Microsoft 365 is a subscription service that offers a suite of productivity and collaboration tools for individuals, businesses, and organizations. With Microsoft 365, you can access the latest versions of Office apps such as Word, Excel, PowerPoint, Outlook, and more, as well as cloud services such as OneDrive, SharePoint, Teams, and Exchange. You can also get advanced security features, device management, and support from Microsoft experts.
Microsoft 365 is designed to help you achieve more with innovative apps, intelligent cloud services, and world-class security. Whether you need to create professional documents, manage projects, communicate with your team, or secure your data, Microsoft 365 has a plan that suits your needs and budget. You can choose from different plans for personal use, home and family, small and medium businesses, large enterprises, education, and non-profit organizations.
Microsoft 365 is more than just Office apps. It’s a comprehensive solution that empowers you to work smarter, faster, and more securely. You can access your files and apps from any device, collaborate with anyone in real time, and stay productive with AI-powered features. You can also customize your experience with add-ons and integrations from Microsoft and third-party partners.
If you want to learn more about Microsoft 365 and how it can benefit you or your organization, visit the official website or contact a Microsoft representative. You can also sign up for a free trial or buy a subscription online. Microsoft 365 is the ultimate productivity solution for the modern workplace.
Microsoft has announced a major update to its cloud storage service, OneDrive, that brings a new design and improved consumer features. The new design, previously available only for business users, is now rolling out to all OneDrive users across the web, mobile, and desktop platforms.
The new OneDrive design aims to make it easier and faster for users to access and manage their files, photos, and videos in the cloud. Some of the key changes include:
A simplified navigation bar that lets users switch between files, recent, shared, and recycle bin views with one click.
A new command bar that shows contextual actions based on the selected items, such as share, download, delete, and more.
A revamped details pane that shows more information about the selected items, such as file size, date modified, sharing status, and activity history.
A new photo view that automatically organizes photos by date and location, and lets users create albums, slideshows and edit photos with built-in tools.
A new video player that supports streaming and downloading of high-quality videos, and lets users trim, rotate, and add captions to videos with built-in tools.
A new personal vault feature lets users store their most sensitive files in a secure folder requiring an extra layer of authentication to access.
Microsoft says that the new OneDrive design will enhance the user experience and productivity of its cloud storage service, which currently has over 250 million active users. The update will also bring OneDrive in line with the Fluent Design System, Microsoft’s design language for its products and services.
The new OneDrive design is rolling out gradually to all users over the next few weeks. Users can check for updates in their OneDrive settings or visit the OneDrive website to try out the new design.
Artificial intelligence (AI) is transforming the healthcare industry in unprecedented ways. From diagnosis to treatment, from research to management, AI is enabling new possibilities and improving outcomes. Here are five things to expect from AI in healthcare in 2024:
AI will augment human doctors, not replace them. AI can assist doctors with tasks such as analyzing medical images, generating reports, recommending treatments, and monitoring patients. However, AI cannot replace the human touch, empathy, and ethical judgment that doctors provide. AI will enhance the capabilities of doctors, not threaten their jobs.
AI will personalize medicine and improve patient experience. AI can help tailor treatments and interventions to each patient’s specific needs and preferences. For example, AI can use genomic data to identify the best drugs for a patient or use behavioral data to nudge a patient to adhere to a treatment plan. AI can also improve patient experience by providing chatbots, virtual assistants, and telemedicine services.
AI will accelerate drug discovery and development. AI can help discover new drugs and test their efficacy and safety faster and cheaper than traditional methods. For example, AI can use natural language processing to mine scientific literature, use computer vision to screen compounds, use machine learning to predict drug interactions use deep learning to design new molecules.
AI will improve healthcare operations and efficiency. AI can help optimize healthcare processes and resources, such as scheduling appointments, managing inventory, allocating staff, and reducing waste. For example, AI can use predictive analytics to forecast demand, use reinforcement learning to optimize workflows, use computer vision to monitor equipment use natural language processing to automate documentation.
AI will democratize healthcare access and quality. AI can help overcome the barriers of cost, distance, and availability that prevent many people from accessing quality healthcare. For example, AI can provide low-cost diagnostic tools, remote consultation services, and online education platforms that can reach underserved populations and regions.
The tech world is buzzing with excitement after Microsoft unveiled its latest device at the Consumer Electronics Show (CES) 2024. The device, which has not been named yet, is a hybrid of a laptop, a tablet, and a smartphone, and promises to revolutionize the way we work, play, and communicate.
The device features a flexible OLED screen that can fold and unfold into different shapes and sizes, depending on the user’s needs. It can also detach from the keyboard and function as a standalone tablet or phone. The device runs on Windows 11, the most advanced operating system from Microsoft, and supports 5G connectivity, wireless charging, and biometric security.
Microsoft claims that the device is the most powerful and versatile gadget ever created, and that it will offer an unparalleled user experience. The device is expected to hit the market later this year, with a price tag of around $2,000. Microsoft says that it will reveal more details about the device in the coming months.
If you are a fan of Microsoft products, or if you are looking for a new gadget that can do it all, you might want to keep an eye on this device. It could be the next big thing in the tech industry, and you don’t want to miss it!
The term “AI” has been used in computer science since the 1950s, but most people outside the industry didn’t start talking about it until the end of 2022. That’s because recent advances in machine learning led to big breakthroughs that are beginning to have a profound impact on nearly every aspect of our lives. We’re here to help break down some of the buzzwords so you can better understand AI terms and be part of the global conversation.
Artificial intelligence Artificial intelligence is basically a super-smart computer system that can imitate humans in some ways, like comprehending what people say, making decisions, translating between languages, analyzing if something is negative or positive, and even learning from experience. It’s artificial in that its intellect was created by humans using technology. Sometimes people say AI systems have digital brains, but they’re not physical machines or robots — they’re programs that run on computers. They work by putting a vast collection of data through algorithms, which are sets of instructions, to create models that can automate tasks that typically require human intelligence and time. Sometimes people specifically engage with an AI system — like asking Bing Chat for help with something — but more often the AI is happening in the background all around us, suggesting words as we type, recommending songs in playlists and providing more relevant information based on our preferences.
Machine learning If artificial intelligence is the goal, machine learning is how we get there. It’s a field of computer science, under the umbrella of AI, where people teach a computer system how to do something by training it to identify patterns and make predictions based on them. Data is run through algorithms over and over, with different input and feedback each time to help the system learn and improve during the training process — like practicing piano scales 10 million times in order to sight-read music going forward. It’s especially helpful with problems that would otherwise be difficult or impossible to solve using traditional programming techniques, such as recognizing images and translating languages. It takes a huge amount of data, and that’s something we’ve only been able to harness in recent years as more information has been digitized and as computer hardware has become faster, smaller, more powerful and better able to process all that information. That’s why large language models that use machine learning — such as Bing Chat and ChatGPT — have suddenly arrived on the scene.
Large language models Large language models, or LLMs, use machine learning techniques to help them process language so they can mimic the way humans communicate. They’re based on neural networks, or NNs, which are computing systems inspired by the human brain — sort of like a bunch of nodes and connections that simulate neurons and synapses. They are trained on a massive amount of text to learn patterns and relationships in language that help them use human words. Their problem-solving capabilities can be used to translate languages, answer questions in the form of a chatbot, summarize text and even write stories, poems and computer code. They don’t have thoughts or feelings, but sometimes they sound like they do, because they’ve learned patterns that help them respond the way a human might. They’re
often fine-tuned by developers using a process called reinforcement learning from human feedback (RLHF) to help them sound more conversational.
Generative AI Generative AI leverages the power of large language models to make new things, not just regurgitate or provide information about existing things. It learns patterns and structures and then generates something that’s similar but new. It can make things like pictures, music, text, videos and code. It can be used to create art, write stories, design products and even help doctors with administrative tasks. But it can also be used by bad actors to create fake news or pictures that look like photographs but aren’t real, so tech companies are working on ways to clearly identify AI-generated content.
Hallucinations Generative AI systems can create stories, poems and songs, but sometimes we want results to be based in truth. Since these systems can’t tell the difference between what’s real and fake, they can give inaccurate responses that developers refer to as hallucinations or confabulations — much like if someone saw what looked like the outlines of a face on the moon and began saying there was an actual man in the moon. Developers try to resolve these issues through “grounding,” which is when they provide an AI system with additional information from a trusted source to improve accuracy about a specific topic. Sometimes a system’s predictions are wrong, too, if a model doesn’t have current l doesn’t have current information after it’s trained.
Responsible AI Responsible AI guides people as they try to design systems that are safe and fair — at every level, including the machine learning model, the software, the user interface and the rules and restrictions put in place to access an application. It’s a crucial element because these systems are often tasked with helping make important decisions about people, such as in education and healthcare, but since they’re created by humans and trained on data from an imperfect world, they can reflect any inherent biases. A big part of responsible AI involves understanding the data that was used to train the systems and finding ways to mitigate any shortcomings to help better reflect society at large, not just certain groups of people.
Multimodal models A multimodal model can work with different types, or modes, of data simultaneously. It can look at pictures, listen to sounds and read words. It’s the ultimate multitasker! It can combine all of this information to do things like answer questions about images.
Prompts A prompt is an instruction entered into a system in language, images or code that tells the AI what task to perform. Engineers — and really all of us who interact with AI systems — must carefully design prompts to get the desired outcome from the large language models. It’s like placing your order at a deli counter: You don’t just ask for a sandwich, but you specify which bread you want and the type and amounts of condiments, vegetables, cheese and meat to get a lunch that you’ll find delicious and nutritious.
Copilots A copilot is like a personal assistant that works alongside you in all sorts of digital applications, helping with things like writing, coding, summarizing and searching. It can also help you make decisions and understand lots of data. The recent development of large language models made copilots possible, allowing them to comprehend natural human language and provide answers, create content or take action as you work within different computer programs. Copilots are built with Responsible AI guardrails to make sure they’re safe and secure and are used in a good way. Just like a copilot in an airplane, it’s not in charge — you are — but it’s a tool that can help you be more productive and efficient.
Plugins Plugins are like relief pitchers in baseball — they step in to fill specific needs that might pop up as the game develops, such as putting in a left-handed pitcher when a left-handed hitter steps up to the plate for a crucial at-bat. Plugins enable AI applications to do more things without having to modify the underlying model. They are what allow copilots to interact with other software and services, for example. They can help AI systems access new information, do complicated math or talk to other programs. They make AI systems more powerful by connecting them to the rest of the digital world.
