Radical Open Innovation News week 41-2019

Welcome to our biweekly selection of digital innovation news. Created using our opinionated automated selection algorithm with a twisted text rank summary creator. We present some top innovation news items to get you thinking, debating and take action in order to make our world even better.

1 Enabling government to advance ‘tech intensity’ with newest cloud product innovations

As governments embrace tech intensity there’s in increasing demand on time and resources to manage data with a secure cloud environment. Examples abound and you’ll hear us showcase our partnerships with the Department of Veterans Affairs, USDA Agricultural Research Service, the Department of the Interior and more in the coming weeks. Government is Embracing Tech Intensity Tech intensity is really an equation – Tech Intensity = (Tech Adoption X Tech Capability) . Trust and as a company Microsoft is focused on providing the inputs to help our customers solve it. It’s really the first step to building tech intensity. I look forward to sharing many more examples of how government is embracing tech intensity to better engage and connect with citizens, modernize the government workplace, and enhance government services to benefit society.

(Microsoft)

2 Using machine learning to hunt down cybercriminals

It’s estimated that in 2017 alone, routing incidents such as IP hijacks affected more than 10 percent of all the world’s routing domains. Through BGP, networks exchange routing information so that data packets find their way to the correct destination. Hijacking IP addresses is an increasingly popular form of cyber-attack. From that, they observed particular qualities of malicious actors and then trained a machine- learning model to automatically identify such behaviors. That’s the idea behind a new machine-learning system developed by researchers at MIT and the University of California at San Diego (UCSD).

(MIT Reseach CS)

3 The State of Machine Learning Frameworks

In 2019, the war for ML frameworks has two remaining main contenders: PyTorch and TensorFlow. My analysis suggests that researchers are abandoning TensorFlow and flocking to PyTorch in droves. Meanwhile in industry, Tensorflow is currently the platform of choice, but that may not be true for long.

(The Gradient)

4 ‘This time with feeling?’

The boundaries of personal space and borders of bodily integrity are being tested by deployments of emotional artificial intelligence (EAI) in private and public spaces. This inevitably entails use of data about internal physiological and experiential contexts, but also factors external to an individual. To explore this, this paper asks and answers the following question: With regard to deployment in out-of-home situations, what are the legal and privacy implications of appraisal-based emotion capture? Criticisms of facial coding have long existed, but recent scholarship and industrial development signals a lack of confidence in ‘basic emotions’ and a turn to appraisal-based accounts of emotion. In this paper, we focus on computer vision and face-based analytics to consider the nature, method and development of facial coding, the potential demise of existing approaches, and the rise of even more invasive methods.

(First Monday)

5 Why Collabora really added Digital Restrictions Management to Weston

DRM (Digital Restrictions Management) is the collective term for software which attempts to restrict the rights of users attempting to access digital media. A: $$$$$ Why does Collabora want you to believe that HDCP support in Weston is a good thing? Digital Restrictions Management is software used by media owners to prevent you from enjoying their content except in specific, pre-prescribed ways. It’s a good thing for you , maybe. It’s a good thing for media conglomerates which want our ecosystem crushed underfoot.

(Drew DeVault’s Blog)

The Radical Open Innovation weekly overview is a brief overview of innovation news on Digital Innovation and Management Innovation from all over the world. Your input for our next edition is welcome! Send it to [info] at [bm-support]dot[org]