term integration remains costly and ineffective, as reported by The Daily the hype about generative AI has raised high expectations in boardrooms, but so far, investments have not led into better profits or meaningful cost savings, according to the report. Even though some companies use AI for customer service, marketing, or writing assistance, these tools mainly save time for workers without directly adding to business earnings, as per The Daily Adda READ: After billion-dollar hirings, Zuckerberg slams brakes on Meta's AI hiring spree as bubble fears shake Silicon Valley The MIT research also downplays fears of widespread job losses due to generative AI in the near future and rather, it suggests that AI's impact will be more about reducing external costs for companies, such as outsourcing, rather than cutting large numbers of jobs, according to the study highlighted that, 'Until AI systems achieve contextual adaptation and autonomous operation, organizational impact will manifest through external cost optimization rather than internal restructuring,' as quoted by The Daily note that many failures come from misunderstanding what AI can and cannot do, like AI can generate text or code quickly, but it cannot actually learn the way humans do, as per the report. Whereas, employees can adjust based on new instructions, past mistakes, and changing needs, but generative AI models cannot carry memory across tasks unless retrained, as reported by The Daily READ: Tech stocks tumble as investors flee — is the AI bubble finally about to burst? Despite ongoing interest from investors and executives, the short-term outlook points to slower progress than many expected, and the study suggests companies should view generative AI as a limited tool rather than a guaranteed driver of growth, according to the Study recommends focusing on narrow use cases where AI can bring immediate, measurable savings or productivity gains, like customer support scripts, coding aids, or document drafting as widespread AI integration is still premature and likely to fail, as reported by The Daily 95% of companies reported no measurable gains in profits or earnings from AI adoption, as per The Daily Adda immediately. The report says AI is more likely to cut external costs, such as outsourcing, than lead to mass layoffs right now.
Time of India
4 hours ago
- Time of India
$30 billion down the drain? MIT says 95% of companies see no returns from Generative AI
AI return on investment : Since the last three years, companies around the world have invested between $30 billion and $40 billion into generative AI projects, but according to a new study from the Massachusetts Institute of Technology, 95% of the companies part of the study reported zero measurable gains from adopting AI tools, as per a report. Widespread Use of AI Tools Hasn't Boosted Profits The MIT report revealed that only about 5% of integrated AI pilots have delivered millions in value, but for the vast majority, there has been no impact on revenue or earnings, according to The Daily Adda report. Many companies quickly began testing programs like ChatGPT, Copilot, and other large language models, and surveys show that over 80% of major firms have explored or piloted these tools, with nearly 40% deploying them to some degree, as per the report. Yet most of this use has been limited to helping individuals work faster rather than improving overall company profits, as reported by The Daily Adda. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like With temperatures hitting 95°F, this is the mini air conditioner everyone's buying in the U.S News of the Discovery Undo ALSO READ: Can ChatGPT help you get out of debt? What experts and users say about AI chatbots' financial advice AI Models Still Can't Think or Learn Like Humans One key problem is that generative AI tools often don't fit well with real work processes, according to the report. The MIT study described that the AI tools have 'brittle workflows, lack of contextual learning, and poor alignment with day-to-day operations,' according to The Daily Adda. Live Events Most generative AI models, unlike human beings, can't retain past feedback or build reasoning skills over time, and they also struggle to adapt to new contexts or apply lessons across different tasks, as per the report. The MIT study highlighted that, 'Most GenAI systems do not retain feedback, adapt to context, or improve over time,' and without these traits, long-term integration remains costly and ineffective, as reported by The Daily Adda. While the hype about generative AI has raised high expectations in boardrooms, but so far, investments have not led into better profits or meaningful cost savings, according to the report. Even though some companies use AI for customer service, marketing, or writing assistance, these tools mainly save time for workers without directly adding to business earnings, as per The Daily Adda report. ALSO READ: After billion-dollar hirings, Zuckerberg slams brakes on Meta's AI hiring spree as bubble fears shake Silicon Valley AI Might Cut Outsourcing, Not Jobs The MIT research also downplays fears of widespread job losses due to generative AI in the near future and rather, it suggests that AI's impact will be more about reducing external costs for companies, such as outsourcing, rather than cutting large numbers of jobs, according to the report. The study highlighted that, 'Until AI systems achieve contextual adaptation and autonomous operation, organizational impact will manifest through external cost optimization rather than internal restructuring,' as quoted by The Daily Adda. Experts note that many failures come from misunderstanding what AI can and cannot do, like AI can generate text or code quickly, but it cannot actually learn the way humans do, as per the report. Whereas, employees can adjust based on new instructions, past mistakes, and changing needs, but generative AI models cannot carry memory across tasks unless retrained, as reported by The Daily Adda. ALSO READ: Tech stocks tumble as investors flee — is the AI bubble finally about to burst? False Expectations Are Driving AI Failures in Business Despite ongoing interest from investors and executives, the short-term outlook points to slower progress than many expected, and the study suggests companies should view generative AI as a limited tool rather than a guaranteed driver of growth, according to the report. Where AI Works Best? The Study recommends focusing on narrow use cases where AI can bring immediate, measurable savings or productivity gains, like customer support scripts, coding aids, or document drafting as widespread AI integration is still premature and likely to fail, as reported by The Daily Adda. FAQs Did most companies see any business return from AI? No. 95% of companies reported no measurable gains in profits or earnings from AI adoption, as per The Daily Adda report. Will AI take people's jobs? Not immediately. The report says AI is more likely to cut external costs, such as outsourcing, than lead to mass layoffs right now.
