Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. The artificial intelligence (AI) component in these programs aims to Read More ... Tags: Computer systems Computer Software Artificial intelligence Artificial intelligence software San Francisco (AFP) - Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. According to PRNewswire, Arria NLG, a leader in artificial intelligence ("AI") and natural language generation ("NLG"), is pleased to announce the private beta launch of Articulator Lite, a cloud-based toolkit that allows users to build their own applications that create content from data.

Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. The artificial intelligence (AI) component in these programs aims to make create a world in which everyone can have a virtual aide that gets to know them better with each interaction. Google is making a high-profile push into AI, with the internet titan's chief referring to it as a force for change as powerful as powerful as smartphones. Google Assistant software is being built into new Pixel handsets--aiming to outdo Apple's Siri--enabling users to organize and use information on the devices and in the cloud--to check emails, stay up to date on calendar appointments, news or ask for traffic and weather data.

Neural Network architecture was based on NVIDIA's Self-driving car paper - End-To-End Learning for Self-Driving Cars

Agile development, rapid learning, granular instrumentation, a large-scale compute and data infrastructure, cutting-edge machine learning -- these are the ingredients that give innovative companies their edge. But to date, this mindset and approach have been largely confined to the world of software and Internet-based services. Look outside of that space and you'll find a wide range of industries -- some hundreds of billions of dollars in value -- that are slow-moving and starved of rapid iteration and learning. Think aerospace, transportation, manufacturing, logistics, material sciences, life sciences, and agriculture. These industries are ripe with opportunities for transformative startups, and are seeing a new wave of entrepreneurs capitalize on them by unlocking the agility and speed of learning we take for granted in the software world.

Having tried logistic regression the first time around, I moved on to decision trees and KNN. But unfortunately, those models performed horribly and had to be scrapped. Random Forest seemed to be the buzz word around the Kaggle forums, so I obviously had to try it out next. I took a couple of days to read up on it, worked out a few examples on my own before re-taking a stab at the titanic dataset. The'caret' package is a beauty.

Global automakers Toyota, BMW and insurer Allianz will license technology from Silicon Valley start-up Nauto, which uses cameras and artificial intelligence systems in cars to understand driver behavior, Nauto said on Friday. Nauto Chief Executive Stefan Heck told Reuters the carmakers and insurer will integrate the technology into their test vehicles and use the aggregate and anonymized data - whether on driving habits, difficult intersections, or traffic congestion - to help develop their autonomous vehicle strategies. The investment by BMWi Ventures, Allianz Ventures and the Toyota Research Institute underscores the auto industry's demand for smart systems to improve vehicle and driver safety, reduce liability and make fleet operations more efficient, while preparing for self-driving cars of the future. Terms of the deal were not disclosed, but the parties will each have an equity stake in Nauto. A third unnamed automaker also invested, Nauto said.

Apple chief executive Tim Cook is among the leading industry experts touting artificial intelligence as a tech on the cusp of world domination. Talking about the evolution of the smartphone, Cook told the Washington Post: "AI will make this product even more essential to you. It will become even a better assistant […] where you probably aren't leaving home without it today – you're really going to be connected to it in the future." But how so – will we soon be permanently wired to the web? Not quite, but we will have something that is, and is set to be very smart indeed.

Researchers at the University of Rochester have developed a model for processing natural language so that a robot can be given basic verbal commands and then act on them without the need for additional programming. Robots can be programmed to perform all sorts of repetitive tasks, but they don't adapt well to changing environments and circumstances. They rely on people to give them direction and orient them to a precise set of parameters that will not change. What if a person could simply tell the robot what is needed and that language could be understood and then acted upon, without the need for extensive programming? Researchers from Robotics and Artificial Intelligence Laboratory at the University of Rochester are working to address this problem.

For Deep Knowledge Ventures, the Hong Kong-based venture firm that added a machine learning algorithm named VITAL to its board in 2014, it was about adding a tool to analyse market data around investment opportunities. For global professional service firms experimenting in this space, machine learning could allow deeper and faster document analysis. And though you may not think you are competing with Silicon Valley salaries for talent, you are if you want great people: a great data scientist can easily be 50 times more valuable than a competent one, which means that both hiring and retaining them can be pricey. As the machine learning ecosystem evolves, companies will find interesting ways to combine in-house industry experience with a range of off-the-shelf tools and open source algorithms to create highly-customised decision-support tools.

Pretty much 100 percent of my generation is obsessed with Instagram. Unfortunately, I left the platform (sorry all) back in 2015. Simple reason, I am way too indecisive about which photos to post and what pithy caption to give them. Fortunately, with ample spare time, those who share my problem can now use an image captioning model in TensorFlow to caption their photos and put an end to the pesky first-world problem. I can't wait for the beauty on the right to start rolling in the likes with the ever-creative "A person on a beach flying a kite."