Machines' ability to learn by processing data gleaned from sensors underlies automated vehicles, medical devices and a host of other emerging technologies. But that learning ability leaves systems vulnerable to hackers in unexpected ways, researchers at Princeton University have found. In a series of recent papers, a research team has explored how adversarial tactics applied to artificial intelligence (AI) could, for instance, trick a traffic-efficiency system into causing gridlock or manipulate a health-related AI application to reveal patients' private medical history. As an example of one such attack, the team altered a driving robot's perception of a road sign from a speed limit to a "Stop" sign, which could cause the vehicle to dangerously slam the brakes at highway speeds; in other examples, they altered Stop signs to be perceived as a variety of other traffic instructions. "If machine learning is the software of the future, we're at a very basic starting point for securing it," said Prateek Mittal, the lead researcher and an associate professor in the Department of Electrical Engineering at Princeton.
Earlier this month the thermal imagery manufacturer FLIR bought the UAV developer Aeryon Labs for $200 million, beating their previous record in publicly disclosed drone investments of $134M. This has been yet another signal that even though the drone industry suffered some hard hits in 2018, the period of consolidation, larger investments and serious R&D advances is ahead. In fact, if one were to look at merely the investment figures for 2018, it wouldn't even be that easy to tell that the drone industry struggled. Records were set, partnerships formed, and accelerators continued to support exceptional start-ups. A total of $702 million was invested into the drone industry in 2018 (up from $625M in 2017), $483 million of which was funnelled into the top 20 drone deals.
Regardless of the industry you work in, you've no doubt heard about artificial intelligence (AI) and its potential in changing the world around us. The technology has been a source of debate in the private and public sectors for more than 50 years, and yet it has only been in the last decade that we've begun to really see momentum build in the AI space. But what actually is AI? Leaving the jargon to one side, it should simply be understood as the use of computer systems to perform tasks that would normally require human intelligence. To date, there has been some significant progress made in the adoption of AI technologies, with industries from financial services to healthcare demonstrating a keen willingness to use AI to their advantage. At the same time, investment has been pouring in at unprecedented levels; investment into UK AI businesses alone now exceeds £3.8 billion according to Big Innovation Centre and Deep Knowledge Analytics.
Volvo has unveiled its first fully electric vehicle, and with it, an important commitment to decarbonization. The carmaker says it will bring out a new electric model every year and reduce production of traditional combustion vehicles and hybrids, so that by 2025, half of its sales will be electric, and the other half will be a decreasing number of plug-in hybrids, with their non-electric motors produced outside the company. The launch and mass marketing of Volkswagen's ID.3, the increased manufacturing capacity of market leader, Tesla, after opening a factory in China, and the efforts of other manufacturers to quickly electrify their catalog, leaves no doubt about where the motor industry is going: the transition to electric vehicles is no longer about when, but at what speed it takes place. If you were thinking of purchasing a new vehicle with an internal combustion engine, know that you are buying obsolete technology. A strike by GM workers over a production switch to electric vehicles, which will mean smaller workforces, says it all.
How are experts looking at the same present and arriving at such different and contradictory futures? Here's a look at five scenarios, and the paths that getting there might take. As artificial intelligence becomes more powerful, a lot of current jobs are doomed to disappear. University of Oxford researchers in 2017 estimated that nearly half of all U.S. jobs were at risk from AI-powered automation. Other forecasts come up with different estimates, but by any measure, the number of lost jobs is potentially huge. Automation has already made manufacturing, mining, agriculture and many other industries much less labor-intensive. One study estimated that from 1993 to 2007, each industrial robot replaced 3.3 workers.
The autonomous vehicle industry is in the process of rerouting. Early AV leaders said fully autonomous cars would hit the mass market by 2020 or 2021--Elon Musk even promised a self-driving Tesla by 2017. But with the end of the decade in sight, two things are certain: The autonomous future remains a long way off, and AV-makers are going to have to change their plan for how to get there. In this presentation, we show you what this new path looks like and lay out the step-by-step changes we'll see on the way to full autonomy. We make the case that AV developers' early shortcomings have ushered in a new era of collaboration and realism.
Artificial Intelligence (AI) and Machine Learning (ML) are amongst the emerging trends in Business and Marketing. Yet, a lot of this cleverness is located in the Cloud. In a not too distant future, several applications will enter our lives that require an increased amount of Intelligence and Computation being implemented closer to the user. Be it for reasons of speed, energy-efficiency or privacy. Think about self-driving vehicles who have to respond more quickly than the time it takes to send data up and down to the cloud.
One of the technologies we are seeing being trialled and deployed in airports is robotic assistants. The humanoid robots are positioned around the airport terminal assisting passengers with queries and information. By making use of Artificial Intelligence (AI) and Machine Learning, the robots can process large amounts of data, with real-time updates to enable them to provide the latest information to passengers. This technology is starting to be used in some select airports but for different functions. Munich Airport in Germany is using robotic assistants primarily for information.
Policies are the foundation for any successful organization. Policies are the rules, or laws, of an organization. Heck, one could argue that an organization's culture is better defined by its policies than it is by the character of its leadership team. Unfortunately, the management, creation and execution of policies haven't changed much since the days of "time-and-motion studies". In many cases, policies are nothing more than a static list of what-if rules that govern what workers are to do in well-defined situations.
This 2019 Radiation activist are warning that the New 5G networks are a'massive health experiment' and a'Global catastrophe' waiting to happen. The New 5G Network in the foreground of controversy, promises lightning-fast speeds and the ability to power new technologies like self-driving cars and advanced augmented and virtual reality experiences. But an undercurrent to all of the things we can do with 5G is concern about what 5G can do to us. There are concerns that the very high-frequency spectrum known as millimeter wavelengths used in early deployments to make 5G a reality could pose adverse health effects for the public. A leading activist on the issue of electromagnetic radiation and its negative impacts on public health has described the rollout of 5G as a "massive health experiment" which could "become a global catastrophe."