We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. All computer algorithms must follow rules and live within the realm of societal law, just like the humans who create them. In many cases, the consequences are so small that the idea of governing them isn't worth considering. Lately, though, some artificial intelligence (AI) algorithms have been taking on roles so significant that scientists have begun to consider just what it means to govern or control the behavior of the algorithms. For example, artificial intelligence algorithms are now making decisions about sentencing in criminal trials, deciding eligibility for housing, or setting the price of insurance.

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run their business. When dentists analyze X-rays, they do so in bright rooms and on computers that aren't specialized for radiology, often with the patient sitting right next to them. Is it any wonder, then, that dentists given the same X-ray might propose different treatments? "Dentists are doing a great job given all the things they have to deal with," says Wardah Inam SM '13, Ph.D. '16.

Imagining military artificial intelligence (AI) applications can make one dream up scenarios like those in the Terminator films, but in reality, AI solutions for defense are much more mundane and focused on improving decision-making for humans, whether they're aircraft maintenance personnel; pilots; or intelligence, surveillance, and reconnaissance (ISR) analysts, says John Canipe, Director of Business Development, Air Force, at SparkCognition Government Systems, during a conversation we had at his company headquarters in Austin, Texas. We also discussed the difference between AI and machine learning (ML), how AI is being applied across multiple military domains, and more. MCHALE: Please provide a brief description of your responsibility within SparkCognition Government Systems and your group's role within the company. CANIPE: As Director of Business Development, Air Force, my current responsibilities are product development, capture management, price/licensing of products, and generating new and recurring sales. MCHALE: We often see AI/ML [artificial intelligence/machine learning] in the same sentence, or used to describe the same thing, but what is the actual difference between AI and ML? CANIPE: Differentiating AI from ML is a struggle everyone is having right now.

Research into Artificial Intelligence (AI) has been ongoing for decades, with early proposals dating back to 1950. However, only in recent years, it has seen a resurgence in popularity thanks to the increased availability of computing power and the growth of big data and machine learning. AI is the ability of machines to perform tasks that ordinarily require human intelligence, such as understanding natural language and recognizing objects. With the rapid expansion of AI, there are opportunities for businesses and individuals alike to capitalize on its capabilities. AI is a field of computer science and engineering focused on the creation of intelligent agents, which are systems that can reason, learn, and act autonomously.

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run their business. When dentists analyze X-rays, they do so in bright rooms and on computers that aren't specialized for radiology, often with the patient sitting right next to them. Is it any wonder, then, that dentists given the same X-ray might propose different treatments? "Dentists are doing a great job given all the things they have to deal with," says Wardah Inam SM '13, PhD '16.

We present extensions to the Open Neural Network Exchange (ONNX) intermediate representation format to represent arbitrary-precision quantized neural networks. We first introduce support for low precision quantization in existing ONNX-based quantization formats by leveraging integer clipping, resulting in two new backward-compatible variants: the quantized operator format with clipping and quantize-clip-dequantize (QCDQ) format. We then introduce a novel higher-level ONNX format called quantized ONNX (QONNX) that introduces three new operators -- Quant, BipolarQuant, and Trunc -- in order to represent uniform quantization. By keeping the QONNX IR high-level and flexible, we enable targeting a wider variety of platforms. We also present utilities for working with QONNX, as well as examples of its usage in the FINN and hls4ml toolchains. Finally, we introduce the QONNX model zoo to share low-precision quantized neural networks.

From cyber operations to disinformation, artificial intelligence extends the reach of national security threats that can target individuals and whole societies with precision, speed, and scale. As the U.S. competes to stay ahead, the intelligence community is grappling with the fits and starts of the impending revolution brought on by AI. The U.S. intelligence community has launched initiatives to grapple with AI's implications and ethical uses, and analysts have begun to conceptualize how AI will revolutionize their discipline, yet these approaches and other practical applications of such technologies by the IC have been largely fragmented. As experts sound the alarm that the U.S. is not prepared to defend itself against AI by its strategic rival, China, Congress has called for the IC to produce a plan for integration of such technologies into workflows to create an "AI digital ecosystem" in the 2022 Intelligence Authorization Act.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Supreme Court Thursday ruled 6-3 that New York's regulations that made it difficult to obtain a license to carry a concealed handgun were unconstitutionally restrictive, and that it should be easier to obtain such a license. The existing standard required an applicant to show "proper cause" for seeking a license, and allowed New York officials to exercise discretion in determining whether a person has shown a good enough reason for needing to carry a firearm. Stating that one wished to protect themselves or their property was not enough.

Mysterious drones hit a major Russian oil refinery in Novoshakhtinsk in the Rostov region, which is near the border with Ukraine, the plant's management said Wednesday. The incident came as the fight between Ukraine and Russia is about to enter its fifth month. The strike sent a ball of flame and black smoke straight into the sky, prompting the suspension of operations, the authorities told local media. A video was shared on the Telegram messaging service, showing a twin-boom tail configured drone crashing into the Russian oil refinery. There are speculations it was a "kamikaze" drone strike conducted by the Ukrainian Armed Forces, according to the Drive.

Temperatures are heating up across the country. Peggy digs deep into the topic of climate change and a new platform that might help in the fight against climate change. She says we know temperatures have oscillated from warnings of an impending ice age to a steady increase in carbon emissions for decades. Now, we need to act. She also discusses: Climate-driven disasters like heat and how it impacts mental health and acuity and worker safety and productivity—and our bottomline. The Heat Action Platform, a place for city officials to find guidance on reducing the impact of extreme heat. What businesses, organizations, and individuals can do to take action.   (6/21/22 - 776) IoT, Internet of Things, Peggy Smedley, artificial intelligence, machine learning, big data, digital transformation, cybersecurity, blockchain, 5G, cloud, sustainability, future of work, podcast This episode is available on all major streaming platforms. If you enjoyed this segment, please consider leaving a review on Apple Podcasts.