Are you ready?
For now, the world’s top gamers can still beat the most sophisticated bots — but the tide may turn in as little as three years, according to a former StarCraft II champion.
Category: robotics/AI – Page 1,788
The future of entertainment: songs that never end, movies with unlimited sequels, TV shows with never ending episodes, and video games that go on forever.
And how the tech works is largely a mystery.
Whoever wins will lead the world, Eric Klien.
The reality is that US and China efforts to develop AI are entwined, even if the tensions of coronavirus and trade disagreements may spur a separation.
Innovation.
The U.S. Air Force plans to have an operational combat drone by 2023. The service plans to build out a family of unmanned aircraft, known as Skyborg, capable of carrying weapons and actively participating in combat. The Air Force’s goal is to build up a large fleet of armed, sort-of disposable jets that don’t need conventional runways to take off and land.
The Air Force, according to Aviation Week & Space Technology, expects to have the first operational Skyborg aircraft ready by 2023. Skyborg will be available with both subsonic and supersonic engines, indicating both attack and fighter jet versions. The basic design (or designs) will likely be stealthy, carrying guided bombs, air defense suppression missiles, and air-to-air missiles inside internal weapons bays. Interesting, according to AvWeek, the Air Force is considering Skyborg as a replacement not only for the MQ-9 Reaper attack drone but early versions of the F-16 manned fighter.
Neurons, specialized cells that transmit nerve impulses, have long been known to be a vital element for the functioning of the human brain. Over the past century, however, neuroscience research has given rise to the false belief that neurons are the only cells that can process and learn information. This misconception or ‘neurocomputing dogma’ is far from true.
An astrocyte is a different type of brain cell that has recently been found to do a lot more than merely fill up spaces between neurons, as researchers believed for over a century. Studies are finding that these cells also play key roles in brain functions, including learning and central pattern generation (CPG), which is the basis for critical rhythmic behaviors such as breathing and walking.
Although astrocytes are now known to underlie numerous brain functions, most existing computer systems inspired by the human brain only target the structure and function of neurons. Aware of this gap in existing literature, researchers at Rutgers University are developing brain-inspired algorithms that also account for and replicate the functions of astrocytes. In a paper pre-published on arXiv and set to be presented at the ICONS 2020 Conference in July, they introduce a neuromorphic central pattern generator (CPG) modulated by artificial astrocytes that successfully entrained several rhythmic walking behaviors in their in-house robots.
The robot seen here can work almost 24–7, carrying out experiments by itself. The automated scientist – the first of its kind – can make its own decisions about which chemistry experiments to perform next, and has already discovered a new catalyst.
With humanoid dimensions, and working in a standard laboratory, it uses instruments much like a human does. Unlike a real person, however, this 400 kg robot has infinite patience, and works for 21.5 hours each day, pausing only to recharge its battery.
This new technology – reported in the journal Nature and featured on the front cover – is designed to tackle problems of a scale and complexity that are currently beyond our grasp. New drug formulations could be autonomously discovered, for example, by searching vast and unexplored chemical spaces.
The Pentagon’s Joint AI Center is working on lethal “tactical edge AI,” but is not working on facial recognition, said JAIC director Nand Mulchandani.
Big data company Openairlines claims to be helping make flying more eco-friendly through in-depth data analysis, but it may be saving more money than fuel.
Dimensionality reduction is an unsupervised learning technique.
Nevertheless, it can be used as a data transform pre-processing step for machine learning algorithms on classification and regression predictive modeling datasets with supervised learning algorithms.
There are many dimensionality reduction algorithms to choose from and no single best algorithm for all cases. Instead, it is a good idea to explore a range of dimensionality reduction algorithms and different configurations for each algorithm.
Soon will be 100 percent efficient.
Researchers from the University of Liverpool have built what they call an intelligent mobile robot scientist that’s able to work continuously nearly 24 hours a day and carry out experiments o…