If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Tensorflow is an open-source end-to-end machine learning framework that makes it easy to train and deploy the model. It consists of two words - tensor and flow. A tensor is a vector or a multidimensional array that is a standard way of representing the data in deep learning models. Flow implies how the data moves through a graph by undergoing the operations called nodes. It is used for numerical computation and large-scale machine learning by bundling various algorithms together.
Artificial intelligence (AI) is all the rage now. It's impacting numerous industries globally and changing the way we do things. One of the critical industries AI is making strides in is the financial technology "fintech" industry. AI now plays a significant role in facilitating financial services, replacing what required manual work a few years ago. For example, banks now apply AI to assess credit risks with high accuracy.
AI is fantabulous and in demand in the banking and finance sector. The technological furtherance in AI – machine learning, computer vision and natural language processing has downright remodelled the business world. The expert opinion states that the growth of the AI market would reach $190 billion by the year 2025! The application of conversational assistants or chatbots is one of the substantial benefits of AI in the banking and finance sector. As opposed to an employee, a chatbot is at one's disposal 24 hours a day, and clients are more complacent using this software programme to answer inquiries and complete many typical banking procedures that traditionally called for face-to-face interaction.
In the days before Yulia Pajevska, 53, was abducted by Russian-backed separatists, the decorated Ukrainian volunteer medic had been evacuating Ukrainians from the besieged city of Mariupol. Her husband, Vadym Puzanov, had only had brief contact with Pajevska through messages and short videos when the patchy internet and her hectic schedule allowed for updates about the dramatic evacuations and airlifts she had been organising in the southeast of the country. Puzanov found out about his wife's abduction when his friend rang him to say he had come across a video uploaded onto Facebook by a former Ukrainian politician which claimed that Pajevska and her driver Serhii were illegally detained at a checkpoint near the town of Manhush in the Donetsk region on March 16. "At first I was shocked and couldn't believe it," Puzanov recalls. According to Puzanov, who is currently in the Ukrainian capital Kyiv, Pajevska and Serhii had been evacuating women and children along a so-called humanitarian corridor between the southeastern cities of Mariupol and Zaporizhzhia when they were stopped and detained.
Artificial Intelligence in financial services is still largely filled with untapped potential. While many bankers may think of things like chatbots and fraud monitoring when it comes to AI, in reality the technology can be used in just about any conceivable part of a bank or credit union. For the most part the industry has not even scratched the surface of how AI can transform banking. Here are some of the top ways financial institutions can deploy artificial intelligence in 2022 and beyond. Let's start with the most obvious application first.
Editor's Note: It has come to our attention that several statements in this article have been based on sources that have later been recanted and are factually incorrect. Court documents from the case show that ShotSpotter accurately showed the location of the gunfire as reported in both the real-time alert, as well as in the forensic report. The initial alert was classified as a possible firework, but through their standard procedure of human analysis, it was determined within one minute to be gunfire. The evidence that ShotSpotter provided was later withdrawn by the prosecution and had no bearing on the results of the case. Sixty-five-year-old Michael Williams was released from jail last month after spending almost a year in jail on a murder charge.
The negative applications of deepfakes can be controlled through blockchain and other deep learning-based image forgery detection tools. However, there is more to deepfakes than just negative applications. Ever since the emergence of deepfakes, they have been normally associated with pranks or cybercrimes. Accordingly, there are several pieces that discuss the ways in which deepfake-related problems can be resolved through blockchain or deep learning-based image forgery detection. The concept of deepfakes, also known as synthetic media, is one of the more irreverent applications of AI and computer vision.
The US is hoping to combat the growing criminal use of drones with new rules that will allow local law enforcement agencies and other organisations to have counter-drone systems. At present, legal restrictions in the US hamper efforts to tackle such activity. The Federal Aviation Administration bans anyone from interfering with an aircraft in flight, including drones, while the Federal Communications Commission forbids jamming radio signals, a common anti-drone technique. Only a few federal agencies are permitted to shoot down drones in extreme circumstances, such as threats to critical infrastructure. US police agencies have been clamouring for counter-drone systems in the face of increasing criminal and careless use of drones.
Image: DroneShield RfPatrol body-worn C-UAS device with enrolled firmware upgrades. DroneShield has announced it has commenced a release of a ground-breaking software update across the global fleet of its C-UAS portable, vehicle/ship based and fixed site devices, deployed with military, intelligence community, Homeland Security, law enforcement, critical infrastructure and other users. Enrolled devices receive quarterly firmware updates of the proprietary DroneShield RFAI Artificial Intelligence engine, with periodic quarters being major enhancements, such as this 2Q22 release. Angus Bean, DroneShield Chief Technology Officer, commented, "DroneShield offers unparalleled C-UAS performance as the original pioneer in this sector. Ongoing R&D programs sustain the cutting-edge nature of our products, protecting and serving our user community. We are excited about the enhancements to the performance of our deployed fleet of devices, developed, field-tested, and rolled out in a highly expedient manner."