The typical American is recorded by security cameras 238 times a week, according to a new report from Safety.com. That figure includes surveillance video taken at work, on the road, in stores and in the home. The study found that Americans are filmed 160 times while driving, as there are about an average of 20 cameras on a span of 29 miles. And the average employee has been spotted by surveillance cameras at 40 times a week. However, for those who frequently travel or work in highly patrolled areas the number of times they are captured on film skyrockets to more than 1,000 times a week.
YI Technology (YI), the global provider of advanced, intelligent imaging technologies and products, announced the launch of the Kami Mini Indoor Camera, a tiny indoor security camera with a big brain, and the YI Dome Camera U, a complete coverage home security camera with extra privacy features. Both home security solutions are powered by YI Technology's proprietary, EDGE-based artificial intelligence (AI) technology which offers the most advanced feature set at the lowest possible price point to make smart home technology more accessible to the masses. YI has pioneered the development of a series of AI-enabled camera processing integrated circuits (ICs) which power Kami Mini and YI Dome Camera U. The sophisticated System-On-a-Chip (SoC) processing leverages Edge-based AI allowing for more advanced computing, fewer false alerts, and guaranteed access to AI features whether or not the user has a cloud subscription. Embedding the advanced AI chip in the camera also reduces detection latency because detection happens directly on the device rather than sending it to the cloud and waiting for a return signal. Recommended AI News: Cryptocurrency Prodigy, Joseph "PlugWalkJoe" O'Connor, Is Helping People Everywhere Master Crypto AI-Based Alerts & Face Detection: Equipped with the latest Edge Computing enabled chip, users can review all the faces that appear in their clips directly in the YI Home or Kami Home Apps.
Nearly all security cameras available today have some form of video analytics on board, according to Brian Baker, vice president, Americas, for Calipsa, a leading provider of deep learning-powered video analytics for false alarm reduction. But why is this the case? And what do facilities managers need to know about it? Video analytics powered by artificial intelligence promise smarter alerts that free your security staff from responding to false alarms, says Baker, a presenter at the 2020 GSX virtual tradeshow. But to find the right AI-backed analytics for your organization, it's first important to understand the basic concepts behind the technologies.
The Los Angeles Police Department has used facial-recognition software nearly 30,000 times since 2009, with hundreds of officers running images of suspects from surveillance cameras and other sources against a massive database of mugshots taken by law enforcement. The new figures, released to The Times, reveal for the first time how commonly facial recognition is used in the department, which for years has provided vague and contradictory information about how and whether it uses the technology. The LAPD has consistently denied having records related to facial recognition, and at times denied using the technology at all. The truth is that, while it does not have its own facial-recognition platform, LAPD personnel have access to facial-recognition software through a regional database maintained by the Los Angeles County Sheriff's Department. And between Nov. 6, 2009, and Sept. 11 of this year, LAPD officers used the system's software 29,817 times.
"Edmond de Belamy," produced by the art group Obvious and auctioned at Christie's in 2018 for $432,500, relied on generative adversarial network algorithms developed over years by various parties, including Ian Goodfellow, Alec Radford, Luke Metz, Soumith Chintala, and Robbie Barrat. The painting ingested tons of artwork samples from artists through the ages to become tuned to produce art of a certain style. One of the most striking PR moments of the AI age was the sale by Christie's auction house in October, 2018, of a painting output by an algorithm, titled "Edmond de Belamy," for $432,000. The painting was touted by the auctioneers, and the curators who profited, as "created by an artificial intelligence." The hyperbole was cringe-worthy to anyone who knows anything about AI. "It," to the extent the entire field can be referred to as an it, doesn't have agency, for one thing.
Artificial intelligence will play a pivotal role in the future of information security. By combining big data, deep learning, and machine learning, AI give machines life; they can imitate human learning, replicate work behaviors, and bring new ways to operate businesses. However, AI assets are very valuable, making them the target of hackers. Once a hacker has an opportunity to discern how the AI model is trained and operated, the model can be easily manipulated. For instance, hackers can destroy the data in the training model, causing major disruption in both the supply and demand side of the entire AI system.
The growing use of artificial intelligence (AI)-powered video analytics over the years has radically altered and improved the operations of many processes, across industries and continents. The findings of the IHS Markit Video Surveillance Intelligence Service shows that there has been a consistent growth in the global professional video surveillance equipment market, with the worldwide market revenue jumping up from $18.2 billion in 2018 to $19.9 billion in 2019. Supply chain management, which basically refers to the handling of various processes comprising the production flow, all till the end product is finally delivered to the customer, has become smarter using the next-gen video analytics technology. Devices that are intelligently embedded with the technology, such as CCTV cameras, are automatically able to gather crucial data in real-time through video feed. The AI-based system then adds intelligence to these devices, which are also able to carefully analyse this data, recognize any kind of critical or abnormal events during any leg of the supply chain, further sending automated alerts in real time.
AI and ML are not magic wands that you can wave to suddenly secure your organization. Security personnel must work closely with these models to train and hone them, and these professionals are neither cheap nor easy to find. Another challenge is data and cost: We need to amass enough clean data to build a robust algorithm we can trust. Clean data doesn't just happen – it must be analyzed and verified for accuracy. The cost of storing massive amounts of data and purchasing the necessary compute time to run hefty ML algorithms is significant, and implementing an all-encompassing AI security solution may be too costly for some.
Every cyber attack is looking more sophisticated than before, or so security teams would have us believe. Breaches in general may be complex, but the complexity is only apparent when you try and rebuild the story of the attack, and this context, or storyline is important. Those complicated storylines often start at the endpoints in a company's system. Endpoints are where an employee might have plugged in a USB device they found in the parking lot, curious to know what's on it. Or maybe an employee opened a malicious PDF attachment they got in an email.