Lifeboat Foundation

The market is definitely there. But, it needs to be able to do a minimum amount of practical things, in about this order: 1. it needs to be able to cook even the most basic of meals, being unable to cook for themselves is usually the main reason someone has to go into a nursing home; 2. being able to clean your average kitchen and bathroom; 3. being able to do basic yard tasks, operating a lawnmower and a snowblower. Those would be the most important, after those get mastered have it equipped to do more niche tasks and entertainment features.

As to when, we have clumsy humanoid robots right now, and AI will supposedly reach human level around 2029. It will just be a task of merging those two between now and then, and getting that robot down to a reasonable cost, which i think would be in the neighborhood of a brand new SUV.

As artificial intelligence advances, we humans will form relationships with our robot helpers and caregivers.

Continue reading “Your future companion in your old age could be a robot” »

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A knock off of Boston Dynamics dog robot, but interesting to see. I’d be curious how loud it is, you know it’s usually pretty loud when there’s no audio.

#AI The Machine Learning 4 SETI Code Challenge (ML4SETI), created by the SETI Institute and IBM, was completed on July 31st 2017. Nearly 75 participants, with a wide range of backgrounds from industry and academia, worked in teams on the project. The top team achieved a signal classification accuracy of 95%. The code challenge was sponsored by IBM, Nimbix Cloud, Skymind, Galvanize, and The SETI League.

The Machine Learning 4 SETI Code Challenge (ML4SETI), created by the SETI Institute and IBM, was completed on July 31st 2017. Nearly 75 participants, with a wide range of backgrounds from industry and academia, worked in teams on the project. The top team achieved a signal classification accuracy of 95%. The code challenge was sponsored by IBM, Nimbix Cloud, Skymind, Galvanize, and The SETI League.

The ML4SETI project challenged participants to build a machine-learning model to classify different signal types observed in radio-telescope data for the search for extra-terrestrial intelligence (SETI). Seven classes of signals were simulated (and thus, labeled), with which citizen scientists trained their models. We then measured the performance of these models with tests sets in order to determine a winner of the code challenge. The results were remarkably accurate signal classification models. The models from the top teams, using deep learning techniques, attained nearly 95% accuracy in signals from the test set, which included some signals with very low amplitudes. These models may soon be used in daily SETI radio signal research.

Continue reading “Using Artificial Intelligence to Search for Extraterrestrial Intelligence” »

White-collar automation has become a common buzzword in debates about the growing power of computers, as software shows potential to take over some work of accountants and lawyers. Artificial-intelligence researchers at Google are trying to automate the tasks of highly paid workers more likely to wear a hoodie than a coat and tie—themselves.

In a project called AutoML, Google’s researchers have taught machine-learning software to build machine-learning software. In some instances, what it comes up with is more powerful and efficient than the best systems the researchers themselves can design. Google says the system recently scored a record 82 percent at categorizing images by their content. On the harder task of marking the location of multiple objects in an image, an important task for augmented reality and autonomous robots, the auto-generated system scored 43 percent. The best human-built system scored 39 percent.

Such results are significant because the expertise needed to build cutting-edge AI systems is in scarce—even at Google. “Today these are handcrafted by machine learning scientists and literally only a few thousands of scientists around the world can do this,” said Google CEO Sundar Pichai last week, briefly namechecking AutoML at a launch event for new smartphones and other gadgets. “We want to enable hundreds of thousands of developers to be able to do it.”

Continue reading “Google’s AutoML Project Teaches AI To Write Learning Software” »

While some automakers look to electrify conventional trucks, General Motors has taken a much more radical approach in its development of next-generation commercial vehicles.

Meet the Silent Utility Rover Universal Superstructure, or SURUS for short.

Unveiled on Friday ahead of the fall meeting of the Association of the United States Army, where it will be presented on Monday, the SURUS is essentially a modular platform designed for heavy-duty trucks that will enable near-silent running, zero harmful emissions, and autonomous operation.

Continue reading “SURUS: GM’s modular platform for silent, self-driving trucks” »

[*This article was first published in the September 2017 issue of Paradigm Explorer: The Journal of the Scientific and Medical Network (Established 1973). The article was drawn from the author’s original work in her book: The Future: A Very Short Introduction (Oxford University Press, 2017), especially from Chapters 4 & 5.]

We are at a critical point today in research into human futures. Two divergent streams show up in the human futures conversations. Which direction we choose will also decide the fate of earth futures in the sense of Earth’s dual role as home for humans, and habitat for life. I choose to deliberately oversimplify here to make a vital point.

The two approaches I discuss here are informed by Oliver Markley and Willis Harman’s two contrasting future images of human development: ‘evolutionary transformational’ and ‘technological extrapolationist’ in Changing Images of Man (Markley & Harman, 1982). This has historical precedents in two types of utopian human futures distinguished by Fred Polak in The Image of the Future (Polak, 1973) and C. P. Snow’s ‘Two Cultures’ (the humanities and the sciences) (Snow, 1959).

What I call ‘human-centred futures’ is humanitarian, philosophical, and ecological. It is based on a view of humans as kind, fair, consciously evolving, peaceful agents of change with a responsibility to maintain the ecological balance between humans, Earth, and cosmos. This is an active path of conscious evolution involving ongoing psychological, socio-cultural, aesthetic, and spiritual development, and a commitment to the betterment of earthly conditions for all humanity through education, cultural diversity, greater economic and resource parity, and respect for future generations.

Continue reading “Contrasting Human Futures: Technotopian or Human-Centred?*” »

AI is only loosely modeled on the brain. So what if you wanted to do it right? You’d need to do what has been impossible until now: map what actually happens in neurons and nerve fibers.

Dubai’s police department has added a flying motorcycle to its arsenal. Capable of flying with or without a pilot, the bike will be used to help rescue missions and monitor traffic. Due to safety concerns, the bike won’t fly higher than 20 feet. Dubai officials plan to start using the vehicle within the next two years.

The flying motorcycle is just the latest piece of absurd technology the Dubai government has introduced in the last year. The bike will join the ranks of Dubai’s jetpack firefighters, flying taxis, and robot police officers.

Dubai’s push for new government technology is part of their plan improve services ahead of their world fair, Expo 2020, which is expected to attract 25 million visitors to the city.

Continue reading “Dubai police add hoverbikes to go with their robocops and flying taxis” »

In a big step on the journey to our robot-laden future, California is moving to permit companies that are developing self-driving cars to test them in the state with no human safety driver at the wheel.

The state that’s home to the biggest concentration of autonomous vehicles is poised to take a big step to help advance the technology — and fend off efforts by other states to attract test programs.