NASA has recently announced it would give funds to a California-based 3D printing company for finding ways to turn asteroids into giant, autonomous spacecrafts, which could fly to outposts in space, the media reported.
Made In Space’s project, known as RAMA (Reconstituting Asteroids into Mechanical Automata), could one day enable space colonization by helping make off-Earth manufacturing efficient and economically viable, Space.com reported.
The company plans to use 3D printing to turn the asteroids into self-flying vehicles by 2030.
About the future death of explainability to understand AI thinking, the writing is on the wall…
These divergent approaches, one regulatory, the other deregulatory, follow the same pattern as antitrust enforcement, which faded in Washington and began flourishing in Brussels during the George W. Bush administration. But there is a convincing case that when it comes to overseeing the use and abuse of algorithms, neither the European nor the American approach has much to offer. Automated decision-making has revolutionized many sectors of the economy and it brings real gains to society. It also threatens privacy, autonomy, democratic practice, and ideals of social equality in ways we are only beginning to appreciate.
At the simplest level, an algorithm is a sequence of steps for solving a problem. The instructions for using a coffeemaker are an algorithm for converting inputs (grounds, filter, water) into an output (coffee). When people say they’re worried about the power of algorithms, however, they’re talking about the application of sophisticated, often opaque, software programs to enormous data sets. These programs employ advanced statistical methods and machine-learning techniques to pick out patterns and correlations, which they use to make predictions. The most advanced among them, including a subclass of machine-learning algorithms called “deep neural networks,” can infer complex, nonlinear relationships that they weren’t specifically programmed to find.
Predictive algorithms are increasingly central to our lives. They determine everything from what ads we see on the Internet, to whether we are flagged for increased security screening at the airport, to our medical diagnoses and credit scores. They lie behind two of the most powerful products of the digital information age: Google Search and Facebook’s Newsfeed. In many respects, machine-learning algorithms are a boon to humanity; they can map epidemics, reduce energy consumption, perform speech recognition, and predict what shows you might like on Netflix. In other respects, they are troubling. Facebook uses AI algorithms to discern the mental and emotional states of its users. While Mark Zuckerberg emphasizes the application of this technique to suicide prevention, opportunities for optimizing advertising may provide the stronger commercial incentive.
We’ve had autonomous cars, autonomous trucks, and autonomous buses, and now Osaka-based diesel engine manufacturer Yanmar is introducing a new line of robotic tractors. On October 1, 2018, the company is releasing its 2-series tractors equipped with the Smartpilot autonomous operating system and Information and Communications Technology (ICT) that allow them to operate in autonomous and semi-autonomous modes.
Interesting article on the limited future of human paid employment for AI, some thoughts.
By Paul R. Daugherty and H. James Wilson
Superman versus Batman. Captain America versus Iron Man. Zuckerberg versus Musk?
The reported clash between the two technology titans is proof that not everyone sees the benefits and dangers of artificial intelligence in the same light. Yet from Facebook’s algorithms to Tesla’s self-driving cars, it’s clear that AI isn’t science fiction any longer—and that we’re already at the cusp of a new era, with AI poised to deliver transformational change in business and society.
The latest robots out of MIT are small enough to float “indefinitely” in the air. Researchers accomplished the feat by attaching 2D electronics to colloids — tiny particles measuring around one-billionth to one-millionth of a meter. All told, the devices are roughly the size of a human egg cell.
What’s more, the addition of photodiode semiconductors means the tiny individual systems are able to be self-powered, without the need for a battery. The system converts light into a small electrical charge that’s enough to keep the device’s on-board environmental sensors running, while storing on-board information.
Posted in robotics/AI
Earlier this month, DARPA announced it is launching a new SHort-Range Independent Microrobotic Platforms (SHRIMP) program. SHRIMP will develop and demonstrate micro-to-milli robotic platforms for scenarios brought on by natural and critical disasters.
As IEEE Spectrum put it, it’s a program to develop “insect-scale robots” for disaster recovery and high-risk environments. The topic is simple enough to understand and it also is obvious that the means of accomplishing these platforms is tough.
DARPA, said its announcement, will be facing the challenge of “creating extremely SWaP-constrained microrobotics.” SWaP refers to size, weight and power.
