We live in a world where artificial intelligence isn't science fiction -- it's reality. And, as Alex Konrad of Forbes previously reported, IBM Watson General Manager David Kenny is currently striving to make sure that AI becomes a "service" soon. Watson is IBM's artificially intelligent supercomputer (not to mention a Jeopardy champion). According to Forbes, IBM and Kenny expect Watson to expand into a 10 billion business within the next ten years. We're thrilled to announce that Kenny will be speaking about how AI is fueling the next massive wave of digital disruption and innovation at IGNITION 2016, Business Insider's flagship annual conference.

NVIDIA welcomes Intel into AI era: Fancy a benchmark deathmatch? New Chinese Cruise Missiles to Have'High Level of Artificial Intelligence'

Over the past several years, many new technological innovations in the healthcare industry have come and gone, but only a handful of trends matured and achieved widespread adoption among healthcare organizations. Bots are another new development that is piquing the interest of healthcare organizations and attempting to become more than a fleeting trend. Is the information collected by Fitbits and Apple Watches covered by HIPAA regulations? Find out more about what's covered – and what isn't – when it comes to wearable devices and data so you can avoid the risks. This email address is already registered.

There was a scene in the 1993 movie Demolition Man where Officer Huxley (Sandra Bullock, who hasn't aged a minute) asked John Spartan (Sylvester Stallone, who has aged for every minute Bullock hasn't) if he'd like to have sex. While most of us currently prefer the hunka chunka to simulated sex, with augmented and virtual reality technologies taking grand leaps every day -- this line of development was inevitable. It will also require artificial intelligence software to solidify and nurture that link, providing the stimulation based on learning factors. That's a dour outlook, but at the end of Demolition Man Spartan physically kissed Huxley and her brain reacted to this stimuli like it never had to the headset.

China is developing a new range of killer cruise missiles fitted with technology which will effectively turn them into killer robots. Dubbed "death drones", the missiles will use artificial intelligence (AI) to guide themselves in flight and potentially even choose new targets. Wang Changqing, director of the General Design Department of the Third Academy of the China Aerospace Science and Industry Corp, told China Daily that his country was leading the world in the development of AI weapons. He said: "We plan to adopt a'plug and play' approach in the development of new cruise missiles, which will enable our military commanders to tailor-make missiles in accordance with combat conditions and their specific requirements. "Moreover, our future cruise missiles will have a very high level of artificial intelligence and automation.

There was a scene in the 1993 movie Demolition Man where Officer Huxley (Sandra Bullock, who hasn't aged a minute) asked John Spartan (Sylvester Stallone, who has aged for every minute Bullock hasn't) if he'd like to have sex. Spartan, who had spent the last few decades literally taking a cold shower, expects physical contact. Instead, he gets a device slipped onto his head while Huxley puts one on hers. This has a name (albeit a ridiculous one), Teledildonics, and could soon become our new sexual reality thanks to advancements in robotics and artificial intelligence. While most of us currently prefer the hunka chunka to simulated sex, with augmented and virtual reality technologies taking grand leaps every day -- this line of development was inevitable.

The promise of big data is incredibly enticing and, for most businesses, just as out of reach. The reason is simple: today's databases are built upon 1970s math that was designed for 20-century data requirements and hardware capabilities. This math has led to tree-structures and associated algorithms that are incapable of delivering the flexibility, scale and performance needed for the dynamic big data world. Even newer tree-structure variants, which were developed in an attempt to solve these issues, can't keep up with big data entropy and velocity. Databases have rigid and complex data infrastructures, requiring an enormous amount of hand-holding to run (think calibration treadmill), and often sacrifice features for small upticks in performance and scale.

The TPG funded venture's enterprise solutions include applied artificial intelligence technologies using machine learning, predictive data analytics, and data sciences with human-centered design, business process engineering and big data. Stephen Pratt said that the large talent pool in India was what made Noodle.ai "Data science is different from software development life cycle and requires highly skilled professionals to build an artificially intelligent engine. We are hiring PhD and master's degree holders from India to work for Noodle.ai," Ted Gaubert, CTO at Noodle.ai wrote a bot programme that crawled through the web to generate and list of professionals with the skills the company was looking for and then the shortlisted candidates were interviewed.

If you don't know, Julia is "a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments." Julia is fast, and enjoys support from and integration with the Jupyter notebook environment. Julia can call C directly without a wrapper, integrates top tier open source C and Fortran code into its Base library, and can easily call Python as well. Julia is built for parallel and cloud computing, and has particular interest from the analytics and scientific computing communities. According to KDnuggets' most recent analytics software poll, Julia placed 8th on the list of most used programming languages.

If you passed high school math and can hack around in Python, I want to teach you Deep Learning. Edit: 50% Coupon Code: "mltrask" (expires August 26) I've decided to write a Deep Learning book in the same style as my blog, teaching Deep Learning from an intuitive perspective, all in Python, using only numpy. I wanted to make the lowest possible barrier to entry to learn Deep Learning. The Problem with most entry level Deep Learning resources these days is that they either assume advanced knowledge of Calculus, Linear Algebra, Differential Equations, and perhaps even Convex Optimization, or they just teach a "black box" framework like Torch, Keras, or TensorFlow (where you just hit "train" but you don't actually know what's going on under the hood). Both have their appropriate audience, but I don't believe that either are appropriate for your average python hacker looking for a 101 on the fundamentals.