Tag: Machine Learning

It’s the job of senior enterprise leaders to ensure that their organizations are ready for the future. Unfortunately the future is unclear to us—all the more so in this era of rapid change, uncertainty, and complexity. As with the weather, we can foresee the near future with some certainty, but as we look further ahead, […]

Organizations need a powerful infrastructure to realize the full value of their data. The purpose of this infrastructure is to organize data, ensure its quality, manage metadata and create a central catalog where the organization’s data can be queried. This infrastructure, called the data foundation, enables organizations to have clean, organized, and easily accessible data […]

We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run. —Roy Amara, Amara’s law I’m fascinated by the technological tipping points in history that have ignited the public’s imagination—the first TV broadcast, manned space flight, or video conference. Each of these events made a […]

Overview Throughout the year, we write blog posts on whatever topics seem to be most important to the AWS customer executives we speak to. Each of us on the Enterprise Strategy team holds 100-200 customer meetings a year, generally at the most senior executive levels, to try to help with their challenges in digital transformation—cultural […]

By Annina Neumann, AI/ML Strategist and Gregor Hohpe, Enterprise Strategist at AWS We routinely underestimate the effects that new technology has in the long run while also overestimating its impact in the short term. What has become known as Amara’s Law, in honor of the late researcher and scientist Roy Amara, is playing out now […]

In the previous blog post I explored with Michelle K. Lee some of the societal impacts of artificial intelligence (AI) and machine learning (ML). In this post I dive into the patterns Michelle has seen organisations implement to take advantage of the promises of ML. ―Phil Some surveys show a gap between an understanding of […]

In my recent blog post I shared a perspective on how to start your exploration of artificial intelligence (AI) and its subset, machine learning (ML), as business tools. I wrote this as a technology practitioner but a student of ML. At the other end of the experience continuum, I have the privilege of working with […]

Any sufficiently advanced technology is indistinguishable from magic. -Arthur C. Clarke

            From speaking with enterprise customers of all shapes and sizes, it is abundantly clear that we all share the same challenges: we’re racing to digitize our businesses, turn stalled progress into frequent innovation, and leverage data and machine learning. However, I feel there’s a gap in understanding how critical […]

One of the challenges many enterprise leaders face is how to experiment and quickly create business value from machine learning without establishing large teams with specialized skillsets and infrastructure. As a CTO, I found that having access to Amazon Web Service’s pre-trained AI Services enabled our developers, even those with no prior machine leaning experience, […]