The Bossier City Police Department has a new tactical police robot worth over 25,000, and it's all thanks to a grant from Firehouse Subs' Public Safety Foundation. "In the last 10 years, we have been able to raise and make donations totaling 18-million in 45 states and Puerto Rico, which I think is great," said foundation spokesman Jim Maxwell. Maxwell said there were nearly 80 grants approved for 1.2-million throughout the country just last week from the foundation. "This happens to be the third grant in the Bossier City and Shreveport area that we've been able to do over the past year," Maxwell said. "We're real happy to do it, we're proud of what we do, we're proud of being able to give back to the community, and we're really proud of our franchisees and team members who really make this happen."

This week Stephen Wolfram, founder and chief executive of Wolfram Research, announced a new component of the Wolfram Language for programming called ImageIdentify. Wolfram also introduced a new website, dubbed The Wolfram Language Image Identification Project, that demonstrates the language's new capabilities. The new site lets you upload images and get inferences and definitions in response. You can provide feedback, which should help it become more accurate. You can hit buttons like "Great!," "Could be better," "Missed the point," and "What the heck?!" After you choose one, the service offers a few more guesses, and a text box where you can type in a tag.

Machine learning (also popularly called "Deep Learning"), cognitive computing and AI are words that now feature in our daily vocabulary. Yet understanding what they actually mean is not quite as common as you might think. The closest misapprehension we get is that Deep Learning is some form of artificial intelligence and computers are networked in ways that are like a human brain. Deep Learning is a very weak form of artificial intelligence where a complex algorithm is trained to recognize patterns during a supervised stage which then leads to greater confidence of accuracy in its unsupervised stage. Considering that I just introduced two new terms trying to explain the first one it will probably be best if we take things from the beginning.

DeepMind was a relatively unknown artificial intelligence (AI) startup in London up until 2014, when it was bought by Google for around 400 million. Today some of the smartest people in the world are queuing up to work at DeepMind, according to an article by Celemency Burton-Hill in The Guardian in February. Interestingly, the same article states that no one has ever left DeepMind, which has created a series of algorithms that can learn for themselves and beat the best humans at games like Go and "Space Invaders." Based in up-and-coming King's Cross, DeepMind now employs around 250 people. However, as Burton-Hill points out, getting a job there is far from easy.

They took NYC Data Science Academy 12 week full time Data Science Bootcamp program between Sept 23 to Dec 18, 2015. The post was based on their second class project(due at 4th week of the program). Our project is centralized around the development of an open source workbench that is focused on providing data scientists with automated tools for exploratory analysis and model selection. The full stack design is made in R, a statistical programming language. Before getting into the low-level details, let's take a step back and think about the trending term "Data Science."

Amazon Services is one of the fastest growing businesses within Amazon. There are over 1.9 million merchants, ranging from students selling their text books to nation-wide retail chains, selling on Amazon's international marketplaces. Collectively, these merchants are responsible for selling about 1/3rd of all items ordered from Amazon.com world-wide. AmazonServices.com is the destination online for sellers to learn, sign-up and to grow their business with Amazon. The team is looking for passionate, talented, and super-smart software engineers.

One area of technology that is helping improve the services that we use on our smartphones, and on the web, is machine learning. Sometimes, the terms machine learning and artificial intelligence get used as synonyms, especially when a big name company wants to talk about its latest innovations, however AI and machine learning are two quite distinct, yet connected, areas of computing. The goals of AI is to create a machine which can mimic a human mind and to do that it needs learning capabilities. However the goal of AI researchers are quite broad and include not only learning, but also knowledge representation, reasoning, and even things like abstract thinking. Machine learning on the other hand is solely focused on writing software which can learn from past experience.

Non-human employees are filling positions in all sorts of workplaces, and they are proving themselves to be fast, accurate, and reliable--more so than their human counterparts. That's why Apple's supplier Foxconn is reported to be replacing up to one million workers with robots in order to meet expected demand for the iPhone 6. And it's why Amazon deploys an army of robots to fetch items in its warehouses. It's also why machines powered by artificial intelligence (AI) are now reading MRIs, sorting through thousands of legal cases to identify pertinent information, and writing news articles. The displacement of workers by technology is nothing new, of course, but the nature of our rapidly advancing technology is, as is the wide variety of roles it's poised to replace.

A report published by the libertarian think tank the Cato Institute warns that the fruits of technological innovation could mean a new range of unexpected threats to the United States. Terrorists and small states equipped with weapons that take advantage of new technologies could devastate U.S. forces abroad--and even strike the homeland. Hammes, a retired U.S. Marine Corps infantry officer and expert on so-called "asymmetrical warfare"--warfare in which combatants avoid enemy strengths to strike weaknesses--warns that technologies such as 3D printing, nanotechnology, space and near-space travel, drones, and artificial intelligence could lead to cheap, inexpensive weapons with intercontinental reach, devastating lethality, and the ability to overwhelm U.S. defenses. According to Hammes, the linchpin of these capabilities is additive manufacturing, or 3D printing. Combine those two and you have a tiny tank hunter that can be difficult for tank crews to shoot down.

Microsoft has decided to pull back its first publicly available artificial intelligence (AI) robot, after a horrible test run. Earlier this week, Microsoft released an artificial intelligence named Tay, who ran through an official Twitter Account, @Tayandyou. Within 24 hours of Microsoft releasing the AI on Twitter, Tay was shut down by Microsoft because of the offensive subject matter the bot was tweeting out. In a CNN Money Article by Hope King titled "After racist tweets, Microsoft muzzles teen chat bot Tay," a comment was made by Microsoft on the incident. "Microsoft blamed Tay's behavior on online trolls," according to the article, "saying in a statement that there was a coordinated effort to trick the program's commenting skills."