Author: Blog Poster

Thanks to cloud technology, researchers can take advantage of faster, more advanced and more scalable resources that enable them to perform tasks that they can’t manage using in-house resources. The cloud also enables scientists to quickly run tests across a variety of platforms and virtual machines with different specifications, which can aid rapid prototyping, interoperability testing, and performance testing. A cloud solution can also provide researchers with ways to augment their existing resources by handling peaks in demand and reducing competition for local resources, when multiple teams are working toward an upcoming deadline. By reducing dependence on on-site computing, research projects can increase efficiency and scalability, and deliver greater results faster.

Watch this video to learn how Australian National University (ANU) is using Microsoft Azure to help decode more than 7 billion base pairs of DNA in the human genome and take its research further than ever before.

Thanks to AI, business applications will soon be able to answer complex questions, help users navigate interfaces, and enable cloud vendors to reduce support from personnel to manage their loads. AI is also being used in various software applications to help decision-makers identify and automate repetitive tasks, improving employee productivity. Increased understanding of how to better implement AI in business applications likely will lead to the emergence of new features, such as natural-language processing (NLP), that can help managers interact in more-intuitive ways with AI-powered apps.

In this article, you’ll learn about the innovative features powered by AI and machine learning (ML) that you can expect to see in business applications in the next five years.

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In recent years, the global business landscape has witnessed a significant increase in cloud adoption. This has created significant value over traditional datacenters via greater scalability, cost-efficiency, and other performance improvements. Yet cloud migration requires careful planning. For a migration to be successful, it’s important for the business to come up with a strategy that also covers the end cloud environment, training, and—most importantly—the readiness of workloads and applications.

In this eBook, you’ll discover the key preliminary steps to consider in evaluating a cloud migration, as well as the various approaches for rehosting, refactoring, rearchitecting, and rebuilding your workloads for the cloud. You’ll also learn about some useful tools that you can use to accelerate your migration project and get tips to help you ensure post-migration success by using Microsoft Azure.

View: Cloud migration essentials

For modern organizations to truly take advantage of digital transformation, they need to be able to obtain, process, and extract insights from as much data as possible. This often puts a strain on businesses’ IT departments as they struggle to update legacy software and equipment to better handle the massive amounts of information available. Fortunately, the cloud has allowed businesses to move away from outdated technology and opened new opportunities for innovation.

Subscribe now to learn how the cloud, AI, and the data management capabilities of Microsoft Azure are driving increased efficiency at today’s leading businesses and organizations.

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Data is vital to scientific research. Without the ability to quickly process and analyze large amounts of data, breakthroughs and publications take longer. This increases administrative tasks and can even lead to projects going over budget. To avoid these pitfalls, modern researchers have begun turning to artificial intelligence (AI) and cloud-based technology, which enable the researchers to avoid the time and expense of setting up and configuring servers, leaving them to focus on their scientific goals.

In this video, you’ll see how researchers at Australian National University (ANU) conduct cutting-edge genome research by using Microsoft Azure to commission a data science virtual machine that allows them to instantly process large amounts of data. You’ll also learn how, thanks to the data management capabilities of Azure, ANU is now able to use unprecedented volumes of data and new analytical frameworks to decrease admin time and maximize the university’s research capabilities.

As scientific research becomes more and more complex, scientists need new, scalable ways to store and analyze ever-larger troves of data. They also need unprecedented amounts of raw computing power to process the data they obtain and deliver timely results that enable projects to stay on track and within budget. To ensure that their research adheres to these restraints, modern-day scientists need to increase efficiency via automation and other approaches whenever they can, wherever they can. Artificial intelligence (AI) and cloud technology give scientists the tools they need to advance research faster than ever before, get results quicker, and achieve scientific breakthroughs like never before.

In this video, you’ll learn how researchers at Australian National University (ANU) are using Microsoft Azure to dramatically shorten the amount of time they spend on data analysis, enabling faster publication of their cutting-edge genome research.

As the world’s population increases, farmers need to keep up with rising demand for their crops and livestock. But with climate conditions changing and resources becoming more precious, it’s critical for modern farms to seek innovative solutions that allow them to upscale their production without increasing their impact on the environment.

Subscribe now to learn how digital solutions powered by Microsoft Azure can be leveraged across both large-scale and small independent farming operations to increase yields and create a more-sustainable industry.

View: Create a more-productive, self-sustaining farm. Get started with Microsoft Azure AI.

In many regions of Africa, climate change has had a profound impact on independent farmers, especially those in isolated areas who lack proper access to running water. Dry seasons are increasingly longer and rains scarcer, making maintaining crops a bigger and bigger challenge with each passing year. For these farmers, traditional methods that were handed down for generations no longer yield the results they need to feed their families, leaving them in a desperate situation. Fortunately, modern technology and digital transformation are now able to provide these farmers with the tools they need to sustain their way of life during these challenging times.

In this video, you’ll learn how Monica, an independent farmer in Kenya, managed to overcome hardships brought on by climate change by using sustainable energy, accurate weather data, and Microsoft Azure.

As societies and workplaces become more digitized, our culture does, too. This daily interaction with technology engenders fascination and speculation about the role devices and technological advancements will play in our societies’ future. Some—if not most— of these assumptions are based on artistic portrayals of the future of technologies such as artificial intelligence (AI), and they are often far from providing an accurate representation of what actually awaits us in the realm of AI and machine learning.

Read this article to uncover the truth behind 12 misconceptions about AI and get a more accurate view of the present and future capabilities of this technology.

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Digital transformation has enabled businesses to reduce costs, streamline operations, embrace entirely new business models, and discover untapped revenue channels. Many of these benefits come from implementing data-driven technologies, including machine learning (ML) and artificial intelligence (AI), that transform the increasing amounts of data produced by today’s organizations into useful insights that can foster new strategies. Despite the massive potential of these technologies, only 37 percent of businesses that adopt them report successful initiatives.

In this infographic, you’ll learn about the main challenges that modern organizations face in implementing AI and ML, and how you can overcome them by using Microsoft Azure AI.

View: The main challenges of advanced analytics