If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
You've heard of robotic bees, but have you heard of robotic butterflies? Chinese researchers have published a study that focuses on their efforts to develop solar-powered wings that imitate the flapping motion of a butterfly. They were able to develop wings that can do this at a rapid rate using light-driven actuators, and a new video shows all of the different ways they can utilize what they've created. The study was published in the journal ACS Applied Materials & Interfaces on January 16th, and a video put out on Wednesday explains how the project came together. When the wing was exposed to the heat of a strong light source, much like the Sun, the polymer layer on the bottom expanded significantly more than the metallic layer on the top, which caused the wing curl.
Inceoglu I, Thomas G, Chu C, Plans D, Gerbasi A (2018). Leadership behavior and employee well-being: an integrated review and a future research agenda. Lopez D, Brown AW, Plans D. (2019). Modelling and simulation of operation and maintenance strategy for offshore wind farms based on multiagent system. Murphy J, Brewer R, Coll M-P, Plans D, Hall M, Shiu SS, Catmur C, Bird G. (2019).
We propose a novel Bayesian approach to modelling nonlinear alignments of time series based on latent shared information. We apply the method to the real-world problem of finding common structure in the sensor data of wind turbines introduced by the underlying latent and turbulent wind field. The proposed model allows for both arbitrary alignments of the inputs and non-parametric output warpings to transform the observations. This gives rise to multiple deep Gaussian process models connected via latent generating processes. We present an efficient variational approximation based on nested variational compression and show how the model can be used to extract shared information between dependent time series, recovering an interpretable functional decomposition of the learning problem.
Artificial intelligence is at the peak of its hype curve, and its applications in the solar energy sector are amid a surge in popularity. Once upon a time confined solely to the domains of science fiction, this technology is transforming the energy landscape, altering how solar assets are managed, operated, and maintained. Year after year, the cumulative global PV capacity is increasing by gigawatts, which are highly dependent on operating conditions that are inherently variable and hard to predict. Also, further consolidation of these solar assets is leading to these portfolios growing not only in size but also in dispersity. These factors have made managing solar assets considerably more challenging.
Globally, thematic investing has tripled over the past five years to around $40.76 billion, per Morningstar Inc. This is steadily taking over the investment world, largely due to the introduction of theme-based funds and also for its long-term and easy-to-comprehend approach. Thematic investing requires investment in companies that can benefit from the technological, demographic and environmental changes (read: Top ETF Areas for 2020). Let's take a look at some of the themes that are currently in vogue. We are living in an era that is largely dominated by AI applications and technological advancements.
Solar power and advanced computing are a key cleantech intersection point. From renewables return on investment optimization to optimal rooftop commercial solar deployment, machine learning is helping us get more efficient and effective in our global transformation. Researchers in the US and China are using machine learning to discover new solar panel chemistries to increase the base efficiency and economic effectiveness of solar panels. They are trialing hundreds or thousands of combinations in virtual test beds before bringing them into the physical world, a key element of the machine-to-reality value proposition. Let's start in the United States with Jinxin Li, Basudev Pradhan, Surya Gaur, and Jayan Thomas from the sun-drenched campus of the University of Central Florida.
The raging Australian and Amazon wildfires have raised a burning question for all of us - why the very technology, that has been a major facilitator to human evolution and growth could not predict, manage or control its destruction? To those of us who are in the business of technology, it is time to ask a few tough questions in our boardroom meetings and take ownership of solving the problem. After all, what is growth worth if the planet itself is in peril? As someone who has witnessed the digital revolution unfold, I may not have a full-proof plan to address the climate emergency, in fact, we don't even have the visibility of all evolving technologies that may be required to solve the climate emergency. But, I am clear and convinced that we have to start now and start with the available technologies which in their own right are very powerful and transformational.
NEW YORK – Everyone has seen warnings at the end of email saying, "Please consider the environment before printing." But for those who care about global warming, you might want to consider not writing so many emails in the first place. More and more, people rely on their electronic mailboxes as a life organizer. Old emails, photos and files from years past sit undisturbed, awaiting your search for a name, lost address, or maybe a photo of an old boyfriend. The problem is that all those messages require energy to preserve them.
The concept of the circular economy is designed to replace the end-of-life economic system with restoration, use of renewable energy, and the elimination of waste through the better design of materials, products, systems and business models. Most leading organizations worldwide have begun identifying feasible opportunities in adopting sustainable business practices, embracing circular business models and leveraging disruptive technologies. For city planners, businesses and policymakers, a smart city transformation from the current economic model, knows as linear economy, to a circular economy encompasses high complexity. They need to consider material and energy, product design, business models, manufacturing, service and distribution processes and data management and more. However, embracing artificial intelligence in a circular economy can expedite the efforts of a smart city project needs, creating ways to accomplish sustainable development goals.