A fast and resilient global supply chain is vital for businesses to meet customer demands and ensure operational efficiency.
The rapid pace of innovation in artificial intelligence has led us to the next stage of AI development, which we call “industry verticalization”: designing AI products to meet the needs of specific industries.
In a webinar entitled “The Art of Possible: Manufacturing Priorities that Will Define 2021,” Çağlayan Arkan, Microsoft’s VP of manufacturing industry shared: “From extreme disruption comes extreme transformation.” His point is well taken. In the aftermath of the pandemic, supply chain has raced to the top of the news and manufacturing is centerstage. Arkan followed
To some extent, the term resilience has become 2020 shorthand for “surviving a global pandemic.” But as technical professionals know well, the goal of resilience long predates the cataclysms we’ve faced this year. As Mark Russinovich, CTO, Microsoft Azure, states: “Resilience is the ability of a system to fail gracefully in the face of—and eventually
There have been many articles written about how supercomputing in the cloud aids in performing compute tasks faster and more cost-effectively. However, with this new capability, both business and IT decision makers are now focusing more on how to manage the much larger volumes of produced data. More model runs and more granular results have
Who would have thought when I made my 2020 health trends and predictions in January that our world would be upended by COVID-19? In a year marked by the health and economic crisis posed by a global pandemic, we’ve seen countless examples of the U.S. health and life sciences community rising to each new challenge
For most organizations, growth is always at the forefront. The pursuit of new service lines, new customers, and new regions motivates business leaders to adopt bigger office spaces, expanded retail locations, and additional franchises. While these aspirations drive each company to bolder aspirations, they do so with a cost. Real estate and facilities management alone
A future for everyone To meet the needs and aspirations of the present without compromising the ability of future generations to meet their own needs—that’s how we at Microsoft define the challenge of sustainable development. We’re constantly exploring innovative ways our technology can address the urgent issues facing the world now, from revolutionizing individual and
2020 has been a year like none other. COVID-19 has brought about not only a public health crisis, but an economic one as well. But historically, skills training has not reached the people in underserved communities who need it most, such as people of color, people with disabilities, and women. Enter the Global Skills Initiative,
Sustainability is about survival. We want our businesses and communities—our species and planet—to carry on without running out of essential resources. Sustainability drives such important outcomes for business and society that it has become a compelling organizational priority. Microsoft has ambitious plans around sustainability. We want to create a future where every person, and every
Financial services institutions are increasingly using artificial intelligence (AI) to automate and augment their decisions. But when it comes to which AI algorithms to use, fairness and transparency must factor into the equation. Black box AI: a cautionary tale Some of the algorithms under heavy consideration today are called “black box” algorithms. While black box
2020 is a time of challenge and opportunity for small businesses who want to prioritize their digital transformation journeys. Fortunately, tools that weren’t seen as feasible for small businesses due to costs and resources are now becoming the norm for SMBs. While many small businesses already take advantage of solutions like cloud storage and collaboration
Machine learning holds the promise of saving time and money while increasing accuracy and efficiency across a variety of business use cases – but there can be pitfalls on the road to implementation. Companies often find artificial intelligence projects surprisingly easy to launch but then deceptively difficult to scale, from both the tech and organization
