Lifeboat Foundation

The odds are now better than ever that future explorers, both robotic and human, will be able to take samples of the lunar’s hidden interior in deep impact basins like Crisium and Moscoviense. This gives planners more options on where to embed the first science colony.

Finding and sampling the Moon’s ancient interior mantle — one of the science drivers for sending robotic spacecraft and future NASA astronauts to the Moon’s South Pole Aitken basin — is just as likely achievable at similar deep impact basins scattered around the lunar surface.

At least that’s the view reached by planetary scientists who have been analyzing the most recent data from NASA’s Gravity Recovery And Interior Laboratory (GRAIL) and its Lunar Reconnaissance Orbiter (LRO) missions as well as from Japan’s SELENE (Kaguya) lunar orbiter.

Continue reading “NASA Now Has New Options For Sampling Moon’s Ancient Interior” »

I do love Nvidia!

During the past nine months, an Nvidia engineering team built a self-driving car with one camera, one Drive-PX embedded computer and only 72 hours of training data. Nvidia published an academic preprint of the results of the DAVE2 project entitled End to End Learning for Self-Driving Cars on arXiv.org hosted by the Cornell Research Library.

The Nvidia project called DAVE2 is named after a 10-year-old Defense Advanced Research Projects Agency (DARPA) project known as DARPA Autonomous Vehicle (DAVE). Although neural networks and autonomous vehicles seem like a just-invented-now technology, researchers such as Google’s Geoffrey Hinton, Facebook’s Yann Lecune and the University of Montreal’s Yoshua Bengio have collaboratively researched this branch of artificial intelligence for more than two decades. And the DARPA DAVE project application of neural network-based autonomous vehicles was preceded by the ALVINN project developed at Carnegie Mellon in 1989. What has changed is GPUs have made building on their research economically feasible.

Continue reading “Nvidia GPU-powered autonomous car teaches itself to see and steer” »

Closing the instability gap.

(Phys.org)—It might be said that the most difficult part of building a quantum computer is not figuring out how to make it compute, but rather finding a way to deal with all of the errors that it inevitably makes. Errors arise because of the constant interaction between the qubits and their environment, which can result in photon loss, which in turn causes the qubits to randomly flip to an incorrect state.

In order to flip the qubits back to their correct states, physicists have been developing an assortment of quantum error correction techniques. Most of them work by repeatedly making measurements on the system to detect errors and then correct the errors before they can proliferate. These approaches typically have a very large overhead, where a large portion of the computing power goes to correcting errors.

Continue reading “Autonomous quantum error correction method greatly increases qubit coherence times” »

A beautiful story about Ray Kurzweil and Bill Joy meeting and discussing Singularity many years ago.

There may be such a thing as a social fabric, or just a tapestry of individual interactions. Either way, we should worry about biotech-super-charged transhumanism, which is on a tear.

Excellent read and a true point about the need for some additional data laws with our ever exploding information overload world.

Laws for Mobility, IoT, Artificial Intelligence and Intelligent Process Automation

If you are the VP of Sales, it is quite likely you want and need to know up to date sales numbers, pipeline status and forecasts. If you are meeting with a prospect to close a deal, it is quite likely that having up to date business intelligence and CRM information would be useful. Likewise traveling to a remote job site to check on the progress of an engineering project is also an obvious trigger that you will need the latest project information. Developing solutions integrated with mobile applications that can anticipate your needs based upon your Code Halo data, the information that surrounds people, organizations, projects, activities and devices, and acting upon it automatically is where a large amount of productivity gains will be found in the future.

Continue reading “Laws for Mobility, IoT, Artificial Intelligence” »

Luv this.

He too wears a golden robe and sings chants.

Continue reading “Robot monk helps spread Buddhism in China” »

Hmmm;

The latest figures are a clear sign that India’s largest outsourcing firms are succeeding at ‘non-linear’ growth, where revenues increase disproportionately compared with hiring.

Continue reading “Automation raises Indian IT industry’s productivity; firms like Infosys, TCS likely to see lower hiring” »

https://youtube.com/watch?v=NiwbMTI38oM

China’s love of robots.

The Ying Ao sink foundry in southern China’s Guangdong province does not look like a factory of the future. The sign over the entrance is faded; inside, the floor is greasy with patches of mud, and a thick metal dust — the by-product of the stainless-steel polishing process — clogs the air. As workers haul trolleys across the factory floor, the cavernous, shed-like building reverberates with a loud clanging.

Continue reading “China’s robot revolution” »

Kurzweil, me and others have been saying devices will eventually be phased out for a while now. However, I do not believe the phase out will be due to AI. I do believe it will be based on how humans will use and adopt NextGen technology. I believe that AI will only be a supporting technology for humans and will be used in conjunction with AR, BMI, etc.

My real question around the phasing out of devices is will we jump from Smartphone directly to BMI or see a migration of Smartphone to AR Contacts & Glasses then eventually BMI?…

(Bloomberg) — Forget personal computer doldrums and waning smartphone demand. Google thinks computers will one day cease being physical devices.

Continue reading “Google CEO Pichai Sees the End of Computers as Physical Devices” »