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) …
The big rub on the first generation of graph databases was that although RDF triple stores were great at storing the simple sentence, they had a hard time with the adverbs, adjectives and clarifying phrases of your data story. If I wanted to store'John is a carpenter since 2001' or'John from Alberta Canada is a carpenter liked by 702 people', the syntax of old-school triple stores had a more tedious, but not impossible way of handling it. It involved creating extra nodes that were confusing to some and a process called reification. Until about a year ago, labeled property graphs (LPG) were better at color and detail than RDF, having a more intuitive syntax for clarifying adverbs, adjectives, and phrases. That was, of course, until recently.
"AI is a fundamental risk to the existence of human civilization in a way that car accidents, airplane crashes, faulty drugs or bad food were not -- they were harmful to a set of individuals within society, of course, but they were not harmful to society as a whole", said Musk at the National Governors Association. At the moment Elon Musk is working hard to combat coming to AI with his nonprofit Open AI and is planning to link the human mind to computers at his company Neuralink.
Japanese police arrested or took other action against 115 people for civil aviation law violations linked to unauthorized drone flights in 2019, up 31 from the previous year, government data showed Thursday. The National Police Agency tally included 51 foreign nationals, of whom 19, the largest group, were Chinese. Seven were from the United States. Last year, the number of cases that led to police actions stood at 111. Of them, 54 cases happened as offenders tried to take commemorative pictures, while 34 cases were flight operation exercises, according to the NPA data.
UPS has partnered with the German tech company Wingcopter to build a fleet of rugged, high speed delivery drones. The drones will be based on a model designed by Wingcopter, which can travel at speeds of up to 150mph and has a range of 75 miles. The drones can also endure a variety of difficult weather conditions, including wind speeds of up to 45mph. The agreements marks the first external partnership for UPS's Flight Forward program, which is focused on developing a range of drone delivery options, according to a report in TechCrunch. 'Drone delivery is not a one-size-fits-all operation,' UPS's Bala Ganesh said.
UPS Flight Forward (UPSFF) is collaborating with German drone-maker Wingcopter to develop the next generation of package delivery drones for a variety of use cases in the United States and internationally. UPSFF is a subsidiary of UPS dedicated to drone delivery. UPS chose Wingcopter for its unmanned aircraft technology and its track record in delivering a variety of goods over long distances in multiple international settings. "Drone delivery is not a one-size-fits-all operation," said Bala Ganesh, vice president of the UPS Advanced Technology Group. "Our collaboration with Wingcopter helps pave the way for us to start drone delivery service in new use-cases. UPS Flight Forward is building a network of technology partners to broaden our unique capability to serve customers and extend our leadership in drone delivery."
In the last post in the series, we defined what interpretability is and looked at a few interpretable models and the quirks and'gotchas' in it. Now let's dig deeper into the post-hoc interpretation techniques which is useful when you model itself is not transparent. This resonates with most real world use cases, because whether we like it or not, we get better performance with a black box model. For this exercise, I have chosen the Adult dataset a.k.a Census Income dataset. Census Income is a pretty popular dataset which has demographic information like age, occupation, along with a column which tells us if the income of the particular person 50k or not. We are using this column to run a binary classification using Random Forest.
Drones can do many things, but avoiding obstacles is not their strongest suit yet – especially when they move quickly. Although many flying robots are equipped with cameras that can detect obstacles, it typically takes from 20 to 40 milliseconds for the drone to process the image and react. It may seem quick, but it is not enough to avoid a bird or another drone, or even a static obstacle when the drone itself is flying at high speed. This can be a problem when drones are used in unpredictable environments, or when there are many of them flying in the same area. Reaction of a few milliseconds In order to solve this problem, researchers at the University of Zurich have equipped a quadcopter (a drone with four propellers) with special cameras and algorithms that reduced its reaction time down to a few milliseconds – enough to avoid a ball thrown at it from a short distance.
Experts have got together to discuss the future of home automation and reveal their predictions for the future of home automation. According to futurologists, around 90 per cent of household chores will be automated thanks to robots, drones and AI by 2040. These will be carried out by drones, robots and virtual AI butlers that will help with laundry, dusting and even making the bed, they claim. Kings College Professor Mischa Dohler and futurologist Dr Ian Pearson created a report with consumer site comparethemarket.com to predict how homes will look in two decades time. Experts have got together to discuss the future of home automation and revealed their predictions for the future of home automation.
Getting around the airport can be tough. There are always large crowds and you are often in a hurry to get to your gate. If you are disabled or elderly, it can be even more of a challenge. One airline is turning to AI to make it easier for those with mobility issues to get around the airport. British Airways has become the first airline to trial fully autonomous, electric mobility devices in North America.
Understanding the predictions of a machine learning model can be as crucial as the model's accuracy in many application domains. However, the black-box nature of most highly-accurate (complex) models is a major hindrance to their interpretability. To address this issue, we introduce the symbolic metamodeling framework -- a general methodology for interpreting predictions by converting "black-box" models into "white-box" functions that are understandable to human subjects. A symbolic metamodel is a model of a model, i.e., a surrogate model of a trained (machine learning) model expressed through a succinct symbolic expression that comprises familiar mathematical functions and can be subjected to symbolic manipulation. We parameterize symbolic metamodels using Meijer G-functions -- a class of complex-valued contour integrals that depend on scalar parameters, and whose solutions reduce to familiar elementary, algebraic, analytic and closed-form functions for different parameter settings.