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Waymo Shares Autonomous Vehicle Dataset for Machine Learning

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Waymo, the self-driving technology company owned by Google's parent company, Alphabet, released a dataset containing sensor data collected by their autonomous vehicles during more than five hours of driving. The set contains high-resolution data from lidar and camera sensors collected in several urban and suburban environments in a wide variety of driving conditions, and includes labels for vehicles, pedestrians, cyclists, and signage. The Waymo team announced the release of the Waymo Open Dataset in a blog post, describing it as "one of the largest, richest, and most diverse self-driving datasets ever released for research." The data was collected by Waymo's vehicles operating in the USA in Phoenix, AZ, Kirkland, WA, Mountain View, CA and San Francisco, CA, at various times of day and night, and in good and bad weather. The dataset consists of 1,000 segments of 20 seconds each, collected at 10Hz (i.e., 200,000 frames) which contain: Waymo also released a Google Colab notebook containing tutorials and a GitHub repository containing TensorFlow helper-code for building models.


Matt Brooks on LinkedIn: "I agree that we #data #analytics professionals must guide the development of #ai algorithms. I wrote an article about this (https://lnkd.in/eXzTXM4) also urging awareness of how we should think differently, esp during the training phase of #ml models to remove bias...but I also wonder if too much #socialengineering will tip the scale too far..."

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USA TODAY is my favorite paper - how could it not be when I started reading it in high school when it first launched? So indeed, I am excited to see they are covering such an important topic in my world #AI #analytics and the risk of bias at scale - in a way non tech people can understand. This is why #diversity matters. This is why #data literacy matters.


UAE to use AI to help with intellectual property issues

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AI could soon help settle intellectual property issues in the UAE. The MoU was signed in Geneva on the sidelines of meetings being held at the World Intellectual Property Organisation (WIPO). Mohammed Ahmed bin Abdulaziz Al Shehhi, undersecretary for economic affairs at the UAE's Ministry of Economy (and who signed the MoU), said the usage of AI in IP could play a large role in shaping he future economy โ€“ in addition to cementing the UAE's status as a future-focussed society that utilises the latest technologies to make life better and more efficient. News of the use of AI in IP comes as Dubai has launched the region's first virtual licences. The virtual company licences, announced by Deputy Ruler Sheikh Maktoum bin Mohammed bin Rashid Al Maktoum, Deputy Ruler of Dubai, allow for investors worldwide to do business in Dubai digitally โ€“ without requiring residence in the emirate.


Xeeva: accelerating procurement results with AI

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Welcome to the October issue of Supply Chain Digital! In our cover feature this month, we speak with Kevin Overdulve, Director in Logistics & Distribution at Deloitte Belgium, about how the disruptive power of AI is shaping the autonomous supply chains of tomorrow. "We see that companies are


Futurist Tim O'Reilly sees a human-computer symbiosis bigger than AI ZDNet

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Tim O'Reilly is a kind of bard of technology, a lyrical poet of computing's past, present and future. Ask him a question and whole paragraphs of reflection bubble up. Is the present state of artificial intelligence, for example, bigger than the open-source software revolution, an epochal development chronicled in detail from the front lines by O'Reilly's publishing company? "That's an interesting question," says O'Reilly, before re-framing it, declaring that there is something bigger than AI itself. "I think in the long run, this transformation to machine autonomy, and to, basically, machines that are in a new kind of hybrid existence with humans -- they talk about AI as separate from us, but all interesting machines are hybrids of human and machine -- we have this machine that has been amplifying things we can do, and I think of the human-machine symbiosis as a trend that is probably bigger than the internet, and bigger than open source, and of which AI is one manifestation."


Does the Fourth Amendment Block Cops from Using Artificial Intelligence? The Crime Report

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The Fourth Amendment's prohibition against unreasonable searches and seizures could prevent law enforcement from applying increasingly sophisticated surveillance and predictive policing technology, including "superhuman" methods employing artificial intelligence, according to a professor at the University of California-Davis School of Law. In an essay published in the Ohio State Journal of Criminal Law, Elizabeth E. Joh argues that the recent U.S. Supreme Court decision in Carpenter v United States established a precedent for using the Fourth Amendment to limit the use of emerging technology, ranging from drones that help patrol borders to predictive-analytic software that can determine when and where the next crime will occur. In that landmark case, decided this summer, the Court ruled law enforcement cannot access citizens' cellphone location records without a search warrant. Although the decision focused on whether information held by "third parties" such as cellphone providers was subject to privacy protections guaranteed under the Constitution, Joh said it also touched on the changing "nature of policing" specifically the technologically enhanced means law enforcement can now exploit to gather information in the cyber era. In the Carpenter case, justices were asked to rule on whether FBI agents sidestepped their constitutional obligations to show "probable cause" for obtaining a search warrant to retrieve the locational data of a suspected serial robber's cellphone to prove he was near the scene of stores in the Detroit area where thefts had occurred.


Most Deepfakes Are Porn, and They're Multiplying Fast

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In November 2017, a Reddit account called deepfakes posted pornographic clips made with software that pasted the faces of Hollywood actresses over those of the real performers. Nearly two years later, deepfake is a generic noun for video manipulated or fabricated with artificial intelligence software. The technique has drawn laughs on YouTube, along with concern from lawmakers fearful of political disinformation. Yet a new report that tracked the deepfakes circulating online finds they mostly remain true to their salacious roots. Startup Deeptrace took a kind of deepfake census during June and July to inform its work on detection tools it hopes to sell to news organizations and online platforms.


ODSC Europe 2019 Open Data Science Conference

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In addition, we'll inform you about our many upcoming events in Boston, NYC, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers! We're Proud to Have Their Best and Brightest in Attendance


KT and WeDo collaborate on using artificial intelligence to detect fraud - VanillaPlus - The global voice of Telecoms IT

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KT Corporation and Portugal-based WeDo Technologies have signed a Cooperation Agreement for AI-FMS (Artificial Intelligence based Fraud Management System) development and sales. KT's Deep Learning-based Artificial Intelligence (AI) module has been implemented and tested on WeDo's RAID FMS system. This AI module, trained with KT Big Data, has showed strong results for fraud detection and prevention, and has reportedly proved to be effective for a number of fraud use cases, with a high degree of accuracy. KT and WeDo plan to supply the AI-based International Revenue Share Fraud (AI-IRSF) module with the RAID platform to communication service providers (CSPs) by the end of 2019. KT's DL (Deep Learning) based AI module has been implemented and tested on WeDo's RAID FMS system.


Computer game to assist clinicians in diagnosing mental health disorders

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A team of researchers led by CSIRO's Data61, the data and digital specialist arm of Australia's national science agency, have developed a novel technique that could assist psychiatrists and other clinicians to diagnose and characterize complex mental health disorders, potentially enabling more effective treatments. Announced today at D61 LIVE in Sydney, the researchers revealed that using a simple computer game and artificial intelligence techniques, they were able to identify behavioral patterns in subjects with depression and bipolar disorder, down to subtle individual differences in each group. The study included 101 participants: 34 with depression, 33 with bipolar disorder, and a control group of 34 subjects. The computer game presents individuals with two choices, and tracks their behavior as they respond. The complex data collected from the game is analyzed through artificial neural networks--brain-inspired systems intended to replicate the way that humans learn--which are able to disentangle the nuanced behavioral differences between healthy individuals, and those with depression or bipolar disorder.