IBM Watson may be able to win "Jeopardy!" The IBM Watson for Cybersecurity beta program launched this week with 40 partners around the world in an effort to help security analysts make better, faster decisions from vast amounts of data, but experts say this is the same promise offered by many other products. IBM said Watson for Cybersecurity will feature natural language processing that can help it to "understand the unique language of security." "The truth is a lot of security vendors today are attaching '[artificial intelligence]' or'cognitive' to a number of products that are really just advanced analytics or machine learning, which are also important elements that can help in the fight against cybercrime," Diana Kelley, executive security advisor for IBM Security, told SearchSecurity. "What Watson will bring to the equation that is unique is the ability to digest vast amounts of both structured data as well as all of the intelligence that exists in natural language, like blogs, white papers and research reports. For example, there are around 10,000 security research papers published each year, and 60,000 security blog posts published every month."

Deep neural networks have evolved to be the state-of-the-art technique for machine learning tasks ranging from computer vision and speech recognition to natural language processing. However, deep learning algorithms are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. To address this limitation, deep compression significantly reduces the computation and storage required by neural networks. For example, for a convolutional neural network with fully connected layers, such as Alexnet and VGGnet, it can reduce the model size by 35x-49x. Even for fully convolutional neural networks such as GoogleNet and SqueezeNet, deep compression can still reduce the model size by 10x.

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So, you want to learn how to build machine learning algorithms? But where do you start? Becoming a data scientist is a really smart career move – it's possibly one of the most valuable jobs out there. That's just one of the reasons it was hailed by the Harvard Business Review as the'sexiest job of the twentieth century' back in 2012. But learning the skills you need to become a truly great data scientist, capable of building powerful machine learning systems with languages like Python and R, isn't easy.

Moore's law, which says computing power doubles every two years, is getting harder to achieve on a single chip. Tech industry heavyweights including IBM, NVIDIA, Google and Mellanox are now working together through the OpenPOWER Foundation to enhance speed at the system level by engineering chips, interconnects, accelerators, memory and other components that work together seamlessly. This will help ensure fast and powerful AI systems that support breakthroughs on numerous key fronts. AI's evolution will continue to drive innovation that makes for smarter cities, improved healthcare, and other advances that will continue to improve our lives.

Few technologies have the transformative potential to reshape how we live, move, and work. Electricity and the Internet were two technologies that fundamentally transformed life in the 20th century. Artificial intelligence (AI) is the 21st century equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans. AI, in its simplest definition, is an umbrella term for technologies that are inspired by biological systems, giving computers human-like abilities related to seeing, reasoning, hearing, and learning.

It was a reliable sort of constant as innovators continued to increase the number of transistors per square inch on integrated circuits. But all good things must come to an end, and Moore's Law has been confounded by another, more immutable law: physics. Though transistors have shrunk to the size of molecules, they cannot--at least, not currently--shrink to the atomic level. However, though processing power has hit its limit, innovation in other areas has not. This is an opportunity for the combined forces of artificial and human intelligence to shine.

Pop culture these days is awash in tales of AI run amok, from machines that act like humans to humans in love with machines. The reason seems clear enough: We're anxious about a world in which machines have superseded us. Designers are already grappling with whether a robot should ever really act like a human. I don't mean robots in the futuristic sense, like you might find in Westworld or 2001, but rather robots that we're increasingly dealing with everyday. I mean the robots that live in Google Allo, Facebook Messenger, and a host of other new services that use chat-based assistants to serve up everything from airplane reservations to outfit advice.

Microsoft's slow advance into the mobile territory held by rivals Apple and Google continues this week with updates and expanded availability of a key mobile application that runs on the opposition's platforms. As iOS and Android circle the wagons to make sure that no other OS platforms can become established in the mobile space, Microsoft is playing a slightly longer game with a different target. Although Windows 10 Mobile is a great environment (and one that I personally enjoy) it does not have the market share or volume of mobile users that are needed to be self-sustaining. Which is why Microsoft is not only focusing on cloud-based services, but also ensuring they are usable on both iOS and Android as well as Windows 10. A quick glance at the app stores shows the prominence of Outlook, the utility of Outlook365, and the quiet magic of OneNote all riding high.

Artificial Intelligence (AI) is changing everything from marketing to healthcare. And this holiday season is the beginning of the future for how marketers will leverage AI to better understand, connect with, and create superior experiences for consumers. To better appreciate the impact that AI is having on retailers, I connected with IBM's first CMO, Michelle Peluso. Peluso has a strong background in retail, having served at the CEO of Gilt as well as the Global Consumer Chief Marketing and Internet Officer at Citigroup. Peluso provides her thoughts below on how Watson's AI capability is changing the way retailers impact the consumer shopping experience.