Asia


Staqu develops AI surveillance system for Uttar Pradesh prisons

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Gurugram-based AI startup Staqu has launched its video analytics platform called JARVIS in Uttar Pradesh. The app was launched by UP Chief Minister Yogi Adityanath. Staqu has established AI-powered video analytics solution with a'Video Wall' that covers CCTV footage from all of 71 prisons of the state, covering a stretch of 900km. The AI-powered video analytics tool is now live with 700 cameras for multi-purpose analytics and can automatically analyse intrusion at the wall, frisking, and unauthorised access, sudden increase of crowd, violence, camera not working, and intrusion detection, amongst others. JARVIS is also equipped to send alerts on various predefined events on the mobile app to the jail superintendent and also to the nodal command centre at Lucknow.


International Guidelines for Ethical AI

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In the last two months, i.e. in April and May 2019, both the EU Commission and the OECD published guidelines for trustworthy and ethical Artificial Intelligence (AI). In both cases, these are only guidelines and, as such, are not legally binding. Both sets of guidelines were compiled by experts in the field. Let's have a closer look. "Why do we need guidelines for trustworthy, ethical AI?" you may ask.


International Guidelines for Ethical AI

#artificialintelligence

In the last two months, i.e. in April and May 2019, both the EU Commission and the OECD published guidelines for trustworthy and ethical Artificial Intelligence (AI). In both cases, these are only guidelines and, as such, are not legally binding. Both sets of guidelines were compiled by experts in the field. Let's have a closer look. "Why do we need guidelines for trustworthy, ethical AI?" you may ask.


SoftBank and University of Tokyo to open business-oriented AI research centers

The Japan Times

SoftBank Corp. and the University of Tokyo have agreed to open artificial-intelligence centers staffed with specialists from the university and around the world, to swiftly turn research into profitable business ventures so Japan can keep up with the U.S. and China. "If they are stuck with research … their funds and passions will drain away," SoftBank Group CEO Masayoshi Son said at an event announcing the joint project at the prestigious university. "By teaming with the University of Tokyo, we want to give students a chance to learn and start a business," said Son, who has stressed the importance of AI for years. Under the arrangement, a pair of facilities -- one on the university's Hongo campus in Bunkyo Ward and the other at a planned new SoftBank office in the Takeshiba district -- will be established in spring and winter of 2020 at the earliest, respectively, under the brand Beyond AI. The Hongo base will handle basic research on the evolution of AI and potential ways to apply the technology in physics, robotics, brain science and other fields.


Intel may buy another AI chip developer, Habana Labs

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Intel is in advanced talks to buy AI chip developer Habana Labs for as much as $2 billion, according to an unnamed source that spoke to Calcalist. Habana Labs is based in Israel. Intel bought Mobileye, a company focused on autonomous driving also based in Israel, in 2017 for $15 billion. Intel wouldn't comment on the possible transaction, and Habana Labs did not respond to a request to comment. The company was founded in 2016 to develop processor platforms for training deep neural networks and inference deployment.


Current patent laws are inadequate for Artificial Intelligence-related Intellectual Property: Report

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MUMBAI: A report published by India's largest software exporter, Tata Consultancy Services, in association with Confederation of Indian Industry, found that despite the evolution of patent laws, the increasing proliferation of artificial intelligence across the world necessitates new policies for the enforcement of intellectual property rights. "Current patent laws treat AI software inventions as logical algorithms implemented on the computer. While patent eligibility of algorithms is valid, there is little about how to deal with inventions that are heuristic in nature," the report found. In artificial intelligence a'heuristic' is a technique used to solve a problem faster than classic methods. Software is no longer limited to traditional rule-based systems and has increasingly turned heuristic, showing higher intelligence over rule-based systems, it cited.


Data Scientist Uses Deep Learning to Predict BTC Price in Real-Time

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A data scientist at India's prestigious Vellore Institute of Technology has outlined a method for how to purportedly predict crypto prices in real-time using a Long Short-Term Memory (LSTM) neural network. In a blog post published on Dec. 2, researcher Abinhav Sagar demonstrated a four-step process for how to use machine learning technology to forecast prices in a sector he purported is "relatively unpredictable" as compared with traditional markets. Sagar prefaced his demonstration by noting that while machine learning has achieved some success in predicting stock market prices, its application in the cryptocurrency field has been restricted. In support of this claim, he argued that cryptocurrency prices fluctuate in accordance with fast-paced technological developments, as well as economic, security and political factors. Sagar's four-step proposed method involves 1) collecting real-time cryptocurrency data; 2) preparing the data for neural network training; 3) testing the prediction using the LSTM neural network; 4) visualizing the results of the prediction.


From the Navy to North Korea to CMC, professor Mike Izbicki discusses his path to pacifism

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"Whether they're [international relations] students who want to apply machine learning tools to what they're working on or computer science students …


Neural Network Projects with Python

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James Loy has more than five years, expert experience in data science in the finance and healthcare industries. He has worked with the largest bank in Singapore to drive innovation and improve customer loyalty through predictive analytics. He has also experience in the healthcare sector, where he applied data analytics to improve decision-making in hospitals. He has a master's degree in computer science from Georgia Tech, with a specialization in machine learning. His research interest includes deep learning and applied machine learning, as well as developing computer-vision-based AI agents for automation in industry.


Lighting up the Blackhole of the Internet using AI by Ashish Vikram & Kuldeep Yadav #ODSC_India

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Enterprises are creating more and more videos and using them for various informational purposes, including marketing, training of customers, partners & employees and internal communications. However, videos are considered as the blackholes of the internet because it is very hard to see what's inside them. The opaque nature of videos equally impacts end users who spend a lot of time navigating to their point of interest, leading to severe underutilization of videos as a powerful medium of information. In this talk, we will describe visual processing pipeline of VideoKen platform which includes Graph-based algorithm along with deep scene text detection to identify key visual frames in the video, FCN-based algorithm for semantic segmentation of screen content in visual frames, Transfer-learning based visual classifier to categorize screen content into different categories such as slides, code walkthrough, demo, handwritten, etc. and Algorithm to detect visual coherency and select indices from the video. We will discuss challenges and experiences in implementing/iterating on these algorithms using our experience with processing 100K video hours of content.