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) …
Future homes will employ potentially hundreds of Internet of Things (IoT) devices whose sensors may inadvertently leak sensitive information. A previous Communications Inside Risks column ("The Future of the Internet of Things," Feb. 2017) discusses how the expected scale of the IoT introduces threats that require considerations and mitigations.2 Future homes are an IoT hotspot that will be particularly at risk. Sensitive information such as passwords, identification, and financial transactions are abundant in the home--as are sensor systems such as digital assistants, smartphones, and interactive home appliances that may unintentionally capture this sensitive information. IoT device manufacturers should employ sensor sensor permissioning systems to limit applications access to only sensor data required for operation, reducing the risk that malicious applications may gain sensitive information. For example, a simple notepad application should not have microphone access.
When six-foot-four inch Marty first rolled into Stop & Shop, the robot walked into history. Social robot experts say it is among the first instance of a robot deployed in a customer environment, namely supermarkets in the Northeast. Marty rolls around the store looking for spills with its three cameras. It does take the place of the human worker, called an associate, that did the same thing, but it means the associate can do something else. Doing the walk-around of the store is seen as a mundane task.
What does interior design have in common with AI art? If you think it is a tricky question and you are tempted to say absolutely nothing, well, stop for a moment because the answer is instead quite simple: they both have an impact on the space where people live in and therefore on people lives. The psychology of space is at the heart of many businesses along with a strong vision of bringing creativity into a project that must show also a distinctive stamp . Creating a project for a commercial area is different that working on one for hospitality or a hospital. The crucial aspect is to tune in with the client and have a solid vision, making a space that is enjoyable and where people want to spend time in and go back to.
In 2004, the U.S. Department of Defense issued a challenge: $1 million to the first team of engineers to develop an autonomous vehicle to race across the Mojave Desert. Though the prize went unclaimed, the challenge publicized an idea that once belonged to science fiction -- the driverless car. It caught the attention of Google co-founders Sergey Brin and Larry Page, who convened a team of engineers to buy cars from dealership lots and retrofit them with off-the-shelf sensors. But making the cars drive on their own wasn't a simple task. At the time, the technology was new, leaving designers for Google's Self-Driving Car Project without a lot of direction.
Take an isolated tribe in the Amazon rainforest. These people have had no contact with civilization, and have never seen anyone who looked different from them. Imagine -- completely cut-off from the 21st century. This is a photograph of the low-flying helicopter that due to a diversion because of a storm, took the National Geographic photographer Ricardo Stuckert out there, above the tribe. What did the helicopter look like to them? In fact, they shot arrows at the helicopter!
I have now played Apex Legends for over 500 hours. The online multiplayer shooter, developed by Californian studio Respawn Entertainment and released in February 2019, has been my obsession all year, seeing off a variety of pretenders from Doom Eternal to Animal Crossing: New Horizons. Set in a science-fiction universe tied to Respawn's successful Titanfall series, it is another title in the battle royale genre alongside the Goliath that is Fortnite, as well as PlayerUnknown's Battlegrounds and Call of Duty: Warzone. You land in a hi-tech future landscape with two team-mates and then you scramble about, finding weapons, while 19 other teams try to kill you and everyone else. The last team left alive is the winner.
User Interface (UI) design is an creative process that involves considerable reiteration and rework. Designers go through multiple iterations of different prototyping fidelities to create a UI design. In this research, we propose to modify the UI design process by assisting it with artificial intelligence (AI). We propose to enable AI to perform repetitive tasks for the designer while allowing the designer to take command of the creative process. This approach makes the machine act as a black box that intelligently assists the designers in creating UI design. We believe this approach would greatly benefit designers in co-creating design solutions with AI.
We propose modeling designer style in mixed-initiative game content creation tools as archetypical design traces. These design traces are formulated as transitions between design styles; these design styles are in turn found through clustering all intermediate designs along the way to making a complete design. This method is implemented in the Evolutionary Dungeon Designer, a prototype mixed-initiative system for roguelike games. We present results both in the form of design styles for rooms, which can be analyzed to better understand the kind of rooms designed by users, and in the form of archetypical sequences between these rooms. We further discuss how the results here can be used to create style-sensitive suggestions. Such suggestions would allow the system to be one step ahead of the designer, offering suggestions for the next phase, assuming that the designer will follow one of the archetypical design traces.
Interactive adaptive systems powered by Reinforcement Learning (RL) have many potential applications, such as intelligent tutoring systems. In such systems there is typically an external human system designer that is creating, monitoring and modifying the interactive adaptive system, trying to improve its performance on the target outcomes. In this paper we focus on algorithmic foundation of how to help the system designer choose the set of sensors or features to define the observation space used by reinforcement learning agent. We present an algorithm, value driven representation (VDR), that can iteratively and adaptively augment the observation space of a reinforcement learning agent so that is sufficient to capture a (near) optimal policy. To do so we introduce a new method to optimistically estimate the value of a policy using offline simulated Monte Carlo rollouts. We evaluate the performance of our approach on standard RL benchmarks with simulated humans and demonstrate significant improvement over prior baselines.
Interoperability in the construction sector is a key issue and researchers, developers and designers have tackled since the introduction of CAD systems. Traditionally, engineers, architects and site operators interact and track their information exchange through paper or digitalized drawings and e-mails. With the introduction of Building Information Modelling (BIM) techniques and tools, operators are using new solutions and methods to keep track and exploit these data. Cover image: ifcOWL ontology (version IFC4ADD2) visualized thanks to WebVOWL, available hereWhat has been described as traditional method corresponds to Level 0 in well-known BIM levels definition. The concept of BIM level 1 represents the criteria needed for the full collaboration for the industry.