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Showing posts from August, 2019

A Distributed Future: Where Blockchain Technology Meets Organisation Design and Decision-making

Blockchain technology records and forever maintains data that cannot be changed. It also involves ‘smart contracts’ and consensus mechanisms that govern processes of automation, as well as the development, evaluation and execution of decisions. Blockchain technology has the potential to transform organisation design due to its decentralised and distributed characteristics. To understand how blockchain will change organisation design and decision-making, let’s first dive into the history of organisation design before investigating the impact of this fundamental technology on organising activity. History of Organisation Design The theory and practice of organisation design have evolved significantly over the past 100 years. At the beginning of the twentieth century, organisations were mostly viewed as closed bureaucracies. Involving a strict hierarchy of authority and power, these organisations were rational entities and assessed purely on economic performance criteria. It was called...

Why We Need AI-Based Video Compression

Over the past couple of years, there’s been a significant increase in the popularity of videos. The word around the net is that videos are set to replace images. The problem is that video files are huge, and their current compression methods are clumsy.  This article reviews the current state of video compression and explains how Artificial Intelligence can help solve the current challenges. Video Compression—What It Is and How It Works Video compression is the process of converting video files. The goal is to reduce the size of the video, so it would take up less space on devices and systems, and consume less bandwidth when loading. You can compress videos through the use of physical or video codecs, which encode and decode video files. Compression techniques—lossy vs lossless There are two compression types. Each utilises a different conversion method. The lossy compression technique eliminates redundant data from the file. By the end of the process, you can achieve a c...

Want To Contribute To An Upcoming Book?

I’ve just started working with O'Reilly on a new book, and we are looking for people to contribute their thoughts for inclusion in the book. The book is going to be called 97 Things About Ethics Everyone In Data Science Should Know. This book will be part of a larger series O’Reilly does called 97 Things, each of which contains -- wait for it -- 97 blog-length essays from a variety of authors on a given topic.  Our goal with the collection is to represent a wide range of voices and ideas from people who have a clear point of view on some aspect of the ethical issues surrounding the field of data science. We're going to organize the book around broad themes, including the ethics surrounding: What types of data science initiatives can be ethically undertaken How to determine what data can be ethically utilized Monitoring and maintenance needed to ensure a process's ongoing ethical state How to ensure that the results of a data science initiative are used e...

Focus on Data to Succeed in AI, Say AI World Government Attendees

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By AI Trends Staff At the AI World Government conference last June,  MeriTalk  conducted a survey of 71 government and industry executives and IT decision- makers abou t how AI is being used in government. The findings were released this week. The survey revealed that more than half of the survey respondents—61% — are working on AI today and another 14% expect to be doing so within the year. Most called AI development a little (42%) or moderately (48%) mature, but 89% said AI will be ready for mission-critical tasks within five years. We  are close, but  survey respondents  still  listed  several changes  needed for AI success across data, technologies, work force, and culture. Focus on Data Governance, Consistency For Success in AI Improved data governance, data-centric architecture, and increased consistency of data formats and tagging were the top three needs in terms of data.  This is also the area where survey respondents...

Drunk Drivers Versus AI Autonomous Self-Driving Cars

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By Lance Eliot, the AI Trends Insider On a recent Friday night, after an evening event, I got onto the road and had some trepidation due to the aspect that I would be using locally popular freeways and highways for which drunken drivers also often used late at night (especially on  Fridays and  Saturdays). I debated whether to instead use other less traveled roads, perhaps being able to avoid those potential drunken drivers, but it would have added considerable time to my journey home and there was no guarantee that I still wouldn’t encounter alcohol-impaired drivers. You likely know that drunk drivers account for nearly one-third of all traffic-related deaths in the United States (per stats by the National Highway Traffic Safety Administration). The rule-of-thumb is that there’s an alcohol driving related death every hour, based on averaging the number of such deaths over the course of a year. You might not realize that annually there are more than 1 million drivers arres...

Tesla’s 500,000 Vehicles on the Road Give it a Lead in Generating Data for its Self-Learning AI Self-Driving Cars

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By AI Trends Staff Tesla is making its own way in the application of AI to self-driving cars, making several key decisions that contrast with designs of other AI self-driving car software developers, and having the advantage of a large installed base of vehicles on the road. One early decision was to make over the air (OTA) software updates available to Tesla drivers. In October 2015, each of Tesla’s 60,000 owners received an OTA update, based on data gathered for a year from all Tesla drivers. In 2014, Tesla sent a software fix for overheating to its 30,000 owners at the time, according to an account in  TEchiexpert . Tesla has compiled data from over 100 million miles driven with its autopilot software. The is being used to generate roadmaps for self-driving cars, which Tesla claims are 100 times more accurate than alternative navigation systems. The company is considering whether to offer the data for sale to other automakers, or possibly offer it to the government to help m...

EmPOWER Uses AI to Better Serve Electricity-Dependent Populations

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By Deborah Borfitz Every community in the country includes people for whom electricity is literally a life-or-death matter—including individuals who receive dialysis because their kidneys stopped working and those who rely on an oxygen concentrator   or ventilator to help them breath .  A power outage can be a l ife-threatening  event in a matter o f hours   for some  medically fragile people , especially if backup batteries fail. The i ncreasing frequency of natural disasters—most notably Hurricane Sandy in 2012—heightened awareness of electricity dependency as a  new  social determinant of health, says  Kristen Finne,  d irector  of the   emPOWER   p rogram  of the U.S. Department of Health and Human Services (HHS) and s enior  p rogram  a nalyst  in the  Assistant Secretary for Preparedness and Response ’s (ASPR)   Office of Emergency Management and Medical Operations . The federal response ...

AI Systems Will Become Our Workmates, Workmates We Understand and Trust

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Contributed Commentary by Pieter Ballon , Director of SMIT at VUB     Science fiction films featuring robots or intelligent machines in the leading roles (such as Blade Runner, Real Humans, Westworld, etc.) have caused us to look at a future with AI with some trepidation. But it won’t happen overnight. We will have time to adjust ourselves to the idea and to control AI systems where necessary so that it becomes a gradual evolution, not a sudden revolution. But it is definitely an evolution that is already underway.   Harvard  Prof.  Michael Porter, sets out four stages that mark the way toward smart objects and systems. Stage one is “Monitoring” by using sensors: a smart product will be aware of its own situation and the world around it. An example of this is the Medtronic glucose meter, which uses a subcutaneous sensor to measure a patient’s blood-sugar level, alerting the patient 30 minutes before that level reaches an alarming status. ...