Many engineering problems require identifying feasible domains under implicit constraints. One example is finding acceptable car body styling designs based on constraints like aesthetics and functionality. Current active-learning based methods learn feasible domains for bounded input spaces. However, we usually lack prior knowledge about how to set those input variable bounds. Bounds that are too small will fail to cover all feasible domains; while bounds that are too large will waste query budget. To avoid this problem, we introduce Active Expansion Sampling (AES), a method that identifies (possibly disconnected) feasible domains over an unbounded input space. AES progressively expands our knowledge of the input space, and uses successive exploitation and exploration stages to switch between learning the decision boundary and searching for new feasible domains. We show that AES has a misclassification loss guarantee within the explored region, independent of the number of iterations or labeled samples. Thus it can be used for real-time prediction of samples' feasibility within the explored region. We evaluate AES on three test examples and compare AES with two adaptive sampling methods -- the Neighborhood-Voronoi algorithm and the straddle heuristic -- that operate over fixed input variable bounds.

Google CEO Sundar Pichai, speaking at a taped television event hosted by MSNBC and The Verge's sister site Recode, said artificial intelligence is one of the most profound things that humanity is working on right now and compared it to basic utilities in terms of its importance. Speaking to Recode's Kara Swisher and MSNBC's Ari Melber, Pichai said AI is "one of the most important things that humanity is working on. It's more profound than, I don't know, electricity or fire," adding that people learned to harness fire for the benefits of humanity but also needed to overcome its downsides, too. Pichai also said that AI could be used to help solve climate change issues, or to cure cancer. The remarks from the chief executive of Google, which is largely perceived as one of the world leaders in the development of artificial intelligence, came after Swisher asked repeatedly about AI's impact on jobs and observed that Silicon Valley tends to have a "shiny happy future" outlook about disruptive technologies.

In recent times, computation has become both pervasive and less constrained by Moore's Law. This is due in large part to the emergence of cloud computing and the rise of massive parallelism. The former has benefited from network improvements and ever increasing connectedness, the latter from the appropriation of hardware like Graphics Processing Units (GPUs) for general purpose computing. This computational leap, coupled with the process of disintermediation [1] taking place around the globe will continue to support revolutions like artificial intelligence (AI), as many have remarked. AI has a long and interesting history.

Elon Musk is CEO of Tesla and SpaceX, has plans to colonize Mars, and thinks AI may turn humans into its pets. But beyond the hype and his enormous net worth and Twitter presence, here's how Musk's companies are actually taking on ... virtually every industry. Elon Musk thinks and acts on a larger, more cosmic scale than we're accustomed to from entrepreneurs. Elon Musk has become a household name synonymous with the future. Whether he's working on electric vehicles (Tesla) or sending rockets into space (SpaceX), his larger-than-life reputation attracts its fair share of hero-worship. Musk can get a hundred breathless reporters to write about him and his companies with little more than a concept drawing and a tweet. His main projects take on almost every major industry and global problem conceivable, and imagine a disruptive fundamental rewiring of that space or sector. Whether he can deliver on his vast promises is often beside the point. And Musk himself is more than happy to feed into this hype machine. We've decided to take a different kind of look into the Musk ecosystem. Rather than assess Elon Musk and his companies on promises and hype, we wanted to look at the ways in which his companies are or are not transforming the industries in which they live -- with numbers, hard evidence, and concrete demonstrations of disruption. Read on for a deep dive into just how the money, invention, and ingenuity of Elon Musk and his companies are transforming these vital industries. First with SolarCity and now with Tesla, eliminating our dependence on fossil fuels and instead drawing energy from the "giant fusion reactor in the sky" aka the sun has been one of Musk's priorities for more than a decade. SolarCity, his first attempt to make solar power mainstream and ubiquitous, was at the forefront of the early 2000s "solar gold rush." In some ways it was a failure, but it remains important to understand its trajectory to understand how Musk and Tesla plan to take on the problem of renewable energy. SolarCity grew to become the country's largest provider of residential solar, then suffered some very public financial problems before being purchased by Musk's other company, Tesla, for $2 billion. That 2016 acquisition was controversial, with many observers calling it a "thinly veiled bailout." And yet Tesla's continuation of SolarCity's work has helped make a stronger case for solar than SolarCity was ever able to make on its own. Elon Musk originally suggested the concept for the company that became SolarCity to his cousins, Peter and Lyndon Rive, in 2004. The concept for SolarCity emerged out of a simple realization: the clock was running low on fossil fuels. The need for a replacement was emerging fast. "If they started now," as Men's Journal reports Musk telling Lyndon in 2004, "They might rule the market."

More melted fuel has been found at the bottom of the Fukushima power planet, seven years after Japan's worst nuclear disaster. Tokyo Electric Power Company (TEPCO), the operator of Japan's crippled nuclear plant, says a long telescopic probe has successfully captured images of the fuel inside the plant's Unit 2 primary containment vessel. The images showed that at least part of the fuel breached the core, falling to the vessel's floor. TEPCO says that that the status inside the primary containment vessel is still stable, and that there are no changes in radiation levels at the site boundaries of Fukushima Daiichi's Nuclear Power Plant. A massive earthquake and tsunami in 2011 caused three reactors at the Fukushima plant to melt.

He concludes with making the claim that humans probably represent the limit of vertebrate evolution. We will need to work together for the next phase in evolution, just like the unicellular organisms did when they became multicellular. All evolutionary processes are repeated patterns that look the same i.e. fractals. This gets quite interesting if we think of technology progress and adoption as a form of cultural evolution that follows a similar pattern. The AI era looks like a'zoomed out' fractal of the electricity era. We have a better ability to observe the fractal nature of cultural evolution now, because technology shifts are happening in shorter time scales following the law of accelerating returns. And it is going to get even faster.

In repeated stochastic games (RSGs), an agent must quickly adapt to the behavior of previously unknown associates, who may themselves be learning. This machine-learning problem is particularly challenging due, in part, to the presence of multiple (even infinite) equilibria and inherently large strategy spaces. In this paper, we introduce a method to reduce the strategy space of two-player general-sum RSGs to a handful of expert strategies. This process, called Mega, effectually reduces an RSG to a bandit problem. We show that the resulting strategy space preserves several important properties of the original RSG, thus enabling a learner to produce robust strategies within a reasonably small number of interactions. To better establish strengths and weaknesses of this approach, we empirically evaluate the resulting learning system against other algorithms in three different RSGs.

That person would establish liaisons with the state departments of transportation, public safety, administrative services and insurance, the state workforce transformation office, the adjutant general and the heads of the Ohio Turnpike and Public Utilities commissions.

Sometimes the speed of Amazon's delivery is bewildering. No matter how obscure your order, the retailer frequently promises same-day delivery. Is it that your neighborhood is full of fly-fishing buffs, or whatever your niche interest may be? Instead, it is likely that the company has already shipped the product to your nearest warehouse because it thought that you might order it. Magical as this might sound, it is the application of a technology known as demand sensing.

Artificial intelligence will be the main focus of this year's World Government Summit as Dubai aims to transform itself into the most digitally-savvy city. Beyond smart cities, AI is seen as a key pillar in providing services across the board. "Every phone will be like a personal computer," said Hussain Lootah, director general at the emirate's municipality. "Providing it in hardware and robotics will maintain the city's landscape too – we plant 70 million flowers every year but AI will help save us a lot of time. We will also have'smart canes' for the elderly and disabled."