Lifeboat Foundation

Quantum biomimetics consists of reproducing in quantum systems certain properties exclusive to living organisms. Researchers at University of the Basque Country have imitated natural selection, learning and memory in a new study. The mechanisms developed could give quantum computation a boost and facilitate the learning process in machines.

Unai Alvarez-Rodriguez is a researcher in the Quantum Technologies for Information Science (QUTIS) research group attached to the UPV/EHU’s Department of Physical Chemistry, and an expert in quantum information technologies. Quantum information technology uses quantum phenomena to encode computational tasks. Unlike classical computation, quantum computation “has the advantage of not being limited to producing registers in values of zero and one,” he said. Qubits, the equivalent of bits in classical computation, can take values of zero, one or both at the same time, a phenomenon known as superposition, which “gives quantum systems the possibility of performing much more complex operations, establishing a computational parallel on a quantum level, and offering better results than classical computation systems,” he added.

The research group to which Alvarez-Rodriguez belongs decided to focus on imitating biological processes. “We thought it would be interesting to create systems capable of emulating certain properties exclusive of living entities. In other words, we were seeking to design quantum information protocols whose dynamics were analogous to these properties.” The processes they chose to imitate by means of quantum simulators were natural selection, memory and intelligence. This led them to develop the concept of quantum biomimetics.

When Jan Scheuermann volunteered for an experimental brain implant, she had no idea she was making neuroscience history.

Scheuermann, 54 at the time of surgery, had been paralyzed for 14 years due to a neurological disease that severed the neural connections between her brain and muscles. She could still feel her body, but couldn’t move her limbs.

Unwilling to give up, Scheuermann had two button-sized electrical implants inserted into her motor cortex. The implants tethered her brain to a robotic arm through two bunches of cables that protruded out from her skull.

Continue reading “New Tech Makes Brain Implants Safer and Super Precise” »

Almost two months to the day after Uber loaded its fleet of self-driving SUVs into the trailer of a self-driving truck and stormed off to Arizona in a self-driving huff, the company is preparing to launch its second experiment (if you don’t count the aborted San Francisco pilot) in autonomous ride-hailing.

What’s different is that this time, Uber has the blessing from Arizona’s top politician, Governor Doug Ducey, a Republican, who is expected to be “Rider Zero” on an autonomous trip along with Anthony Levandowski, VP of Uber’s Advanced Technologies Group. The Arizona pilot comes after California’s Department of Motor Vehicles revoked the registration of Uber’s 16 self-driving cars because the company refused to apply for the appropriate permits for testing autonomous cars.

What’s the ground truth on artificial intelligence (AI)? In this video, John Launchbury, the Director of DARPA’s Information Innovation Office (I2O), attempts to demystify AI–what it can do, what it can’t do, and where it is headed. Through a discussion of the “three waves of AI” and the capabilities required for AI to reach its full potential, John provides analytical context to help understand the roles AI already has played, does play now, and could play in the future.

Download the slides at: http://www.darpa.mil/about-us/darpa-perspective-on-ai

Going straight to Level 5 may hurt Ford in the short-term, as competitors will be able to offer some self-driving functionality to customers that want it. However, the decision let’s Ford power on ahead with its driverless dream, which it aims to have on the road by 2021.

Ford plans to skip ‘Level 3’ autonomy and shoot right for Level 5, the highest level of car automation. The automaker decided to skip the midway point after it noticed a few of its engineers dozing while testing semi-autonomous vehicles.

Even with “bells, buzzers, warning lights, vibrating seats and steering wheels, and another engineer in the passenger seat” the engineers struggled to maintain situational awareness, according to Raj Nair, Ford’s chief product development officer.

Continue reading “Ford To Skip Level 3 Autonomy To Keep Sleepy Drivers Happy” »

I believe that this is a stretch for me. However, wouldn’t be nice if we could. Imagine Steve Jobs could still run Apple, we could hear Einstein and Bhor debate, etc. Again cool concept but at this stage hard to believe it will be real until we learn more about Quantum Biosystem in the mix; and even then unlikely. Nonetheless, good luck with it MIT.

Imagine debating the interpretation of a Shakespearean sonnet and being able to clarify its meaning with the bard himself. Or sitting in history class and being able to ask George Washington questions about the Constitution, no soul-conjuring witchcraft required.

In the next decade, advancing AI technology will allow us to learn from the dead first-hand. New chatbot programs are being developed to keep our knowledge active after our physical being passes away.

Continue reading “Want to chat with Shakespeare? AI bots will soon allow us to talk to the dead” »

Sharing in case folks would like to listen in.

Microsoft’s Station Q was founded in 2006. The focus of the team has always been topological quantum computing. By taking a full systems architecture approach, we have reached the point where we now able to start engineering a scalable quantum computer. The goal is to be able to solve major problems in areas of interest (e.g., Chemistry, Materials and Machine Learning). This talk will focus on the types of applications that we will be trying to solve as well as the unique approach to quantum computation that we’ve developed. For reference, see:

Current Approach: https://arxiv.org/abs/1610.05289 Chemistry Application: https://arxiv.org/abs/1605.03590 Other papers: https://arxiv.org/find/all/1/all:+wecker_d/0/1/0/all/0/1

In the past, traditional methods to understand the behavior of quantum interacting systems have worked well, but there are still many unsolved problems. To solve them, Giuseppe Carleo of ETH Zurich, Switzerland, used machine learning to form a variational approach to the quantum many-body problem.

Before digging deeper, let me tell you a little about the many-body problem. It deals with the difficulty of analyzing “multiple nontrivial relationships encoded in the exponential complexity of the many-body wave function.” In simpler language, it’s the study of interactions between many quantum particles.

If we take a look at our current computing power, modeling a wave function will need lot more powerful supercomputers. But, according to Carleo, the neural networks are pretty good at generalizing. Hence, they need only limited information to infer something. So, fiddling with this idea, Carleo and Matthias Troyer created a simple neural network to reconstruct such multi-body wave function.

UPS has successfully tested a drone that launches from the top of a UPS truck and autonomously delivers packages. http://abcn.ws/2lsyjjM