BRUSSELS – The European Commission's strategy for artificial intelligence focuses on the need to establish "trust" and "excellence." Recently proposed AI regulation, the Commission argues, will create trust in this new technology by addressing its risks, while excellence will follow from EU member states investing and innovating. With these two factors accounted for, Europe's AI uptake supposedly will accelerate. Unfortunately, protecting EU citizens' fundamental rights, which should be the AI regulation's core objective, appears to be a secondary consideration; and protections for workers' rights don't seem to have been considered at all. AI is a flagship component of Europe's digital agenda, and the Commission's legislative package is fundamental to the proposed single market for data.

This blog was written by an independent guest blogger. Historically, the idea of artificial intelligence (AI) saturating our world has been met with suspicion. Indeed, it's one of the more popular tropes of science fiction -- learning machines gain sentience that helps them take over the planet. While we're not even slightly close to that dystopian reality, we have reached a point at which AI has been significantly integrated into various aspects of our society. While this isn't without its risks, largely from a security standpoint, there are huge benefits.

Artificial intelligence and automation are the new farmhands as growers try to boost productivity amid soaring global demand for food, biofuels and other agricultural products. Why it matters: Farmers one day will be able to manage their fields from their kitchen table, using a smartphone or tablet to drive machinery, inspect plants and irrigate or treat crops with fertilizer or insecticides. Driving the news: Agriculture machinery giant Deere & Company last week acquired Bear Flag Robotics for $250 million. The big picture: With the United Nations predicting the world population will grow to 9.7 billion people by 2050, the agriculture industry says it will need to double the amount of food, feed, fiber and bioenergy it produces. Agriculture jobs are projected to grow just 1% from 2019 to 2029, slower than other occupations, according to the U.S. Bureau of Labor Statistics.

Artificial intelligence is rapidly evolving from a futuristic technology to one that embraces us in our daily lives. AI is displacing people, whether it is through moving employment to more productive activities or by automating the menial work. Such debates are certainly significant, but they overlook the greater transformational tale. After all, digital transformation occurs at all levels of organizations and industries. Let's take a look at the industries which are likely to get affected by AI Disruption.

This paper presents Bayesian parameter estimation for first order Grey system models' parameters (or sometimes referred to as hyperparameters). There are different forms of first-order Grey System Models. These include $GM(1,1)$, $GM(1,1| \cos(\omega t)$, $GM(1,1| \sin(\omega t)$, and $GM(1,1| \cos(\omega t), \sin(\omega t)$. The whitenization equation of these models is a first-order linear differential equation of the form \[ \frac{dx}{dt} + a x = f(t) \] where $a$ is a parameter and $f(t) = b$ in $GM(1,1|)$ , $f(t) = b_1\cos(\omega t) + b_2$ in $GM(1,1| cos(\omega t)$, $f(t) = b_1\sin(\omega t)+b_2$ in $GM(1,1| \sin(\omega t)$, $f(t) = b_1\sin(\omega t) + b_2\cos(\omega t) + b_3$ in $GM(1,1| \cos(\omega t), \sin(\omega t)$, $f(t) = b x^2$ in Grey Verhulst model (GVM), and where $b, b_1, b_2$, and $b_3$ are parameters. The results from Bayesian estimations are compared to the least square estimated models with fixed $\omega$. We found that using rolling Bayesian estimations for GM parameters can allow us to estimate the parameters in all possible forms. Based on the data used for the comparison, the numerical results showed that models with Bayesian parameter estimations are up to 45\% more accurate in mean squared errors.

We introduce OPtical ADversarial attack (OPAD). OPAD is an adversarial attack in the physical space aiming to fool image classifiers without physically touching the objects (e.g., moving or painting the objects). The principle of OPAD is to use structured illumination to alter the appearance of the target objects. The system consists of a low-cost projector, a camera, and a computer. The challenge of the problem is the non-linearity of the radiometric response of the projector and the spatially varying spectral response of the scene. Attacks generated in a conventional approach do not work in this setting unless they are calibrated to compensate for such a projector-camera model. The proposed solution incorporates the projector-camera model into the adversarial attack optimization, where a new attack formulation is derived. Experimental results prove the validity of the solution. It is demonstrated that OPAD can optically attack a real 3D object in the presence of background lighting for white-box, black-box, targeted, and untargeted attacks. Theoretical analysis is presented to quantify the fundamental performance limit of the system.

Roughly a year ago, Latent AI, a now three-year-old, Menlo Park, California-based startup, pitched a handful of investors during TechCrunch's Battlefield competition. It didn't win that contest, but that hasn't kept it from winning the interest of investors elsewhere. It just closed on $19 million in Series A funding in a round co-led by Future Ventures and Blackhorn Ventures, with participation from Booz Allen, Lockheed Martin, 40 North Ventures, and Autotech Ventures. The company has now raised $22.5 million altogether. Steve Jurvetson, the veteran investor and co-founder of Future Ventures, says of possible applications to think of "face-detection algorithms running locally within security cameras or appliances, or Siri-like voice interfaces working instantly," even when there's no network connectivity.

Muscat: A field visit for the Steering Committee team, in charge of supervising the zone designated for artificial intelligence (AI) at Duqm was organised by the Public Authority for Special Economic Zones and Free Zones (OPAZ). The steering committee includes representatives from several government entities, namely the Ministry of Defence, the Royal Oman Police (ROP), the Ministry of Higher Education, Scientific Research and Innovation, the Ministry of Transport, Communications and Information Technology, and Telecommunication Regulatory Authority (TRA). This came after the recent announcement of the OPAZ, allocating an area of 18 square kilometres of land to support and encourage the use of modern techniques, including AI experiments in the Special Economic Zone at Duqm (Sezad). "The Authority is seeking to achieve several key objectives, most importantly, the localisation of investment opportunities in the field of artificial intelligence, drone experiments and future technology," Ahmed bin Saleh Al Farsi, Chairman of the Committee, said. "In addition to building basic infrastructure to apply e-government strategy and smart cities, the Authority will also be creating and implementing research opportunities in the zone under the supervision of the committee for practical and academic uses, and to overcome the challenges and difficulties facing the implementation of AI projects, drones and future technology in the zone," he added.

Deep in the heart of Appalachia, modern science and America's bucolic past meet at a unique crossroad of scientific discovery and luddite lifestyles. The Quiet Zone, by journalist Stephen Kurczy, is the story of a sleepy small town that hosts the Green Bank radio telescope. But the presence of this installation comes at a price: due to the telescope's exceeding sensitivity, virtually every device and appliance that emits radio waves, Wi-Fi signals, or microwave radiation is banned for square miles around. That means that Green Bank, West Virginia has about as much tech today as it did in the 1950's (maybe even a little less) -- and some people very much like it that way. In the excerpt below, Pocahontas County attorney, Robert Martin, recounts the challenges of attempting to modernize the region without loosing a horde of gentrifiers upon it as well.

In this blog post, we'll answer the question, "How did the Brexit vote impact exchange rates between the British Pound and US Dollar?" To do so, we'll use causal inference techniques to estimate the impact of what statisticians call a "treatment," in this case a policy decision. Please note that this is a technical blog post aimed at educating about concepts and tools with public data, not any political or economic implications. The techniques we'll discuss here can apply to all kinds of scenarios, such as the impact of a marketing campaign or product introduction on sales. Causal inference is needed because we don't have a controlled experiment for this scenario. An ideal experiment contains carefully matched groups, except for the explanatory variable being investigated.