An artificial skin that senses temperature and pressure can send signals 1000 times faster than the human nervous system. The skin could one day cover prosthetic limbs to help people use them better or be used on robots to help them sense their surroundings. Benjamin Tee at the National University of Singapore and his colleagues created the artificial skin, consisting of physical sensors that can detect pressure, bend, and temperature, placed inside a layer of plastic. All of the sensors are connected together using a single wire, meaning that the measurement from across the skin arrive at the same time."In If you have 1000 sensors, and each one takes 1 millisecond to scan, then the entire scanning operation will take 1 full second."

Tesla Powerwalls and Solar Roof, two of Elon Musk's innovative strategies to get consumers onto the solar grid, require waits of six months or longer. The company says customers are hungry, but it doesn't have the product yet. Tesla is cutting the price of the Model 3, as it aims to make its best-selling product more affordable, and is discontinuing versions of other vehicles. Tesla said on Monday that it's reducing the price of the Model 3 by $1,000 to $38,990. The company will no longer sell the standard range versions of the Model S and Model X, raising the minimum costs consumers will have to pay for those cars.

Elon Musk wants to link human brains with computers. The CEO of SpaceX and Tesla Motors is exploring just such a connection through another company he has launched, called Neuralink. Elon Musk has revealed that his stealth neurotechnology start-up is poised to begin human clinical trials soon on brain implants. Musk's Neuralink gave a presentation late Tuesday and released a white paper divulging details of its progress on implants that could eventually enable patients to overcome devastating injuries. The company, which has been pursuing the technology for years with Musk's financial backing and leadership, touted its initial results as promising for potentially treating conditions such as Alzheimer's, spinal injuries and blindness.

Some Uber drivers in New York City want to see a decrease in the commission taken by the company. SAN FRANCISCO -- Gig economy workers are increasingly ubiquitous, shuttling us to appointments and delivering our food while working for Uber, Lyft, DoorDash and others. Thanks in large part to the app-based tech boom emanating from this city, 36% of U.S. workers participate in the gig economy, according to Gallup. But not all gigs are created equal, Gallup adds, noting that so-called "contingent gig workers" experience their workplace "like regular employees do, just without the benefits of a traditional job -- benefits, pay and security." California lawmakers are weighing what is considered a pro-worker bill that, if passed into law, would set a national precedent that fundamentally redefines the relationship between worker and boss by forcing corporations to pay up.

We hear a lot about AI and its transformative potential. What that means for the future of humanity, however, is not altogether clear. Some futurists believe life will be improved, while others think it is under serious threat. Here's a range of takes from 11 experts. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia. That is the first sentence in Yudkowsy's 2002 report entitled "Artificial Intelligence as a Positive and Negative Factor in Global Risk" for the Machine Intelligence Research Institute (MIRI).

Categorical data are commonplace in many Data Science and Machine Learning problems but are usually more challenging to deal with than numerical data. In particular, many machine learning algorithms require that their input is numerical and therefore categorical features must be transformed into numerical features before we can use any of these algorithms. One of the most common ways to make this transformation is to one-hot encode the categorical features, especially when there does not exist a natural ordering between the categories (e.g. a feature'City' with names of cities such as'London', 'Lisbon', 'Berlin', etc.). For each unique value of a feature (say, 'London') one column is created (say, 'City_London') where the value is 1 if for that instance the original feature takes that value and 0 otherwise. Even though this type of encoding is used very frequently, it can be frustrating to try to implement it using scikit-learn in Python, as there isn't currently a simple transformer to apply, especially if you want to use it as a step of your machine learning pipeline.

Since its invention by a Hungarian architect in 1974, the Rubik's Cube has furrowed the brows of many who have tried to solve it, but the 3-D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine. DeepCubeA, a deep reinforcement learning algorithm programmed by UCI computer scientists and mathematicians, can find the solution in a fraction of a second, without any specific domain knowledge or in-game coaching from humans. This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state--each of six sides displaying a solid color--which apparently can't be found through random moves. For a study published today in Nature Machine Intelligence, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the shortest path to the goal state about 60 percent of the time. The algorithm also works on other combinatorial games such as the sliding tile puzzle, Lights Out and Sokoban.

CHICAGO -- Grant Thornton LLP is collaborating with Microsoft and Hitachi Solutions to turn information into foresight. The collaboration uses artificial intelligence (AI) and machine learning (ML) to help Grant Thornton identify its clients' nascent business needs. Grant Thornton can then design solutions to address its clients' challenges before they balloon. As one of the nation's largest accounting, tax and consulting firms, Grant Thornton works with clients to overcome all manner of hurdles, from financial and operational to technological and risk-related. "We focus on staying ahead of our clients' needs," explains Nichole Jordan, Grant Thornton's national managing partner of Markets, Clients and Industry.

The human record for solving a Rubik's Cube has been smashed by an artificial intelligence. The bot, called DeepCubeA, completed the popular puzzle in a fraction of a second - much faster than the quickest humans. While algorithms have previously been developed specifically to solve the Rubik's Cube, this is the first time it has done without any specific domain knowledge or in-game coaching from humans. It brings researchers a step closer to creating an advanced AI system that can think like a human. "The solution to the Rubik's Cube involves more symbolic, mathematical and abstract thinking," said senior author Professor Pierre Baldi, a computer scientist at the University of California, Irvine.

No longer does artificial intelligence only exist in sci-fi movies and books about dystopian futures. It's in the here and now, continuously transforming the way in which we live and work. Many of us interact with AI on a daily basis - we call on Siri to give us directions to nearby coffee shops or ask Alexa to order us goods on Amazon. AI is also seamlessly supplementing and enhancing operations across a variety of industries and increasingly disrupting internal company functions. However, at the same time, it's also becoming more and more apparent where AI still has limitations that prevent it from fully replicating human behavior.