The Ezviz Mini Trooper starter kit includes a camera, base station, and an 8GB microSD card for storing security video. It supports motion detection, automatically recording video of triggering events and pushing alerts via the Ezviz companion app, and has a built-in mic to capture ambient audio (but no two-way communication). The Mini Trooper starter kit includes one base station, one camera, and an 8GB card. Thanks to its PIR sensor, the Mini Trooper's motion detection is pretty spot on.
In the short-term, it's important that AI creators, businesses and consumers already employing AI educate people about the real world applications of AI and how to best secure the data AI pulls from to learn new tasks and respond to human inquiries. Take Amazon's planned fulfillment center on Staten Island that promises to create 2,250 human jobs while using robots to do administrative and physical fulfillment work. Of course, it remains to be seen if Amazon's move is one toward human and robot collaboration or total automation, but I'm confident the center will provide the global industry with an important case study on scaling AI for business. They're looking to the tech community and government leaders to define AI's role in business, in the home and, more broadly, in the future of humanity.
Next month at Black Hat USA in Las Vegas, a group of researchers will help broaden enterprise security horizons by showing a new use case of how attackers can bridge the cyber world with the physical world by creatively targeting IIoT systems. In the talk, Breaking the Laws of Robotics: Attacking Industrial Robots, a group of researchers from the Politecnico di Milano in Italy stress-tested the cyber and physical security of computer-controlled robotic arms used worldwide in factories throughout a range of manufacturing scenarios. Zanero is associate professor at Politecnico di Milano, as well as a Black Hat review board member. The findings transcend the FUD of Cyber 9/11 warnings of yesteryear and will dig into some very realistic scenarios of the kinds of subtle problems attackers could stir up with some simple hacks of IIoT factory systems.
For this reason, one of the most important tools in the CISO's arsenal is user behavior analytics (UBA), a solution that scans data from a security information and event management (SIEM) system, correlates it by user and builds a serialized timeline. Users at high risk are flagged with information such as job title, department, manager and group membership to enable analysts to quickly investigate that particular user's behavior in the context of his or her role within the organization. By combining all of a user's data from disparate systems and utilizing artificial intelligence (AI) to gain insights, UBA empowers analysts with new threat hunting capabilities. Two standard deviations from the mean do not constitute machine learning, and five failed logins in one minute do not constitute artificial intelligence.
The one and only reason why businesses are turning to automatic emotion detection is you! What are the possible applications of emotionally intelligent machines? In addition, when automatic emotion recognition is used in public safety, healthcare, or as assistive technology, it can greatly improve the quality of people's lives, allowing them to live in a safer environment or reducing the impact that disabilities or other health conditions have. We are defining today how machine emotional intelligence will evolve and how it'll be used.
"We are making every lamp post a smart lamp post to mount different types of sensors," Prime Minister Lee Hsien Loong said in his National Day Rally speech on Sunday (Aug 20) when he spoke about making Singapore a Smart Nation. During the year-long trial, GovTech and other agencies will monitor noise, water and sewage levels for better estate management, and install smart water meters in homes to better track the use of utilities. National water agency PUB has sensors to detect water levels in drains. Boston police identified the two bombers within three days, after pulling together and analysing a vast amount of data from CCTV cameras, social media and footage contributed by the public.
The data generated through digital devices of consumers offers vast insight into their minds and lifestyles. The use of IoT, Big Data, and Cloud Computing all generate and require the use of massive data spread across numerous systems. As companies entrust their data and applications to cloud computing they also expect full security of it. In organizations, it is important for IT and cyber security teams to reach mutual understanding and develop security systems and strategies that ensure secure digital transformation.
CHENNAI, India, Aug 9 (Thomson Reuters Foundation) - With more than 20 million humans working as modern slaves, a technology developer is hoping artificial intelligence will help clean up the world's supply chains and root out worker abuse. Developer Padmini Ranganathan said mobile phones, media reports and surveillance cameras can all be mined for real-time data, which can in turn be fed into machines to create artificial intelligence (AI) that helps companies see more clearly what is happening down the line. Modern-day slavery has come under increasing scrutiny in recent year, putting regulatory and consumer pressure on companies to ensure their supply chains are free from forced labour, child workers and other forms of slavery. Ranganathan works for information technology services company SAP Ariba, which helps companies better manage their procurement processes.
The Movidius Neural Compute Stick uses deep neural network processing and machine vision technology to "reduce barriers to developing, tuning and deploying AI [artificial intelligence] applications," Intel said in a statement yesterday. The Neural Compute Stick is built with vision processing unit (VPU) technology developed by Movidius that's already being used in devices ranging from drones to video surveillance cameras. Prior to its acquisition by Intel for a reported $400 million in September, Movidius had released its own Fathom Neural Compute Stick, to help developers deploy trained neural networks to a range of devices equipped with Myriad 2 VPUs. In its new incarnation from Intel Movidius, the Neural Compute Stick lets developers bring trained neural networks built on the Caffe framework to embedded apps running on a variety of Myriad 2 VPU-based devices.