Digital evidence appears in nearly 90 percent of all crimes committed today.1 This is a massive increase. Only 20 years ago it was unusual to have digital evidence at the center of a case. It is now a big part of what juries and judges expect to see as part of the evidence that proves innocence or guilt. To learn more about how Microsoft technology can help, visit our booth 5410 at the International Association of Chiefs of Police (IACP) Annual Conference 2022 in Dallas, Texas from October 15 to 18.

Contact centres for financial institutions have traditionally been a core touch point for customers to access various types of immediate support – from queries to complaints to fraud alerting. Today their role hasn't necessarily changed. However, the value organisations place on them certainly has. The focus is shifting from fitting customers around business processes to reshaping contact centres around customers' needs. For years, the role of contact centres was limited – often confined by traditional 9-5 working hours. It was predominantly aimed at driving down costs and improving efficiencies.

Azure Machine Learning provides an environment to create and manage the end-to-end life cycle of Machine Learning models. Azure Machine Learning's compatibility with open-source frameworks and platforms like PyTorch and TensorFlow makes it an effective all-in-one platform for integrating and handling data and models. Azure Machine Learning is designed for all skill levels, with advanced MLOps features and simple no-code model creation and deployment. Azure Machine Learning (Azure ML) is a cloud-based environment where you can build and manage machine learning models. It's designed to govern the entire ML life cycle, so you can train and deploy models without focusing on setup.

Today marks the start of RSNA 2020, the annual meeting of the Radiological Society of North America. I participated in my first RSNA 35 years ago and I am super excited--as I am every year--to reconnect with my radiology colleagues and friends and learn about the latest medical and scientific advances in our field. Of course, RSNA will be very different this year. Instead of traveling to Chicago to attend sessions and presentations, and wander the exhibits, I'll experience it all online. While I will miss the fun, excitement, and opportunities to connect that come with being there in person, I am amazed by what a rich and comprehensive conference the organizers of RSNA 2020 have put together using the advanced digital tools that we have at hand now.

AI presents incredible opportunities for organizations to change the way they do business. With 1,000 researchers--including winners of the Turing Award and Fields Medal--in 11 labs, Microsoft has established itself as a leader in AI through its dogged focus on innovation, empowerment, and ethics. Now, the groundbreaking capabilities of AI can move beyond the lab to make a positive impact on every enterprise, every industry. Manufacturers have accrued vast stores of data through digital technologies and IoT--offering new windows into operational efficiency and business performance. Culling that data for actionable insights on predictive maintenance and performance improvements has become increasingly essential for an industry that operates on thin margins.

Today at our flagship technology event, Future Decoded, we announced the launch of the Microsoft UK AI for Good 2020 accelerator programme to help UK purpose-driven ventures advance their AI solutions and create positive social change. Now in its second year, the Accelerator builds on last year's success, which saw 11 organisations graduate, all of whom reported positive impact on their business following the programme. Unveiled this morning by our Chief Environmental Officer Dr Lucas Joppa, the UK AI for Good Accelerator will be run by Microsoft for Startups and the Social Tech Trust from our accelerator space in Shoreditch, London. "AI is one of the most important tools we have to accelerate innovation at the speed and scale we need to address climate change and other important societal challenges. It's exciting to see Microsoft's AI for Good initiative evolving to engage new partners and help catalyse social impact organisations across the UK." "We have an exciting opportunity to help more social tech ventures to shape the future we want to see, using AI. I'm inspired by the growth we've seen from the 11 ventures in our first cohort and can't wait to see the very best UK social tech innovations that emerge as we open applications for our second AI for Good programme, in partnership with Microsoft."

Today at our flagship technology event, Future Decoded, we announced the launch of the Microsoft UK AI for Good 2020 accelerator programme to help UK purpose-driven ventures advance their AI solutions and create positive social change. Now in its second year, the Accelerator builds on last year's success, which saw 11 organisations graduate, all of whom reported positive impact on their business following the programme. Unveiled this morning by our Chief Environmental Officer Dr Lucas Joppa, the UK AI for Good Accelerator will be run by Microsoft for Startups and the Social Tech Trust from our accelerator space in Shoreditch, London. "AI is one of the most important tools we have to accelerate innovation at the speed and scale we need to address climate change and other important societal challenges. It's exciting to see Microsoft's AI for Good initiative evolving to engage new partners and help catalyse social impact organisations across the UK." "We have an exciting opportunity to help more social tech ventures to shape the future we want to see, using AI. I'm inspired by the growth we've seen from the 11 ventures in our first cohort and can't wait to see the very best UK social tech innovations that emerge as we open applications for our second AI for Good programme, in partnership with Microsoft."

At this juncture in the early stages of the AI-powered Fourth Industrial Revolution, a lot of attention has been paid to the possibility that millions of workers will be displaced by automation and robots, raising fears of rising unemployment in the years ahead. However, in the manufacturing industry today, the problem is not one of too many people chasing too few jobs-- it's the opposite. Manufacturing is being transformed by technology at a dramatic pace at a time of near-record low levels of unemployment, leading to a shortage of workers with the required skills for the new era of intelligent manufacturing. Currently, the U.S. Bureau of Labor Statistics (BLS) reports that there are more than half a million unfilled manufacturing jobs in the United States. This gap is expected to widen significantly as baby boomers retire in increasing numbers over the next few years and the demand for people with the kind of digital skills that the American manufacturing industry requires continues to grow.

Sometimes, you can't see what's right in front of you. This is doubly true if what's in front of you is terabytes of data; the hundreds of thousands of text messages, images, videos, and phone records that constitute just a fraction of the evidence in a criminal investigation. Law enforcement agencies the world over are faced with this exact scenario--enormous amounts of data isolated in siloed systems. Sorting through information in search of relevant insights, the type of leads that could crack a case is often a tedious, manual process. That's where AI solutions based in Microsoft Azure can help.

In my earlier post, I discussed basics of machine learning (ML) and techniques that can drive powerful outcomes for manufacturers. Now, let's discuss the approach for realizing those outcomes. I start every ML discussion with two questions: What is the business problem? And, what is the hypothesis? Starting this way forces everyone to think about what problem we are trying to solve, what data we might need, what our acceptance criteria should be, and what actions we should take based on the predictions. The ability to answer these questions varies depending on the organization's AI Maturity level, but going through the questions provides key insights into the actual problem.