Lifeboat Foundation

GPS is an utterly pervasive and wonderful technology, but it’s increasingly not accurate enough for modern demands. Now a team of researchers can make it accurate right down to an inch.

Regular GPS registers your location and velocity by measuring the time it takes to receive signals from four or more satellites, that were sent into space by the military. Alone, it can tell you where you are to within 30 feet. More recently a technique called Differential GPS (DGPS) improved on that resolution by adding ground-based reference stations—increasing accuracy to within 3 feet.

Now, a team from the University of California, Riverside, has developed a technique that augments the regular GPS data with on-board inertial measurements from a sensor. Actually, that’s been tried before, but in the past it’s required large computers to combine the two data streams, rendering it ineffective for use in cars or mobile devices. Instead what the University of California team has done is create a set of new algorithms which, it claims, reduce the complexity of the calculation by several order of magnitude.

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What you’re looking at is the first direct observation of an atom’s electron orbital — an atom’s actual wave function! To capture the image, researchers utilized a new quantum microscope — an incredible new device that literally allows scientists to gaze into the quantum realm.

An orbital structure is the space in an atom that’s occupied by an electron. But when describing these super-microscopic properties of matter, scientists have had to rely on wave functions — a mathematical way of describing the fuzzy quantum states of particles, namely how they behave in both space and time. Typically, quantum physicists use formulas like the Schrödinger equation to describe these states, often coming up with complex numbers and fancy graphs.

Up until this point, scientists have never been able to actually observe the wave function. Trying to catch a glimpse of an atom’s exact position or the momentum of its lone electron has been like trying to catch a swarm of flies with one hand; direct observations have this nasty way of disrupting quantum coherence. What’s been required to capture a full quantum state is a tool that can statistically average many measurements over time.

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Here is a concept to think about when we’re 20 or 30 years into the future — imagine a world where humans and all living things in it are truly Singular, and the new AI & Humanoid robots are alive and well. Will AI (including Robots) ever need therapy, will AI ever get stressed out or have panic attacks, will any humans know what AI is thinking once we give AI more independence?

I ask these questions because as we enhance and evolve AI to be like humans and interpret and process emotions, feelings, and interact like humans; will AI expeience fully the struggles of everyday life like some humans do? And, when needs counseling or therapy will they go to another AI or will they see a human therapist?

As we evolve AI; we must look at the full longer picture around AI including how human do we really wish to make AI.

Continue reading “What does artificial intelligence see when it watches political ads?” »

What if computers could recognize objects as well as the human brain could? Electrical engineers at the University of California, San Diego have taken an important step toward that goal by developing a pedestrian detection system that performs in near real-time (2−4 frames per second) and with higher accuracy (close to half the error) compared to existing systems. The technology, which incorporates deep learning models, could be used in “smart” vehicles, robotics and image and video search systems.

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Around the world, cities are choking on smog. But a new AI system plans to analyze just how bad the situation is by aggregating data from smartphone pictures captured far and wide across cities.

The project, called AirTick, has been developed by researchers from Nanyang Technological University in Singapore, reports New Scientist. The reasoning is pretty simple: Deploying air sensors isn’t cheap and takes a long time, so why not make use of the sensors that everyone has in their pocket?

The result is an app which allows people to report smog levels by uploading an image tagged with time and location. Then, a machine learning algorithm chews through the data and compares it against official air-quality measurements where it can. Over time, the team hopes the software will slowly be able to predict air quality from smartphone images alone.

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Carnegie Mellon University is embarking on a five-year, $12 million research effort to reverse-engineer the brain and “make computers think more like humans,” funded by the U.S. Intelligence Advanced Research Projects Activity (IARPA). The research is led by Tai Sing Lee, a professor in the Computer Science Department and the Center for the Neural Basis of Cognition (CNBC).

The research effort, through IARPA’s Machine Intelligence from Cortical Networks (MICrONS) research program, is part of the U.S. BRAIN Initiative to revolutionize the understanding of the human brain.

Continue reading “CMU announces research project to reverse-engineer brain algorithms, funded by IARPA” »

Researchers at the University of Bristol have created ‘Mogrify’ — an algorithm that can predict how to reprogram virtually any type of cell

One way of creating new cells is with stem cells. The most famous of these are embryonic and induced pluripotent stem cells, the latter made from your own cells. While these cells have immense potential, the process of creating them is complicated and not without error. Coaxing these cells into a new type once you’ve made them is also easier said than done.

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Twitters 1st step to recapture consumers.

A Tweetstorm is brewing in San Francisco.

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Nice — Bridgewaters engaged. Actually, not too surprised by this.

IBTimes UK spoke to AI finance startup Walnut Algorithms about machine learning and the financial sector.

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