Here’s an an idea for a formula for figuring out how much innovation an organization will do. I never know how good math is for this kind of thing, but it adds structure to programming an organization to be innovative, rather than career advancement seeking: In organizations, the competing forces can be described as “stake in outcome” versus “perks of rank.” When employees feel they have more to gain from the group’s collective output, that’s where they invest their energy.

Just as it is easy to misinterpret the reason for an icebreaker activity, it’s easy to mistake certain social customs of Americans that might suggest strong personal connections where none are intended. For example, Americans are more likely than those from many cultures to smile at strangers and to engage in personal discussions with people they hardly know. Others may interpret this “friendliness” as an offer of friendship. Later, when the Americans don’t follow through on their unintended offer, those other cultures often accuse them of being “fake” or “hypocritical.

I’ve tracked at least three different definitions of DevOps since the days of “agile infrastructure”: Using Puppet and Chef (and then Ansible and Chef) to replace Opsware and BladeLogic. Full stack engineers to setup EC2, load-balancers, and other Morlock shit. Full stack engineers are bad, but sort of the same thing. Also, you can’t have a DevOps “group” or title. But, you know, someone should do all that automation. Putting all the people on one team, having them focus on a product, and establishing a culture of caring and learning.

A brief overview: The expansion centers around Google’s new open-source hybrid cloud package called Anthos, which was introduced at the company’s Google Next event this week. Anthos is based on – and supplants – the company's existing Google Cloud Service beta. Anthos will let customers run applications, unmodified, on existing on-premises hardware or in the public cloud and will be available onGoogle Cloud Platform(GCP) withGoogle Kubernetes Engine(GKE), and in data centers withGKE On-Prem, the company says.

A brief overview: The expansion centers around Google’s new open-source hybrid cloud package called Anthos, which was introduced at the company’s Google Next event this week. Anthos is based on – and supplants – the company's existing Google Cloud Service beta. Anthos will let customers run applications, unmodified, on existing on-premises hardware or in the public cloud and will be available onGoogle Cloud Platform(GCP) withGoogle Kubernetes Engine(GKE), and in data centers withGKE On-Prem, the company says.

A brief overview: The expansion centers around Google’s new open-source hybrid cloud package called Anthos, which was introduced at the company’s Google Next event this week. Anthos is based on – and supplants – the company's existing Google Cloud Service beta. Anthos will let customers run applications, unmodified, on existing on-premises hardware or in the public cloud and will be available onGoogle Cloud Platform(GCP) withGoogle Kubernetes Engine(GKE), and in data centers withGKE On-Prem, the company says.

Want to come to Austin & talk about DevOps, Java, THE DIGITAL TRANSFORMATIONS & cloud hoopla? Apply to speak at SpringOne Platform this year, Oct 7th to 10th. I help pick talks for 3 tracks, so you can torment me! This is the last week to CFP! SUBMIT!

Obtaining FDA approval can be a difficult and long process. “The traditional paradigm of medical device regulation was not designed for adaptive AI or ML technologies, which have the potential to adapt and optimize device performance in real – time to continuously improve healthcare for patients,” the report said. “The highly iterative, autonomous, and adaptive nature of these tools requires a new, total product lifecycle (TPLC) regulatory approach that facilitates a rapid cycle of product improvement and allows these devices to continually improve while providing effective safeguards.

Obtaining FDA approval can be a difficult and long process. “The traditional paradigm of medical device regulation was not designed for adaptive AI or ML technologies, which have the potential to adapt and optimize device performance in real – time to continuously improve healthcare for patients,” the report said. “The highly iterative, autonomous, and adaptive nature of these tools requires a new, total product lifecycle (TPLC) regulatory approach that facilitates a rapid cycle of product improvement and allows these devices to continually improve while providing effective safeguards.

Obtaining FDA approval can be a difficult and long process. “The traditional paradigm of medical device regulation was not designed for adaptive AI or ML technologies, which have the potential to adapt and optimize device performance in real – time to continuously improve healthcare for patients,” the report said. “The highly iterative, autonomous, and adaptive nature of these tools requires a new, total product lifecycle (TPLC) regulatory approach that facilitates a rapid cycle of product improvement and allows these devices to continually improve while providing effective safeguards.