Digital Asset Managers and administrators spend an enormous amount of time and energy on metadata application. It is tedious, thankless work, but absolutely necessary to find assets in the sea of digital petabytes. In the last few years, we've seen a growing number of applications -- Facebook, Ancestry.com, Netflix -- make use of machine learning to help perform specific tasks. Isn't it time your digital asset management (DAM) system did as well?

Artificial Intelligence will remain a high profile topic for years to come and rightfully so: research firms expect the market to grow at a CAGR of 50% to reach $37 billion by 2025. This will generate game-changing productivity gains and transform entire industries. Since the first successful AI experiments in 1955, progress has accelerated dramatically. AI is now broadly used, providing tangible applications for many consumers daily. Examples include Amazon's algorithms making pointed recommendations, Siri answering questions with real-time data from the internet and Watson entering many commercial markets, where AI was absent yesterday.

Google's voice assistant has been released into the wild, making an appearance in several blockbuster smartphones unveiled at Mobile World Congress (MWC) in Barcelona. The Siri-like assistant will feature in the latest flagship phones from Nokia, Samsung, Huawei LG, Sony and HTC. It's the first time the artificial intelligence (AI) powered Google Assistant has featured in any non-Google products as the Silicon Valley giant announced it would also come to all phones running the latest Android operating systems. Read more: Blackberry's famous qwerty keyboard is back It's a major move for Google which was late to the show, launching a voice assistant only in October last year for its Pixel phone and Home smart speaker. Meanwhile, Amazon has pioneered its Alexa assistant in the Echo device which first hit countertops in 2015.

One of the best features of the Pixel and Pixel XL smartphones is the Google Assistant, Google's own voice-activated assistant that competes with Apple's Siri. With today's announcement however, it looks like Google Assistant will be available on more devices starting this week. The great thing about Google Assistant is that it allows users to talk to their Pixel and Pixel XL phones in a conversational or natural way. Whether it's asking questions, making reservations and appointments, Google Assistant is can do it all. It has proven to be quite an impressive AI assistant and has even been lauded by some as even being smarter than Apple's Siri, Amazon's Alexa and Microsoft's Cortana.

These days, even when I read news about India's state owned air carrier, as "New AI connectivity between cities X & Y", the first connection my (poor human) brain makes is to Artificial Intelligence. Only then it connects to Air India. This is because everyone (in my extended professional circle) is talking of Artificial Intelligence. Though I had done a short elective on AI in my computer engineering days (16 years back), done some basic LISP programming as part of it, had presented a paper on'Genetic Algorithms' in a seminar (again that long ago), and am an avid watcher of Sci-Fi movies around AI (and claim to have understood Matrix the first time I watched it - with subtitles though, ha!), I realize that my knowledge of what AI is, is no better than a layperson (or worse, since half knowledge is more dangerous). This article is an endeavor to sort of unpack AI (and the associated words like ML - machine learning, DL - deep learning) for myself. And publishing it around to benefit others that are in a similar boat. And also to get feedback from others to correct my understanding. Without much dumbing down (or may be with), Artificial Intelligence is fundamentally anything that a computing machine does. Even the basic accountant calculator that does 2 2 4 is'artificial intelligence'. However, we do not consider them as'AI' because of what is called'AI effect' - When we know'how' a machine does something'intelligent,' it ceases to be regarded as intelligent. Tools we take for granted (pick any of your favorite app) are all'AI'. Anything that is'eaten by software' can be considered as Artificial Intelligence. And why is everyone talking about it?

We propose a privacy-enhanced matrix factorization recommender that exploits the fact that users can often be grouped together by interest. This allows a form of "hiding in the crowd" privacy. We introduce a novel matrix factorization approach suited to making recommendations in a shared group (or nym) setting and the BLC algorithm for carrying out this matrix factorization in a privacy-enhanced manner. We demonstrate that the increased privacy does not come at the cost of reduced recommendation accuracy.

We investigate a novel cluster-of-bandit algorithm CAB for collaborative recommendation tasks that implements the underlying feedback sharing mechanism by estimating the neighborhood of users in a context-dependent manner. CAB makes sharp departures from the state of the art by incorporating collaborative effects into inference as well as learning processes in a manner that seamlessly interleaving explore-exploit tradeoffs and collaborative steps. We prove regret bounds under various assumptions on the data, which exhibit a crisp dependence on the expected number of clusters over the users, a natural measure of the statistical difficulty of the learning task. Experiments on production and real-world datasets show that CAB offers significantly increased prediction performance against a representative pool of state-of-the-art methods.

Samsung's Windows-based Galaxy Books, unveiled Sunday at Mobile World Congress, point to a critical weakness in the company's multiple-OS strategy. The company uses Windows 10 in PCs, Android in smartphones, and Tizen across wearables and smart appliances. This has led to a lack of coherence among Samsung devices, in contrast to the near-seamless product integration that has fueled Apple's success as the world's most valued company. The specific issues with the Galaxy Books are relatively small, but are nevertheless symptoms of the larger problem: walls among devices and an inconsistent user experience across the company's product line. The lack of a broad app ecosystem for Samsung devices has not helped. Samsung has taken a siloed approach to product development, said Werner Goertz, lead Samsung analyst at Gartner.

Lenovo is working with Amazon to get the Alexa voice assistant into a range of Motorola smartphones, and in the process, looking to depose Google's voice assistant technology. The partners will first focus on developing an Alexa "Mod," a block that will attach to a Moto Z modular handset. The companies will then integrate Alexa directly into a variety of Moto handsets and devices, Lenovo said during a press conference in Barcelona on Sunday. The Moto Z is much like Google's Project Ara, where individual parts like speakers and projectors can be added to boost the functionality of the handset. The exact details of the Alexa Mod for Moto Z weren't provided, but an onstage image showed a speaker that could hook up to the handset.

The Huawei Watch 2 was revealed by the Chinese technology giant Sunday at Mobile World Congress in Barcelona. Huawei vows the 4G sport smartwatch will be "your perfect workout companion" in a trailer of the device promoted by the hastag #FreeYourSpirit. Users also have access to a workout data report. There a one-press button on the lower crown which allows users to start the workout app instantly, and also has quick training options with fat-burning run or cardio run modes. The device also supports offline music and has a built-in speaker.