Cazza’s 3D printing robots has introduced a new way of construction, which is more eco-friendly and cost-effective than traditional methods.
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Category: robotics/AI – Page 2214
YOKOSUKA, Japan (AP) — A Japanese industrial group unveiled Thursday a robot designed for underwater probes of damage from meltdowns at the Fukushima Dai-Ichi nuclear plant after the March 2011 earthquake and tsunami.
Remote controlled robots are key to the decades-long decommissioning process for the plant. But super-high radiation and structural damage inside the reactors hampered earlier attempts to inspect areas close to the reactors’ cores.
The developers say they plan to send the new “mini manbo,” or “little sunfish,” probe into the primary containment vessel of Unit 3 at Fukushima in July to study the extent of damage and locate parts of melted fuel thought to have fallen to the bottom of the chamber, submerged by highly radioactive water.
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Drones. Drone is a word you see pretty often in today’s pop culture. But drones seem to be an extremely diverse species. Even flightless vehicles are occasionally referred to as drones. So what exactly is a drone?
In this video series, the Galactic Public Archives takes bite-sized looks at a variety of terms, technologies, and ideas that are likely to be prominent in the future. Terms are regularly changing and being redefined with the passing of time. With constant breakthroughs and the development of new technology and other resources, we seek to define what these things are and how they will impact our future.
Juergen Schmidhuber is the father of Deep learning Artificial Intelligence.
Since age 15 or so, the main goal of professor Jürgen Schmidhuber has been to build a self-improving Artificial Intelligence (AI) smarter than himself, then retire. His lab’s Deep Learning Neural Networks (NNs) (since 1991) and Long Short-Term Memory have transformed machine learning and AI, Deep Learning since 1991 – Winning Contests in Pattern Recognition and Sequence Learning Through Fast and Deep / Recurrent Neural Networks and are now (2017) available to billions of users through the world’s most valuable public companies including Google, Apple, Microsoft, Amazon, etc. In 2011, his team was the first to win official computer vision contests through deep NNs, with superhuman performance. His research group also established the field of mathematically rigorous universal AI and recursive self-improvement in universal problem solvers that learn to learn (since 1987).
He predicts trillions of AI in the 2050s will mine and develop the asteroids.
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Very interesting new feature in Aeon on AI that also discusses my short fiction The Jesus Singularity: https://aeon.co/essays/why-is-the-language-of-transhumanists…so-similar #transhumanism
The most avid believers in artificial intelligence are aggressively secular – yet their language is eerily religious. Why?
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“Deep Learning” computer systems, based on artificial neural networks that mimic the way the brain learns from an accumulation of examples, have become a hot topic in computer science. In addition to enabling technologies such as face- and voice-recognition software, these systems could scour vast amounts of medical data to find patterns that could be useful diagnostically, or scan chemical formulas for possible new pharmaceuticals.
But the computations these systems must carry out are highly complex and demanding, even for the most powerful computers.
Now, a team of researchers at MIT and elsewhere has developed a new approach to such computations, using light instead of electricity, which they say could vastly improve the speed and efficiency of certain deep learning computations. Their results appear today in the journal Nature Photonics (“Deep learning with coherent nanophotonic circuits”) in a paper by MIT postdoc Yichen Shen, graduate student Nicholas Harris, professors Marin Soljacic and Dirk Englund, and eight others.
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Now you have until 6/30 to submit a proposal to the Agency’s Lifelong Learning Machines (L2M) program.
Here’s the vision: Muster all the creativity that you can with the goal of developing fundamentally new machine learning approaches that enable systems to learn continually as they operate and apply previous knowledge to novel situations. Current AI systems only compute with what they have been programmed or trained for in advance; they have no ability to learn from data input during execution time and cannot adapt online to changes they encounter in real environments. The goal of L2M is to develop substantially more capable systems that are continually improving and updating from experience.
Consult the Broad Agency Announcement for more information: https://www.fbo.gov/…/…/DARPA/CMO/HR001117S0016/listing.html
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I’ll be on a panel and also doing an author’s roundtable (The Transhumanist Wager) at FreedomFest in Las Vegas on July 21. It’s one of the largest gatherings of free minds in the world and this year is the 10th anniversary. If you’re there, please say hello! Others are speaking on life extension and AI. Here’s my speaker’s page:
Check out what Zoltan Istvan will be attending at FreedomFest 2017.
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