Robots in the work place can perform hazardous or even 'impossible' tasks; e.g., toxic waste clean-up, desert and space exploration, and more. AI researchers are also interested in the intelligent processing involved in moving about and manipulating objects in the real world.
The image recognition technology that underlies today's autonomous cars and aerial drones depends on artificial intelligence: the computers essentially teach themselves to recognize objects like a dog, a pedestrian crossing the street or a stopped car. The problem is that the computers running the artificial intelligence algorithms are currently too large and slow for future applications like handheld medical devices. A Stanford-designed hybrid optical-electrical computer designed specifically for image analysis could be ideal for autonomous vehicles. Now, researchers at Stanford University have devised a new type of artificially intelligent camera system that can classify images faster and more energy efficiently, and that could one day be built small enough to be embedded in the devices themselves, something that is not possible today. The work was published in the August 17 Nature Scientific Reports.
Byron Reese believes technology has only truly reshaped humanity three times in history. The first came with the harnessing of fire. And the "third age" came with the invention of the wheel and writing. Reese, CEO and publisher of the technology research company, Gigaom, and host of the Voices in AI podcast, has spent the majority of his career exploring how technology and humanity intersect. He believes the emergence of artificial intelligence is pushing us into a "fourth age" in which AI and robotics will forever transform not only how we work and play, but also how we think about deeper philosophical topics, such as the nature of consciousness.
If buying a Raspberry Pi or one of the many other single-board computers available isn't a tough enough challenge, hacker Marcel Thürmer has sketched out enough details about his Blueberry Pi open-source hardware project to help the like-minded take things to the next level. As Thürmer wryly notes on the GitHub page where he's left the Blueberry Pi's schematics, this is just "another fruit single-board computer" based on the Allwinner V3s system on chip (SoC). However, while some single-board computer makers have open-sourced their hardware designs, unless you're building a large enough quantity, it's probably not worth the cost or effort. The key difference with the Blueberry Pi, according to hacker site Hackaday is that Thürmer has made it cheap and simple enough to build without needing your own pick-and-place robot. That particular SoC, intended for cameras, is useful because it comes with an easy-to-solder TQFP or'thin quad flat-pack' package, which allowed him to choose a two-layer printed circuit board (PCB) and is cheaper than, say, an eight-layer PCB.
An Amazon office building at 27 Melcher St. in Boston, which houses some of the 1,200 Amazon corporate staff who work in the greater Boston area. The newly refurbished building was formerly a Necco wafer candy factory. Amazon has 17 tech hubs in North America outside Seattle that employ more than 17,500 corporate, as opposed to warehouse and fulfillment, staff. That number is anticipated to rise to 26,200 by 2023. Here's where they are -- and why.
When it comes to the breakthroughs that brilliant scientists and engineers are working on in 2018, artificial intelligence technology somehow manages to be both the most promising and most polarizing development of these times. As a collective, Big Tech is throwing billions of dollars at artificial intelligence, which those involved would rather we all call machine learning. The notion that we can teach computers to learn -- to absorb data, recognize patterns, and take action -- could have an enormous impact on nearly everything we do with a computer, and pave the way for computers to move into new and game-changing places, such as the self-driving car. This technology still has a long way to go, despite the fact we've been talking about it for decades. But it's starting to become real, and alongside that progress has come perhaps one of the biggest backlashes against an aspect of the evolution of information technology.
Tesla's Model S sedan, the car company's flagship vehicle, was first shown as a prototype in 2009, has been on sale since 2012, and, barring one small change to remove the fake grille at the front, has looked exactly the same for nearly a decade. This is notable because most manufacturers fully redesign their cars every four to six years to keep them fresh--and to keep buyers buying. For Tesla, tech upgrades are the selling point. The company pushes software updates several times a year, adding features like summon, where a car pulls in and out of a garage with nobody inside, or camper-mode, for sleeping in the car with the heating on. Tesla's biggest claim is that one day, all the cars it's currently building will be capable of full-self driving.
The race for dominance in artificial intelligence will be to the 2020s what the space race was to the 1960s, and the competition is gaining on us fast. A dozen nations around the world, ranging from our closest ally, Canada, to our fiercest competitor, China, are pouring billions of dollars into AI research and development. Machines capable of making complex decisions independent from human input will bring economic change on the scale of the industrial revolution. Facebook already uses artificial intelligence to identify your face in newly uploaded photos. Computers can find tumors in medical images with greater accuracy than doctors.
BEIRUT: The rise of Artificial Intelligence has grown and developed globally, owing to various advances in many fields. Although many people are still finding it hard to understand the virtual intelligence, others are taking in the challenge and bringing together ways to connect computers and humans, producing new AI material that somehow benefits many. With the inspiration of corralling several key ideas, Nicolas Zaatar and Charlie El Khoury have developed their own startup NAR – Next Automated Robot – whose mission was to transform drones from flying cameras to flying computers. "We thought, what if we use the drone as an inspector gadget?" The ideas they have combined are information, data, algorithm, uncertainty, computing, and finally, optimizing.
The unique topic of artificial intelligence (AI) for humanitarian assistance and disaster relief (HA/DR) was in the spotlight last week, as leading minds from academia, industry and the federal government met to discuss how modern technology can help victims of disasters around the globe. "The problem of catastrophes affecting humanity will unfortunately always be among us," said Chief of Naval Research Rear Adm. David J. Hahn. "The great minds in this room are here to figure out how we can best leverage artificial intelligence and autonomy to better deliver resources and people to those in urgent need." As Hahn addressed the group, pictures of naval relief efforts over many years scrolled behind him, including Sailors and Marines assisting victims in Haiti after an earthquake, Japan after an earthquake and tsunami, New Orleans and New York after hurricanes, and more. Hahn noted the Navy and Marine Corps are uniquely suited to support rescue and relief work done by different federal agencies, when called upon.
The world of an 80s teenager was one of arcade machines, LPs and Nintendo game consoles. And now you can step back in time and enter that world thanks to a computer museum that has recreated it using a series of fascinating exhibitions. They include an 80s classroom with'state-of-the-art' Apple IIe computers, a'friend's basement' that contains wood-panelled walls and a classic Nintendo Entertainment System (NES) console, and a videogame arcade. A typical basement from the 1980s has been recreated at the Living Computers: Museum Labs in Seattle. There is also a 1980s classroom packed with Apple IIe computers.