Countries have assassinated people with drones, but those attacks now appear to include robotic weapons on the ground. The New York Times sources claim Israel assassinated top Iranian nuclear scientist Mohsen Fakhrizadeh on November 27th, 2020 using a remotely-controlled, AI-assisted machine gun. Israel reportedly mounted the gun on a pickup truck by the side of the road and, when Fakhrizadeh's car approached had a distant operator fire the gun using a satellite link. The attack was precise, sparing Fakhrizadeh's wife, but may not have used facial recognition to assist with aiming as unnamed Iranian officials said. While Israel purportedly used the AI to compensate for the satellite system's lag and gun recoil, operatives identified Fakhrizadeh by staging a decoy car with a camera to force a U-turn and get a clear image.
In a presentation at the EURETINA 2021 Virtual Congress, Anat Loewenstein, MD, MHA, discussed optimizing optical coherence tomography (OCT) and how physicians can determine with even more accuracy precisely what is happening in patients' eyes with neovascular age-related macular degeneration (nAMD) because of the potential afforded by application of artificial intelligence (AI). Loewenstein is professor and director of the Department of Ophthalmology at Tel Aviv Medical Center, the Sidney A. Fox Chair in Ophthalmology, and vice dean, Sackler Faculty of Medicine, Tel Aviv University, Israel. OCT is a major step forward in patient diagnosis, treatment, and monitoring but shortcomings remain. For example, physicians routinely make qualitative assessments of the presence and degrees of intraretinal/subretinal fluid and pigment epithelial detachments, but these are not precise assessment that are likely to result in poor inter-grader agreement and intra-grader consistency; OCT also provides the central subfield thickness, but the retinal fluid and neural tissue are not considered separately. As Loewenstein pointed out, In neovascular AMD, it is important to distinguish between retinal fluid localization in the intraretinal and subretinal compartments and their volumetric information for informing retreatment decisions and predicting visual outcomes.
Artificial intelligence could one day organize the world. As if in anticipation of this, a maritime platform developer called Orca AI has just begun a research trial of new safety systems for autonomous ships, equipping a vessel with artificial intelligence that recognizes other ships to safely guide it through busy sea traffic, according to a recent press release from the company. Orca AI was founded in 2018 by a pair of naval tech experts, and designs software platforms with extreme specificity for maritime vessels. The firm blends existing safety systems with sensors to enhance the navigation and safety of vessels making their way through crowded (and sometimes dangerous) waterways. Orca AI is headquartered in Israel, and aims to link sea-bound vessels with 24/7 land-based AI insights.
An Israeli defense contractor on Monday unveiled a remote-controlled armed robot it says can patrol battle zones, track infiltrators and open fire. The unmanned vehicle is the latest addition to the world of drone technology, which is rapidly reshaping the modern battlefield. Proponents say such semi-autonomous machines allow armies to protect their soldiers, while critics fear this marks another dangerous step toward robots making life-or-death decisions. The four-wheel-drive robot presented Monday was developed by the state-owned Israel Aerospace Industries' "REX MKII." It is operated by an electronic tablet and can be equipped with two machine guns, cameras and sensors, said Rani Avni, deputy head of the company's autonomous systems division.
Efforts are continuing to explore the use of automation, artificial intelligence, and image recognition to improve the navigation and safety of ship operations. Earlier this year, Japan's Mitsui O.S.K. Lines demonstrated its efforts are using augmented reality (AR) technology to enhance navigational awareness and now NYK announced that it has begun a trial on the system that can monitor the horizon to recognize dangerous objects that might be within a ship's range. NYK working with its strategic research and development subsidiary MTI Co. installed the Automatic Ship Target recognition System developed in Israel by Orca AI on one of NYK's vessels. The goal is to verify the detection capability and the contribution the system can make to the role of the lookout on a ship's bridge. Working with Orca, NYK also plans to improve the target detection algorithm through the use of data collection and machine learning on the Israeli company's servers.
Association Rules is one of the very important concepts of machine learning being used in market basket analysis. This course covers the working Principle of Association Mining and its various concepts like Support, Confidence, and Life in a very simplified manner. All of these algorithms has been explained by taking working examples. Parteek Bhatia is Professor in the Department of Computer Science and Engineering and Former Associate Dean of Student Affairs at Thapar Institute of Engineering and Technology, Patiala. At present he is on sabbatical at Tel Aviv University, Israel and acting as Visiting Professor at LAMBDA Lab, TAU.
In a new paper published in The International Journal of Astrobiology, Joseph Gale from The Hebrew University of Jerusalem and co-authors make the point that recent advances in artificial intelligence (AI)--particularly in pattern recognition and self-learning--will likely result in a paradigm shift in the search for extraterrestrial intelligent life. While futurist Ray Kurzweil predicted 15 years ago that the singularity--the time when the abilities of a computer overtake the abilities of the human brain--will occur in about 2045, Gale and his co-authors believe this event may be much more imminent, especially with the advent of quantum computing. It's already been four years since the program AlphaGO, fortified with neural networks and learning modes, defeated Lee Sedol, the Go world champion. The strategy game StarCraft II may be the next to have a machine as reigning champion. If we look at the calculating capacity of computers and compare it to the number of neurons in the human brain, the singularity could be reached as soon as the early 2020s.
When soldiers look through the sights of their assault rifles with the Elbit System's new artificial intelligence data platform, their view is transformed to resemble a first-person shooter video game. Shooters push buttons on a grip to toggle among layers of information about their surroundings, including motion detection, range, ammunition levels and more data that's just a click away. ARCAS, which the Israel-based company is featuring at the DSEI conference in London, incorporates a microcomputer in the weapon to process data and provide a graphical user interface to display the information in the rifle's electro-optical sight and through an optional helmet-mounted eyepiece. The demo used ARCAS systems mounted on M-4s, with testers shooting at stationary targets. The use of ideas from the gaming world is clear when putting the sight up to the eye.
Major disruptive technologies such as artificial intelligence, machine learning, computer vision, IoT, and many other have helped tech companies to offer a wide range of technical products and services across the world. This has increased the demand for tech stocks among investors in these recent years. Some tech stocks are established names whereas some are rising high gradually in Industry 4.0. Analytics Insight provides a list of the top 5 tech stocks, according to Yahoo Finance. Fiverr International Ltd. is an Israel-based tech company focused on offering a platform to allow sellers and buyers in exchanging products and services.
Today, the most powerful artificial intelligence systems employ a type of machine learning called deep learning. Their algorithms learn by processing massive amounts of data through hidden layers of interconnected nodes, referred to as deep neural networks. As their name suggests, deep neural networks were inspired by the real neural networks in the brain, with the nodes modeled after real neurons -- or, at least, after what neuroscientists knew about neurons back in the 1950s, when an influential neuron model called the perceptron was born. Since then, our understanding of the computational complexity of single neurons has dramatically expanded, so biological neurons are known to be more complex than artificial ones. To find out, David Beniaguev, Idan Segev and Michael London, all at the Hebrew University of Jerusalem, trained an artificial deep neural network to mimic the computations of a simulated biological neuron.