In a recent interview with us, Vijay D'Souza, Director of the Center for Enhanced Analytics at the US Government Accountability Office, noted that, 'Regardless of the goals, it's important to understand the quality of the data you have. The quality determines how much you can rely on the data to make good decisions.' As it stands, bad data is ruining companies' data initiatives. This is one of the primary reasons why just 25% of businesses are successfully using their data to optimize revenue, despite the tremendous resources being pumped into them. IBM estimates that bad data is costing organizations some $3.1 billion a year in the US alone, while in Experian's Data Quality survey, 83% of companies said their revenue is affected by inaccurate and incomplete customer or prospect data.

MOGADISHU, Somalia – U.S. forces say they have carried out three drone strikes within 24 hours in Somalia, stepping up their campaign against the Islamic extremist rebels of al-Shabab and the Islamic State group. The strikes by unmanned drones killed several extremist fighters, a spokeswoman for the U.S. military command in Africa told The Associated Press Sunday. With these three attacks, the U.S. has now carried out 26 attacks in Somalia against extremist targets in 2017, she said. The latest U.S. strikes were carried out in coordination with Somalia's government, she said. The first strike happened Saturday at approximately 4:30 p.m. local Somalia time and it killed one fighter for the extremists group, al-Shabab, said a U.S. Africa command statement.

Bias is how far removed a model's predictions are from correctness, while variance is the degree to which these predictions vary between model iterations.

Two open letters have been sent by Artificial Intelligence experts to the Australian Prime Minister Malcolm Turnbull, which was signed by 122 AI researchers, and to the Canadian Prime Minister Justin Trudeau, which had 216 signatures on it.

Roundup It's been an interesting fortnight, sorry, two weeks in AI. In addition to what we've already reported, we have news about HPE developing what looks like a neural network accelerator chip, TensorFlow updates, Google's effort to teach software to make software, and other bits and pieces. The next biz in line claiming to be working on developing a fast custom-designed chip supposedly for neural networks is HPE. It was first reported on our sister site, The Next Platform, this week, although there are scant details on how the hardware works, its specs or even if it can deal with stuff like deep learning. That's mainly because our colleagues got wind of the secret R&D effort before it was due to be made public, and the enterprise IT giant is keeping schtum for now. The mysterious chip's "dot product engine" (DPE) architecture is apparently geared toward carrying out matrix operations at speed, which is useful for executing AI algorithms quickly.

Provided by The Next Web China this week announced an AI-powered unmanned police station will open in one of its capitol cities, proving once again that no other country quite embraces artificial intelligence like it does. The station appears to be designed with driver and vehicle related matters in mind, making it more like a Department of Motor Vehicles (DMV) than a cop shop. It will provide driver's examinations via simulator, registration services, and feature advanced face-scanning technology developed by Tencent, according to a report from Chinese financial paper Caijing Neican. Setting aside the myriad of law enforcement related implications, there's still plenty to unpack concerning the idea of unmanned government buildings. This station will be open to the public 24/7, and since citizens will presumably be dealing with dedicated hardware there should be far less points of failure than web-based solutions tend to have.

Police in the US state of Delaware are poised to deploy "smart" cameras in cruisers to help authorities detect a vehicle carrying a fugitive, missing child or straying senior. The video feeds will be analyzed using artificial intelligence to identify vehicles by license plate or other features and "give an extra set of eyes" to officers on patrol, says David Hinojosa of Coban Technologies, the company providing the equipment. "We are helping officers keep their focus on their jobs," said Hinojosa, who touts the new technology as a "dashcam on steroids." The program is part of a growing trend to use vision-based AI to thwart crime and improve public safety, a trend which has stirred concerns among privacy and civil liberties activists who fear the technology could lead to secret "profiling" and misuse of data. US-based startup Deep Science is using the same technology to help retail stores detect in real time if an armed robbery is in progress, by identifying guns or masked assailants.

In 1983, a curious teenager named David Lightman found a backdoor in a military computer system and very nearly caused the United States to start a nuclear war. If this sounds familiar, it isn't because it happened in real life. This was the plot of a movie called War Games, and it very realistically portrayed some common hacking techniques of the day like war dialing and phone phreaking. What was most surprising about this movie was that, unlike some science fiction movies, the problems it described were real and needed immediate solutions. But it would take five years for the first theoretical paper to be published on a term that would be eventually become well-known outside of the cybersecurity community: the firewall.

By definition, museums store and display objects of historical, scientific, artistic, or cultural significance. Want to see dinosaur skeletons, medical oddities, Civil War weapons, or Renoir masterpieces? But without relatability and modern storytelling, even the most captivating exhibits can be, well, a bit stuffy and boring. Especially for young people who are used to rich, complex multimedia experiences. If museums want to remain engaging and relevant in changing times, it makes sense that they would adopt new technology trends to elevate their purpose. According to the American Alliance of Museums (AAM), artificial intelligence is one of the biggest trends in the field to watch.

Healthcare and Artificial Intelligence (AI) are each very much in the news right now. The United States Senate has released draft legislation for the repeal the Affordable Care Act (aka "Obamacare"), leaving some Americans with trepidation about their coverage. Meanwhile, the phrases "machine learning" (ML) and "artificial intelligence" can inspire concerns of their own. What if there were a way to combine healthcare coverage with machine learning to try and make delivery of services not just more efficient (which many worry can be code for "less generous") but more proactive as well? Could this cut costs and enhance care?