Dr. Roberto Paredes joined in 2000 the Computer Science Department of the Universidad Politécnica de Valencia (UPV), where he is until now serving as an Associate Professor. His current fields of interest include Statistical Pattern Recognition, Machine Learning, Biometrics, Large-scale problems, Multimedia Retrieval and Relevance Feedback. Dr. Paredes is the head of the PRHTL Research Centre and former President of the Spanish AERFAI Association. Moreover he is now the CTO and Co-founder of Solver Machine Learning, a spin-off of the UPV. Nowadays he is focused mainly in Deep Learning techniques and some of his DL solutions are applied to different sectors where Solver Machine Learning is working on.

For drone users, Hurricane Harvey is likely to be the event that propelled unmanned aircraft to become an integral part of government and corporate disaster-recovery efforts. In the first six days after the storm hit, the Federal Aviation Administration issued more than 40 separate authorizations for emergency drone activities above flood-ravaged Houston and surrounding areas. They ranged from inspecting roadways to checking railroad tracks to assessing the condition of water plants, oil refineries and power lines. That total climbed above 70 last Friday and topped 100 by Sunday, including some flights prohibited under routine circumstances, according to people familiar with the details. Industry officials said all of the operations--except for a handful flown by media outlets--were conducted in conjunction with, or on behalf of, local, state or federal agencies.

Samsung has received a permit to test self-driving vehicles in California, marking the entry of the world's largest smart phone maker four months after iPhone maker and arch rival Apple Inc received a permit. Its parent company in May secured permission from South Korean authorities to test a self-driving car fitted with its own sensors and software systems. At that time, South Korean officials said the company planned to use the car to develop a self-driving car algorithm that could drive in adverse weather. In a statement to Reuters, Samsung did not say what precisely what it planned to test in the United States but said it secured the permit'in pursuit of a smarter, safer transportation future.' The company, part of a massive conglomerate that makes everything from washing machines to heavy machinery, said it has'no plans to enter the car-manufacturing business.'

In this episode, MeiXing Dong talks with Leon Kuperman, CTO of CUJO, about cybersecurity threats and how to guard against them. They discuss how CUJO, a smart hardware firewall, helps protect the home against online threats.

A team of economists from the left-leaning Roosevelt Institute conclude in a new research study that implementing a guaranteed income of $1,000 a month for all Americans would accelerate U.S. economic growth by an additional 12.56% over eight years if it were financed by increased federal debt. If the same program were financed by increased redistributive taxes, the growth impact would be smaller, producing an additional 2.62% of GDP growth over 8 years. But the federal deficit would also, according to the model, shrink by 1.39%. In both scenarios, unemployment would also decrease. A universal basic income, or UBI, is a once-fringe policy proposal that has gained increasing public support in the U.S., including from many tech business leaders including Elon Musk and Mark Zuckerberg. In part, the idea is appealing because it would help insulate workers against labor market shocks likely to be produced by innovations like self-driving cars and artificial intelligence.

DataRobot enables government users to build and deploy highly accurate machine learning models in a fraction of the time. "Identifying and hiring the top data scientists is hard for any organization but none more so than the federal government," said Erin Hawley, VP of Public Sector for DataRobot. "Our platform makes it easier than ever for an organization to adopt data science into their environment, at a fraction of the cost and time. We're excited to partner with DLT as it is their vision to bring together a community of data science partners that will be a key advantage to federal government agencies." Recently launched, the DLT AnalyticsStackTM is a public sector focused Big Data, Analytics and Data Science'solution stack' providing agencies with a scalable reference framework that addresses rapidly evolving big data requirements and use cases.

In essence, people who interact with advanced technology want to be able to trust it appropriately, and then act on that trust. In interpersonal relationships, and otherwise, humans act largely based on trust. For example, a supervisor asks a subordinate to accomplish a task based on several factors that indicate they can trust them to accomplish that task. When consumers make purchases, they do so with trust that the product will perform as promised. Likewise, when using something like an autonomous vehicle, the user must be able to trust it appropriately in order to use it properly. With the rapid advancement of the capabilities of intelligent computing technology to do tasks that were previously assumed to be too complicated for computers, there has been much recent discussion regarding how humans can trust this technology - although the connection to trust is not always made explicit, per se.

Futuristic technologies are being adopted at an unprecedented rate -- millions of smart speakers are being sold across the U.S., smart homes are in the making which deploy several internet-of-things devices, and self-driving vehicles are being tested across many states. But even as these technologies are coming ever closer to realization, we haven't yet assessed their usage, impact and security protocols fully. While these technologies become commonplace, the security aspect, especially, has been largely ignored both by the government and the companies backing them. That said, the government has recently begun to act on the issue, making a start with the security guidelines for smart homes. Still, the little bit they have done, like the proposed The Internet Of Things Cybersecurity law, is inadequate as these guidelines cannot be a one-time exercise; they need to be updated periodically -- at least every quarter -- after assessing the risk environment.

A sheen is starting to appear on Rocky Blumhagen's forehead, just below his gray hair. He's marching in place in a starkly lit room decked out with two large flatscreens. On both of the TVs, a volcano lets off steam through wide cracks glowing with lava, their roar muffling the Andean percussion and flutes on the soundtrack. Rocky reaches out his left hand, as if to grasp a coin from midair, and one of them disappears with a brrring. "I don't know if I can do it," he says to a guy named Josh sitting nearby in a felt-covered lounge chair. He looks up from his iPad, watching Rocky, age 66, grab, jog, kick, and reach his way through the videogame. "Keep it up," Josh says as the heart monitor in the corner of the screen reads 129.

Alphabet Inc.'s (NASDAQ:GOOGL) (NASDAQ:GOOG) Google has been at the forefront of research into the nascent science of artificial intelligence (AI). The company first delved into AI more than six years ago and has become one of the foremost developers of the new technology. Innovations resulting from AI have come at a fast and furious pace in recent years. Virtual assistants are found on nearly every smartphone. The self-driving cars being developed by Google's Waymo unit have moved from the drawing board to the streets, and the company is currently testing its early rider program in the Phoenix, Arizona, metro area.