I was eager to learn about the latest developments in the Semantic Web through the lens of a "new kind of semantics" as Abraham Bernstein et al. explored in their Viewpoint "A New Look at the Semantic Web" (Sept. If I understand it correctly, semantics is a mapping function that leads from manifest expressions to elements in a given arbitrary domain. Based on set theory, logicians have developed a framework to set up such mapping for formal languages like mathematics, provided one can fix an interpretation function. On the other hand, 20th-century logicians (notably Alfred Tarski) warned of the limits of the framework when applied to human languages. Now, to the extent it embraces a set-theoretic semantics (as in the W3C's Ontology Web Language), the Semantic Web seems to be facing exactly such limitations or experiencing, dealing with, and suffering them.

Changing geopolitical strategy and rapid technological progress are also conspiring to render the term military increasingly incoherent. The United States--the one power to emerge unscathed from World War II and ascendant from the Cold War, and the one power that invests the greatest amount of resources in its battle-hardened military--possesses such overwhelming conventional military superiority over anyone else that potential adversaries instead embrace asymmetric warfare. Thus, Gen. Valery Gerasimov, chief of the General Staff of the Armed Forces of Russia, wrote in a seminal article in 2014 that "the very'rules of war' have changed. The role of nonmilitary means of achieving political and strategic goals has ... in many cases ... exceeded the power of force of weapons in their effectiveness." He also spoke of the need for "the broad use of political, economic, informational, humanitarian, and other nonmilitary measures," with conventional force "resorted to ... primarily for the achievement of final success in the conflict."

This month, I will attend the Conference and Workshop on Neural Information Processing Systems (NIPS), the premier gathering in the machine learning field. I've participated in this conference most years since it began in 1987 and I'm looking forward once again to catching up with colleagues and friends as well as exploring new developments in the field. Until recently, the conference attracted a few hundred attendees. The number of participants has grown rapidly in recent years and this year there are more than 4,500 people registered! This explosion of activity in machine learning is remarkable and reflects the positive trend of research making its way to the marketplace.

The U.S. Internet giant announced that Google Translate has been switched to a new system called Neural Machine Translation (NMT), an end-to-end learning framework that learns from millions of examples. The multilingual system is based on machine learning that provides computers with the ability to learn without being explicitly programmed. Unlike the current translation system that was adopted 10 years ago, the new system considers the entire sentence as one unit. Previous systems translated words and phrases independently within a sentence. Google said the NMT interprets entire sentences, making the translation not only sound much more like a native speaker of the language but more accurate.

Amazon Web Services CEO Andy Jassy introduced a bevy of new services and capabilities at the AWS re:Invent conference in Las Vegas this week. The new analytic and artificial intelligence (AI) services aren't unique, but there's little doubt they'll be huge hits. Jassy framed his announcements around the theme of giving enterprises "superpowers." Examples included powerful new compute instances supporting superhero-like speed, new database services enabling "flight" from the high cost of commercial databases, and new IoT services enabling "shapeshifting" out to the edge of the enterprise. I was most interested in the "X-Ray Vision" introductions, which included Athena and QuickSight analytic services and Rekognition, Polly and Lex artificial intelligence (AI) services.

A U.K. startup that uses artificial intelligence to help banks and other financial firms with anti-money laundering compliance received $8.2 million to fund its expansion in Europe and North America. The financing for London-based ComplyAdvantage is being lead by British venture capital firm Balderton Capital. The company, which said in a statement it has 200 clients globally, said it would use the money to expand its operations, adding to its current team of about 50 employees. It will also open a sales office in New York this week. Complying with the growing body of anti-money laundering and know-your-customer regulations around the world is becoming an expensive headache for financial institutions.

Then came eBay and Amazon in 1995....... Amazon started as bookstore and eBay as marketplace for sale of goods. Since then, as Digital tsunami flooded, there are tons of websites selling everything on web but these two are still going great because of their product recommendations. We as customers, love that personal touch and feeling special, whether it's being greeted by name when we walk into the store, a shop owner remembering our birthday, helping us personally to bays where products are kept, or being able to customize a website to our needs. It can make us feel like we are single most important customer. But in an online world, there is no Bob or Sandra to guide you through the product you may like.

As we go about our daily lives, we tend to assume that our perceptions--sights, sounds, textures, tastes--are an accurate portrayal of the real world. Sure, when we stop and think about it--or when we find ourselves fooled by a perceptual illusion--we realize with a jolt that what we perceive is never the world directly, but rather our brain's best guess at what that world is like, a kind of internal simulation of an external reality. Still, we bank on the fact that our simulation is a reasonably decent one. If it wasn't, wouldn't evolution have weeded us out by now? The true reality might be forever beyond our reach, but surely our senses give us at least an inkling of what it's really like.

At the AWS re:Invent event, Amazon has announced a host of new services that highlight its commitment to enterprises. Andy Jassy, CEO of AWS, emphasized on the innovation in the areas of artificial intelligence, analytics and hybrid cloud. Amazon has been using deep learning and artificial intelligence in its retail business for enhancing the customer experience. The company claims that it has thousands of engineers working on artificial intelligence to improve search and discovery, fulfillment and logistics, product recommendations, and inventory management. Amazon is now bringing the same expertise to the cloud to expose the APIs that developers can consume to build intelligent applications.

It was in this same dingy diner in April 1993 that three young electrical engineers--Malachowsky, Curtis Priem and Nvidia's current CEO, Jen-Hsun Huang--started a company devoted to making specialized chips that would generate faster and more realistic graphics for video games. "We've been investing in a lot of startups applying deep learning to many areas, and every single one effectively comes in building on Nvidia's platform," says Marc Andreessen of venture capital firm Andreessen Horowitz. Starting in 2006, Nvidia released a programming tool kit called CUDA that allowed coders to easily program each individual pixel on a screen. From his bedroom, Krizhevsky had plugged 1.2 million images into a deep learning neural network powered by two Nvidia GeForce gaming cards.