What is Artificial Intelligence?

a diagram illustrating how the photovoltaic retinal prosthesis works

A Pro-forming photovoltaic artificial retina has just been launched after several years of research and development.

The good news is, this retinal prosthesis works by feeding the embedded solar cells with a beam of light. Unlike other types of retinal prosthesis which uses RF signals to power the nano-circuits, this new retinal prosthesis uses light to activate both power and data cells.

Researchers from Standford University have uniquely designed this photovoltaic retinal prosthesis with miniature solar cells. The 3mm thick subretinal device works together with a video camera that captures images, a pocket PC that processes the video feed, and a bright near-infrared LCD display built into video goggles, which beams invisible light to the chip.

This Stanford device is implanted in the back of the retina. The chip is also configured in three layers such that together are 30 micrometers thick. The layer is a series of pixels, each formed from a three photovoltaic cells of three different sizes. The purpose of which is to boost the amount of current each pixel sends to the still functional intermediate layers of the retina that perform the eye’s natural image processing and data compression.

According to Daniel Palanker, a Stanford professor of ophthalmology who worked on the chip, "a photovoltaic prosthesis is limited to a pixel size of about 50 µm, corresponding to visual acuity of 20/100." Which is already sufficient for face recognition and for reading large fonts.

Click here to read more about Photovoltaic Retinal Prosthesis, Standford Artificial Retina

artist's rendring of brain activities

Natural brain activities have been measured to show changes in the learning curves of the brain connection during particular activities.

Researchers from Washington University School of Medicine in St. Louis and the University of Chieti, Italy, have recently reported in their study that the brain's spontaneous activity is but organized in patterns of correlated activity. Furthermore, this study have shown that the learning behaviors have caused considerable changes in the spontaneous brain patterns.

The researchers performed an experiment on 14 volunteers who were brain-scanned through fMRI as they rested. Then, they were scanned again as they went through the activities involving watching displays of MRI patterns with an inverted 'T' in an area of the screen. The activities lasted for five to seven days.

After the experiment, the subjects were scanned for the third time while they did nothing.

fMRI scan results have shown that at the start of the experiment, while the subjects rested, the spontaneous brain activities in the two parts of the brain were weakly correlated with the two regions involved in the activities.

Also, scans showed that either of these two is active during the tests, meaning they do not work simultaneously which lead to the conclusion that "disruption of spontaneous correlated activity may be a common mechanism through which brain function abnormalities manifest in a number of neurological, psychiatric or developmental conditions," Corbetta says.

Click here to learn more about Learning 'Sculpts of the Brain, Spontaneous Brain Patterns, Anti-Correlation between Parts of the Brain

captcha technology is continually evolving to outstmart robot hackers

"Humans have a very special skill that computer bots have not yet been able to master," says Prof. Cohen-Or leader of a research project of the Tel Aviv University's Blavatnik School of Computer Sciences.

CAPTCHAs were first developed to prevent bots from adding URLs to the search engine. The idea was contextualized in 1997 by Andrei Broder, Martin Abadi, Krishna Bharat, and Mark Lillibridge, who used images resistant to OCR (Optical Character Recognition).

CAPTCHAs are specifically designed as tasks that only humans can perform. Several researchers attempted to create a reliable 'captcha' application. A few of these applications like computer character recognition, voice or sound and image recognition are still widely used today.

Adding to the list is another 'emergence technology' which is being developed at Tel Aviv University's Blavatnik School of Computer Sciences to better outsmart computer bots.

The team demonstrated how a video captcha code may be harder to outsmart. Using a technology called an 'emergence image', an object is only recognizable when it's moving, and a person can identify this image in a matter of seconds.

In a recent research paper, Dr. Cohen-Or, co-authored by colleagues in Taiwan, Saudi Arabia and India, described a "synthesis technique" that involves generating images of 3-D objects, like a running man or a flying airplane that will enable security developers to generate an infinite number of moving "emergence" images that will be virtually impossible for any computer algorithm to decode.

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A Day With Keats, painting by William James Neatby (1860-1910)

A painting masterpiece is an art. But how does a typical computer interprets it? This is quite difficult to do when we talk of high-level concepts of classification, like how, we, humans use our perception abilities and unique taste in art.

But a group of researchers from the University of Girona and the Max Planck Institute in Germany has shown a schematic evidence that a computer can now understand how paintings are done and classified.

They developed mathematical algorithms that provide clues about the artistic style of a painting. How the painter made his brush strokes create a masterpiece that stands to astound many people. The unique composition of colors or certain aesthetic measurements can already be quantified by a computer, but machines are still far from being able to interpret art in the way that people do.

Using low-level classification, the researchers were able to show that their artificial vision algorithms can be programmed to "understand" pictures and compare between artistic strokes.

Lady with flowers by Edmund H. Garrett (1853-1929)

The artificial vision algorithms makes use of low-level pictorial information to determine an artist's brush thickness, the type of material used and the composition of the palette of colors. Although the researchers admit that it's absolutely difficult to copy how humans interpret art, but, according to them "they can look for trends".

Click here to read more about Understanding Art Through Computer, Artificial Vision Algorithms.

ClimateWizard is an interactive database of complete climate information

A new web tool has just been demonstrated at the The Nature Conservancy in Copenhagen, Denmark, in conjunction with an on-going climate summit. The lead author and presenter, Evan Girvetz worked on the this new model of the world climate during his postdoctoral work at the University of Washington's School of Forest Resources and just accepted a job with The Nature Conservancy.

Climate Wizard is the latest web tool that accesses complete information of the world's climate in real time. The new tool can be used by both scientists and non-scientists to get interactive information on projected temperature and precipitation changes using 16 of the world's most prominent climate-change models.

The web tool can be used also to gather data on habitat shifts that will affect endangered species, places where crops could be at risk because of drought and temperatures that could cripple fruit and nut production in California's Great Central Valley.

Climate Wizard uses several parameters to maximize collection of data. One can generate climate changes for the past 50 years, or even 50 future years until the end of the century 2080.

It is a large database of information using the Intergovernmental Panel on Climate Changes on estimates of greenhouse gas emissions being high, medium or low in the future. All other variables are generated on colored maps of focused states, countries or regions around the world.

Click here to read more about Climate Wizard, World Climate software, World Climate Information Database