Information Science – Lifeboat News: The Blog

Nov 3
2015

How Facebook Will Use Artificial Intelligence to Understand Your Entire Social Life

Short Bytes: Artificial Intelligence holds a special place in the future of the humanity. Many tech giants, including Facebook, have long been working on improving the AI to make lives better. Facebook has decided to reveal its milestones in Artificial Intelligence Research in the form of a progress report.

It doesn’t matter if you are scared of AI like Elon Musk or Stephen Hawking or if you have an opinion same as that of Google’s chief of Artificial Intelligence that computers are remarkably dumb. Companies are still going through the byzantine process of training the machines and creating human brain algorithms. Meanwhile, Facebook has just announced its progress report.

Facebook’s AI research team (FAIR) will present at NIPS, an Artificial Intelligence conference, its report card and reveal the team’s achievements regarding its state-of-the-art systems. Facebook has been trying to improve the image recognition and has created a system that speeds up the process by 30% using 10 times less training data from previous benchmarks.

Oct 30
2015

Physicists mimic quantum entanglement with laser pointer to double data speeds

In a classic eureka moment, a team of physicists led by The City College of New York and including Herriot-Watt University and Corning Incorporated is showing how beams from ordinary laser pointers mimic quantum entanglement with the potential of doubling the data speed of laser communication.

Quantum entanglement is a phrase more likely to be heard on popular sci-fi television shows such as “Fringe” and “Doctor Who.” Described by Albert Einstein as “spooky action at a distance,” when two quantum things are entangled, if one is ‘touched’ the other will ‘feel it,’ even if separated by a great distance.

“At the heart of quantum entanglement is ‘nonseparability’ — two entangled things are described by an unfactorizable equation,” said City College PhD student Giovanni Milione. “Interestingly, a conventional laser beam (a laser pointer)’s shape and polarization can also be nonseparable.”

Oct 28
2015

Why BPG will replace GIFs and not only

This means that BPG not only is way smaller than JPEG but also delivers a better quality. And that’s not all! It also supports animations!

And when I say animation, I actually say GIF-like movies with MP4 quality that are actually smaller than the mp4 it was built from.

Let’s see an example (I have not included a GIF example because the same quality size and frame rate means that the GIF will have exactly 33.8MB)

Oct 25
2015

Are the Laws of Physics Really Universal?

Can the laws of physics change over time and space?

As far as physicists can tell, the cosmos has been playing by the same rulebook since the time of the Big Bang. But could the laws have been different in the past, and could they change in the future? Might different laws prevail in some distant corner of the cosmos?

“It’s not a completely crazy possibility,” says Sean Carroll, a theoretical physicist at Caltech, who points out that, when we ask if the laws of physics are mutable, we’re actually asking two separate questions: First, do the equations of quantum mechanics and gravity change over time and space? And second, do the numerical constants that populate those equations vary?

Oct 23
2015

Why Self-Driving Cars Must Be Programmed to Kill

Self-driving cars are already cruising the streets. But before they can become widespread, carmakers must solve an impossible ethical dilemma of algorithmic morality.

Oct 20
2015

DNA Is Multibillion-Year-Old Software

Nature invented software billions of years before we did. “The origin of life is really the origin of software,” says Gregory Chaitin. Life requires what software does (it’s foundationally algorithmic).

1. “DNA is multibillion-year-old software,” says Chaitin (inventor of mathematical metabiology). We’re surrounded by software, but couldn’t see it until we had suitable thinking tools.

2. Alan Turing described modern software in 1936, inspiring John Von Neumann to connect software to biology. Before DNA was understood, Von Neumann saw that self-reproducing automata needed software. We now know DNA stores information; it’s a biochemical version of Turning’s software tape, but more generally: All that lives must process information. Biology’s basic building blocks are processes that make decisions.

Oct 17
2015

How Tesla is ushering in the age of the learning car

Tesla’s new autopilot system is relying on the cutting edge of machine learning, connectivity and mapping data.

While Tesla’s new hands-free driving is drawing a lot of interest this week, it’s the technology behind-the-scenes of the company’s newly-enabled autopilot service that should be getting more attention.

At an event on Wednesday Tesla’s CEO Elon Musk explained that the company’s new autopilot service is constantly learning and improving thanks to machine learning algorithms, the car’s wireless connection, and detailed mapping and sensor data that Tesla collects.

Oct 16
2015

System that replaces human intuition with algorithms outperforms human teams

Big-data analysis consists of searching for buried patterns that have some kind of predictive power. But choosing which “features” of the data to analyze usually requires some human intuition. In a database containing, say, the beginning and end dates of various sales promotions and weekly profits, the crucial data may not be the dates themselves but the spans between them, or not the total profits but the averages across those spans.

MIT researchers aim to take the human element out of big-data analysis, with a new system that not only searches for patterns but designs the feature set, too. To test the first prototype of their system, they enrolled it in three data science competitions, in which it competed against human teams to find predictive patterns in unfamiliar data sets. Of the 906 teams participating in the three competitions, the researchers’ “Data Science Machine” finished ahead of 615.

In two of the three competitions, the predictions made by the Data Science Machine were 94 percent and 96 percent as accurate as the winning submissions. In the third, the figure was a more modest 87 percent. But where the teams of humans typically labored over their prediction algorithms for months, the Data Science Machine took somewhere between two and 12 hours to produce each of its entries.

Oct 14
2015

New Portable Device Counts White Blood Cells Through the Skin

Madrid, Spain (Scicasts) — A novel way to count white blood cells without a blood test, simply by applying a small device on the fingertip, is being developed by a team of young bioengineers.

The technology, that combines an optical sensor with algorithms, has already three prototypes on the go and is specially designed to be used on chemotherapy patients, who could know their immune system levels in real time. It could also serve to detect serious infections.

A group of young bioengineers from various countries, including Spaniard Carlos Castro, is developing a portable device capable of counting white blood cells in real time, without requiring a blood test. The system includes an innovative optics sensor through the skin that can observe white cells as they flow past a miniature lens. This new device could be applied to improve the treatment of patients who are left immunosuppressed after chemotherapy treatments and to prevent sepsis.

Oct 9
2015

Brain simulation breakthrough reveals clues about sleep, memory

The Blue Brain Project is a vast effort by 82 scientists worldwide to digitally recreate the human brain. While still far from that goal, the team revealed a breakthrough that has already provided insight into sleep, memory and neurological disorders. They created a simulation of a third of a cubic millimeter of a rat’s brain. While that might not sound like much, it involves 30,000 neurons and 37 million synapses. In addition, the simulated level of biological accuracy is far beyond anything so far. It allowed them to reproduce known brain activities — such as how neurons respond to touch — and has already yielded discoveries about the brain that were impossible to get biologically.

To create the simulation, researchers did thousands of experiments on rat brains over a 20 year period, logging each type of synapse and neuron discovered. That led to a set of fundamental rules describing how neurons connect to synapses and form microcircuits. Using the data, they developed an algorithm to pinpoint the synapse locations, simulating the circuitry of a rat’s brain. All of that data was then run through a supercomputer: “It was only with this kind of infrastructure that we could solve the billions of equations needed,” said software lead Felix Schurmann.