Sunday, September 08, 2019


Conflicts short of war?
Report reveals play-by-play of first U.S. grid cyberattack
A first-of-its-kind cyberattack on the U.S. grid created blind spots at a grid control center and several small power generation sites in the western United States, according to a document posted yesterday from the North American Electric Reliability Corp.
The unprecedented cyber disruption this spring did not cause any blackouts, and none of the signal outages at the "low-impact" control center lasted for longer than five minutes, NERC said in the "Lesson Learned" document posted to the grid regulator's website.
But the March 5 event was significant enough to spur the victim utility to report it to the Department of Energy, marking the first disruptive "cyber event" on record for the U.S. power grid (Energywire, April 30).
"So far, I don't see any evidence that this was really targeted," said Reid Wightman, senior vulnerability analyst at industrial cybersecurity firm Dragos Inc. "This was probably just an automated bot that was scanning the internet for vulnerable devices, or some script kiddie," he said, using a term for an unskilled hacker.
Nevertheless, the case turned heads at multiple federal agencies, collectively responsible for keeping the lights on in the face of an onslaught of cyber and physical threats.




Low hanging fruit.
What enterprises intend to do with artificial intelligence
Business process automation and customer support are foremost on the minds of executives and managers buying or implementing AI systems, and where many of the budget dollars.
That's the word coming out of a survey of 100 executives by Leverton, which looked at corporate motivations for AI acquisitions.




Some obvious uses for AI in my field.
Machine learning has the potential to disrupt nearly every industry during the next several years, and the auditing profession is no exception (Julia Kokina and Thomas H. Davenport, “The Emergence of Artificial Intelligence: How Automation Is Changing Auditing,” Journal of Emerging Technologies in Accounting, Spring 2017, http://bit.ly/2Heshyk ). Jon Raphael, chief innovation officer at Deloitte, expects machine learning to significantly change the way audits are performed, as it enables auditors to largely “avoid the tradeoff between speed and quality” (“Rethinking the Audit,” Journal of Accountancy, Apr. 1, 2017, http://bit.ly/2Vxx7RB ). Rather than relying primarily on representative sampling techniques, machine learning algorithms can provide firms with opportunities to review an entire population for anomalies.




Familiar challenges to any change.
4 CHALLENGES TO ARTIFICIAL INTELLIGENCE ADOPTION AND THEIR SOLUTIONS
1. Gaining Organization-Wide Buy-In
2. Developing a Clear AI Strategy
3. Finding the Right Talent
4. Overhauling Existing Systems




For my geeks.
Interactive: The Top Programming Languages
This app ranks the popularity of dozens of programming languages. You can filter them by excluding sectors that aren’t relevant to you, such as “Web” or “Embedded.”




Only a scifi nut (like me) would be interested in this infographic.
AI has been making science fiction dreams into reality for decades.



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