Based on the disturbing number of successful data breaches over the past few years, it's pretty evident that organizations are being overwhelmed by the growing number of threats. However, a new breed of security solution has sprung up, offering to apply machine learning to enterprise security. These tools deliver the ability to analyze networks, learn about them, detect anomalies and protect enterprises from threats.

Of the many misconceptions about machine learning, the idea that they can't be prejudiced is likely the most harmful. As stated by Moritz Hardt in How big data is unfair, machine learning is not, by default, fair or just in any meaningful way. Even though many researchers and practitioners have noted this repeatedly in the past, the message is still lost. It's not uncommon to hear variations of "algorithms don't have in-built bias" even when there is an entire field of research dedicated to fighting that very issue. To make this clearer, prejudice in machine learning will haunt us for years to come.

Can you tell the difference between talking to a human and talking to a machine? Or, is it possible to create a machine which is able to converse like a human? In fact, what is it that even makes us human? Turing's Imitation Game, commonly known as the Turing Test, is fundamental to the science of artificial intelligence. Involving an interrogator conversing with hidden identities, both human and machine, the test strikes at the heart of any questions about the capacity of machines to behave as humans.

Apps are tools that help us satisfy our needs and our desires. Yet our operating systems know nothing of our needs and desires. My word processor doesn't know why I'm opening it; my email client why I'm composing a message; nor my social network service what I'm looking for in the hundreds of posts that could appear in my feed. The burden of translating needs and desires into apps and operations that those apps can understand falls onto the user. He has to break down his purpose into a plan and each of the steps of this plan has to be an operation that his device can perform.

Open AI, a non-profit artificial intelligence research company backed by Elon Musk, launched a toolkit for developing and comparing reinforcement learning algorithms. OpenAI Gym is a suite of environments that include simulated robotic tasks and Atari games as well as a website for people to post their results and share code. OpenAI researcher John Schulman shared some details about his organization, why reinforcement learning is important and how the OpenAI Gym will make it easier for AI researchers to design, iterate and improve their next generation applications.

Mary Shelley's Frankenstein was the first pop culture example of artificial intelligence. Since then, the media, and especially Hollywood have depicted artificial intelligence numerous times. The depictions of artificial intelligence that we see in movies like Terminator or I, Robot are still nothing but science fiction, but the possibility of super smart artificial intelligence capable of matching human intelligence is no longer a far-fetched idea. In fact, due to the exponential growth of the artificial intelligence industry, we could see that level of artificial intelligence in a matter of years. According to analysts who track the growth of computing costs and the costs for such technologies, in just four years, 4,000 dollars would be enough to buy a computer than could rival the human brain.

Artificial intelligence just might be the biggest game changers in the world of technology this century. One of the reasons it has grown so quickly in such a short period of time is because businesses are beginning to see the useful real-world applications it has to offer. Already, dozens of industries such as healthcare diagnostics, automatic trading, business processing, advertising, and social media are using artificial intelligence to operate more efficiently and be more successful. It's predicted that spending on artificial intelligence will increase from just over 200 million in 2015, to over 11 billion in 2024 as more businesses begin to invest in the technology.

When Google's AlphaGo computer program triumphed over a Go expert earlier this year, a human member of the Google team had to physically move the pieces. Manuela Veloso, the head of Carnegie Mellon's machine learning department, would have done it differently. "I'd require the machine to move the pieces like I do," she says. "That's the world in which I live, which is a physical world." If Google can make cars that drive themselves, surely it could add robotic arms to a Go match. Even in 1997, I.B.M. could have given Deep Blue robotic arms in its match against Garry Kasparov.

Chinese search engine Baidu and chipmaker Nvidia announced a partnership Thursday that will focus on using artificial intelligence to develop a computing platform for self-driving cars. The platform will include cloud-based high-definition maps. The announcement, made by Nvidia CEO Jen-Hsun Huang at the Baidu World Conference, will bring together two companies that see vast potential in artificial intelligence. It also comes on the heels of Baidu receiving approval from the California Department of Motor Vehicle to test autonomous vehicles on public roads in the state. Baidu bidu is the 15th company to receive a permit to test autonomous vehicles in California.

LG is certainly no stranger when it comes to robotics and smart appliances, but until now, such products have had limited use. With the company's latest announcement, this will change. The electronics giant has confirmed that it's currently investing a lot of resources into robots in the hope of capitalizing on advanced AI, which could eventually be implemented into products that combine hardware with artificial intelligence in order to work with smart home appliances as well as to develop machines that could perform everyday tasks. "We will prepare for the future by aggressively investing in smart home, robots and key components and strengthen the home appliances business's capabilities," said Jo Seung-jin, head of LG's appliances business. As of now, there's no time frame for when we'll see the results of these investments on the shelves, but LG already has plans for products that will work with air conditioners and washing machines, though combining AI with self-driving cars is also something the company is researching.