Here is a great discussion and interview on the potential and power of Natural Language Processing with Allyson Ettinger.
Microsoft Ignite was this week and, in case you missed it, here’s a great wrap up of the highlights.
The economic impact of the COVID-19 pandemic cannot be overstated and we may not know the full extent of the damage for some time to come.
However, one thing has become clear: digital transformaion can cushion the blow and realize efficiencies even now.
Artificial intelligence is one of the most tech-forward ways that businesses are boosting efficiency, though not the only one, by any means. But the goals of incorporating newer, digitally powered tools are similar: greater company efficiency and more satisfied customers.
This video posted by Microsoft has an interesting look at the challenges holding companies back from digital transformation in the cloud era.
What if we could store data in such a way that we never had to worry about quality loss or degradation? Microsoft Partner Deputy Lab Director Ant Rowstron shares his thoughts on redesigning the datacenter for a cloud-centric world. An ordinary piece of glass could have an extraordinary impact on the ways in which we store data and preserve collective memories. Using silica glass presents an energy efficient, sustainable and nearly indestructible method of data storage that could change the way we preserve our history, movies and music and more.
Discover more about this story at Microsoft Innovation: http://msft.social/b1iM95
TechCrunch takes a closer look at Barcelona-based Scaled Robotics.
The company built a Wall-E doppelgänger to navigate around and build maps of construction sites by fusing images, video, and data captured by its robots.
As businesses rush to become more data driven and leverage AI to better serve customers and be more competitive, enterprises are quickly learning that the way to AI readiness leads straight to the cloud. Here’s an interesting article on the state of AI-readiness, sometimes called digital transformation.
But how do companies step up their infrastructure to become “AI ready”? Are they deploying data science platforms and data infrastructure projects on premises or taking advantage of a hybrid, multi-cloud approach to their infrastructure? As more and more companies embrace the “write once, run anywhere” approach to data infrastructure, we can expect more enterprise developments in a combination of on-prem and cloud environments or even a combination of different cloud services for the same application. In a recent O’Reilly Media survey, more than 85% of respondents stated that they plan on using one (or multiple) of the seven major public cloud providers for their data infrastructure projects,
Enterprises across geographies expressed interest in shifting to a cloud data infrastructure as a means to leveraging AI and Machine Learning with more than 80% of respondents across North America, EMEA and Asia replying that this is their desired choice. A testament to the growing trend towards a hybrid, multi-cloud application development is the finding in the same survey that 1 out of 10 respondents uses all three major cloud providers for some part of their data infrastructure (Google Cloud Platform, AWS and Microsoft Azure).
will is disrupting every business in every industry. Usually, this process has been labelled by some as “Digital Transformation.” Working with customers has shown me that, while many want to be ready for the Age of AI, most have not taken the steps necessary to truly transform into a data driven organization.
Here’s a post outlining signs that your company may have stalled in its transformation.
The ongoing and amorphous nature of digital transformation change efforts can make progress hard to gauge – sometimes leading to stagnation. As Korn Ferry senior client partner Melissa Swift has pointed out, digital transformation is a marathon, not a sprint. So how do you know when you’re running a productive marathon or when you’ve hit a hill that the team is truly stuck on?
Individual digital project metrics, while important to track the performance of digital transformation programs, may not provide a complete picture of progress. However, IT leaders can keep an eye out for other qualitative signs that indicate their organization’s effort may be stalled.
Last week, I spoke to a group of high school students about careers in STEM. Aside from being happy that STEM is now encouraged, I pointed out to them that the workforce they will be entering may look different than the one they see now. By the time they hit the workforce, digital transformation will have made short work of companies that have not become data driven. The only surviving and thriving companies will be the one who adapted quickly.
Proving that point is this article from TechRepublic and helpful advice on how to stay ahead of the robots.
Here’s an interesting video related to the article: