Google unveiled its artificial intelligence software this summer that could recognize faces of cats, people and other things by training on YouTube videos. The technology is now being used to improve the results for Google’s products, such as speech recognition for Google Voice.
Google’s neural network, which processes data similar to the way the brain works and learns, is based on simulating groups of connected brain cells that communicate with each other. When it absorbs data, the neural network becomes better at processing it and recognizing relationships among the data. That’s what we call learning.
Vincent Vanhoucke, leader of Google’s search recognition efforts, told Technology Review that results have been improved 20 percent to 25 percent for speech recognition. Other Google products could benefit too.

The fight of producers in the region against diseases in citrus is intense. The attention is mainly focused in three diseases that the European Union considers to be cases worthy of quarantine: scabies, cancrosis and Dark Spot. A single fruit infected and exported can cause a whole shipment to be refused. And the ones able to identify those diseases are few.
But the story is about to end, since new advances in artificial intelligence are reaching the citrus sector. Soon a photo will be enough, when sent to a system that can detected if the fruit is infected or not. This is the result of work carried out by experts at the Investigation Group for Signs and Computational Intelligence from the School of Engineering and Hydric Science in the National University of the Coast and CONICET.

Researchers at EPFL have developed a system that manages multiple parameters and learns what is best for your house by imitating the most complex computer in the world – your brain. The technology has spun off into a new start-up called Neurobat.
The Neurobat regulator has already been installed in several test buildings, among which are one at CSEM, and one in a private villa. Various tests have shown savings in fuel up to 65%, which suggests that savings of around 50% are envisageable in an average building.

It may seem strange to think of the first manned spaceship to Mars as a flying farm. But consider how difficult it would be to carry all the food a crew would need for what might be a three-year round-trip voyage. Much better to grow your food as you go. AEMC (Advanced Environmental Monitoring and Control) Bioregenerative Life Support project at NASA is using Neural Network to control the on board green machine and keep it humming at peak efficiency.

All medications have side-effects from common aspirin to herbal remedies and from standard anticancer drugs to experimental immunosuppressants. However, predicting important side effects, serious adverse drug reactions, ADRs, is with current understanding almost impossible. However, a neural network technology trained with past data could give drug companies and healthcare workers a new tool to spot the potential for ADRs with any given medication.
Writing in the International Journal of Medical Engineering and Informatics, at team from the University of Medicine and Dentistry of New Jersey, has developed a new model that tests show is 99.87 percent accurate in predicting adverse drug reactions among 10,000 observations for ADRs.

Liver fibrosis progression is commonly found in patients with CHB. Liver biopsy is a gold standard for identifying the extent of liver fibrosis, but has many draw-backs. It is essential to construct a noninvasive model to predict the levels of risk for liver fibrosis.

339 chronic hepatitis B patients with HBsAg-positive were investigated retrospectively, and divided at random into 2 subsets with twice as many patients in the training set as in the validation set; 116 additional patients were consequently enrolled in the study as the testing set. A three-layer artificial neural network was developed using a Bayesian learning algorithm. Sensitivity and ROC analysis were performed to explain the importance of input variables and the performance of the neural network.

Praxis Electronic Medical Records Announces New Version 5 With Breakthrough in EHR Documentation. Based on a unique technology called 'Concept Processing,' an intelligent neural network, Praxis EMR becomes progressively faster and smarter by learning from the physician using it. Physicians using Praxis 5 with Datum can chart rapidly with complete freedom while also producing discrete data required by third parties.

Researchers at the Mayo Clinic employed Artificial neural networks technique to assist in the diagnosis of a heart infection, endocarditis, related to implanted devices such as pacemakers. If left unchecked, such an infection can be fatal, and treatment is no certain cure. Under normal conditions, this disease has to be confirmed via an invasive surgical procedure, but the ANN allowed them to rule out endocarditis in cases of unknown diagnosis.

Nobody has automated the process of diagnosing epilepsy from ordinary EEG data--until now. Around 50 million people suffer from epilepsy--about 1 percent of the world's population, say Forrest Sheng Bao at Texas Tech University, in Lubbock, and a few pals. Bao and colleagues have come up with a system that may have a dramatic impact. Various groups have attempted to automate the process of epilepsy diagnosis using pattern recognition programs to spot the characteristic signature of the condition in EEG data. But these all depend on the EEG-video data that is so hard to get.

A GreaseMonkey userscript is able to solve simple CAPTCHA by using a purely JavaScript-based neural network implementation The intriguing piece of code runs locally and has been written by Shaun Friedle to subvert the CAPTCHA check of the Megaupload service.
An artificial neural network is a computational model used to analyze behavior in computational science. As opposed to a linear model, this one implies interconnected data processing artificial “neurons,” which establish relationships between input and output, and determine patterns.
GreaseMonkey is a powerful extension for Mozilla Firefox. It allows users to create local scripts written in JavaScript in order to alter the appearance and functionality of the web pages rendered within the browser. Common uses include blocking ads or certain unnecessary page elements from being displayed, thus resulting in a more resource-friendly and clean browsing experience.

As industrial-grade Artificial Neural Networks implementation for financial prediction, NeuralCode utilizes Supervised Learning with Multi-Layer Perceptrons and Optimized Back Propagation for complex learning. It uses historical data for predicting or uncovering trends and patterns. Inputs are fed into network with adjustable weights. When output is produced, it is compared with targeted output.

Quintura has developed a hosted site search platform built to provide intuitive, visual-based search and navigation for site visitors. Using a dynamic tag cloud to search deeper into an area, Quintura hopes to engage users in “site search far more than ever before, resulting in additional page-views and click-throughs.” Such a notion will be appealing to web publishers who can add Quintura’s hosted solution for free.