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) …
It is 2021, and I'm not playing on an Xbox, PlayStation or Nintendo Switch. This isn't an old Atari 2600 previously collecting dust in a closet, or an emulator I found online. It's a fresh home video game console: the Atari VCS. Having spent some time playing Atari VCS, it's easy to get trapped by the nostalgic feelings of popping in my "Asteroids" or "Missile Command" cartridges. However, the VCS delivers plenty of modern touches such as wireless, rechargeable controllers and Wi-Fi support for downloadable games.
Sometime around September 2019, my boyfriend was trying to convince me to do something I had no interest in: learn to play video games. To be polite, I took the Nintendo Switch controller from his hands and, for the next several hours, snapped with considerable anger whenever I forgot the difference between A, B, X, and Y, or the godforsaken purposes of ZL and ZR. I have made a concerted and largely successful effort to stay away from pursuits that require hand-eye coordination in all my years. In high school, I hid from the ball during soccer scrimmages. I developed a reputation during college sessions of Mario Kart with friends for picking up the controller and immediately driving my car into a ditch.
Kentucky-based Aviation Safety Resources is developing ballistic parachutes for use in aircraft ranging from 60 lbs to 12,000 lbs. The Air Force's Agility Prime program awarded a phase I small business technology transfer (STTR) research contract to Jump Aero and Caltech to create an electronic parachute powered by machine learning that would allow the pilot to recalibrate the flight controller in midair in the event of damage, the company announced on April 7. "The electronic parachute is the name for the concept of implementing an adaptive/machine-learned control routine that would be impractical to certify for the traditional controller for use only in an emergency recovery mode -- something that would be switched on by the pilot if there is reason to believe that the baseline flight controller is not properly controlling the aircraft (if, for example, the aircraft has been damaged in midair)," Carl Dietrich, founder and president of Jump Aero Incorporated, told Avionics International. This technology was previously difficult to certify because of the need for deterministic proof of safety within these complex systems. The research was sparked when the Federal Aviation Administration certified an autonomous landing function for use in emergency situations which created a path for the possible certification of electronic parachute technology, according to Jump Aero. The machine-learned neural network can be trained with non-linear behaviors that occur in an aircraft in the presence of substantial failures such those generated by a bird strike, Dietrich said.
I admit, I approached this bizarro platformer with a certain amount of trepidation, on account of occasionally having a rocky time playing games with my beloved partner. People imagine it's some holy-grail nirvana to have a gamer partner, but the truth is Keza is just a bit too good at games to be wholly tolerant towards others (mostly: me) flailing around haplessly – especially in Nintendo games, effectively her second native language. Keza is a classic back-seat gamer, always spotting the solution in 0.3 seconds and barking at you for getting there fractionally later. And yet, It Takes Two has a pleasant, companionable feel to it – possibly because of the madcap cooperation at its heart. For once, our slapstick failures to nail the arm down of an angry boss were cause for gentle ribbing and hoots of laughter, rather than impatient harrumphing.
For us to build our API, we are going to leverage the Flask micro-framework. Due to various reasons such as being extremely powerful, simple to use, and very good documentation, Flask is a popular choice for microservices in Python -- See Documentation. "Micro" does not mean that your whole web application has to fit into a single Python file (although it certainly can), nor does it mean that Flask is lacking in functionality. The "micro" in microframework means Flask aims to keep the core simple but extensible. Let's first take a look at our directory structure…
Canadian boffins are testing semi-autonomous exoskeletons that could help people with limited mobility walk again without the need for implanted sensors. Researchers at the University of Waterloo, Ontario, are hard at work trying to combine modern deep-learning systems with robotic prostheses. They hope to give disabled patients who have suffered spinal cord injuries or strokes, or are inflicted with conditions including multiple sclerosis, spinal, cerebral palsy, and osteoarthritis, the ability to get back on their feet and move freely. The project differs from other efforts for amputees that involve trying to control the movement of machines using electrodes implanted in nerves and muscles in the limbs and brain, explained Brock Laschowski, a PhD student at the university who is leading the ExoNet study. "Our control approach wouldn't necessarily require human thought. Similar to autonomous cars that drive themselves, we're designing autonomous exoskeletons that walk for themselves."
By connecting control systems, from industrial gateways, to edge servers, and subsequently to enterprise infrastructure, automation companies hope to gain operational insights that will yield efficiency and productivity. For example, the Siemens AG factory in Amberg, Germany, where the company manufactures programmable logic controllers (PLCs), has undergone this digital transformation to enable use cases ranging from AI-enabled quality inspection to predictive maintenance. Historically, automation systems at the Amberg facility have operated as independent, isolated units without a network connection to each of the other systems in a physical cluster or the broader factory network. As a result, the machine data required to perform functions like predictive maintenance remained trapped within silos on individual devices, and could not be exposed to higher-order analytics systems that perform machine learning tasks. To facilitate advanced Industry 4.0 use cases, the factory needed an architectural redesign that implemented networking and compute infrastructure at the edge without uprooting existing automation endpoints.
We study the problem of adaptive control of the linear quadratic regulator for systems in very high, or even infinite dimension. We demonstrate that while sublinear regret requires finite dimensional inputs, the ambient state dimension of the system need not be bounded in order to perform online control. We provide the first regret bounds for LQR which hold for infinite dimensional systems, replacing dependence on ambient dimension with more natural notions of problem complexity. Our guarantees arise from a novel perturbation bound for certainty equivalence which scales with the prediction error in estimating the system parameters, without requiring consistent parameter recovery in more stringent measures like the operator norm. When specialized to finite dimensional settings, our bounds recover near optimal dimension and time horizon dependence.
We study planning problems for continuous control systems with uncertainty caused by measurement and process noise. The goal is to find an optimal plan that guarantees that the system reaches a desired goal state within finite time. Measurement noise causes limited observability of system states, and process noise causes uncertainty in the outcome of a given plan. These factors render the problem undecidable in general. Our key contribution is a novel abstraction scheme that employs Kalman filtering as a state estimator to obtain a finite-state model, which we formalize as a Markov decision process (MDP). For this MDP, we employ state-of-the-art model checking techniques to efficiently compute plans that maximize the probability of reaching goal states. Moreover, we account for numerical imprecision in computing the abstraction by extending the MDP with intervals of probabilities as a more robust model. We show the correctness of the abstraction and provide several optimizations that aim to balance the quality of the plan and the scalability of the approach. We demonstrate that our method can handle systems that result in MDPs with thousands of states and millions of transitions.
Best known for its Wi-Fi controllers that imbue dumb room air conditioners with smarts, Sensibo has leveraged its expertise to build the Sensibo Pure, a Wi-Fi-connected air purifier for small rooms. The Senisbo Pure can work in conjunction with Sensibo's other products to improve air quality, but it doesn't depend on the presence of one. The tradeoff for this air purifier's relatively small size--it measures 7.68 x 7.68 x 15.28 inches (WxDxH)--is that it can cover rooms only up to 173 square feet (e.g., a room with dimensions of about 13 x 13 feet with a typical 8-foot ceiling). Multiple Sensibo Pure's can be deployed around your home and controlled from its mobile app once they're connected to your Wi-Fi network (2.4GHz only). A feature Sensibo calls Pure Boost can increase that coverage to 294 square feet for a limited time (more on that in a bit).