Building a simple but powerful recommendation system is much easier than you think. This guide explains innovations that make machine learning practical for business production settingsand demonstrates how even a small-scale development team can design an effective large-scale recommender. In this guide, Practical Machine Learning: Innovations in Recommendation, authors and Mahout committers Ted Dunning and Ellen Friedman shed light on a more approachable recommendation engine design and the business advantages for leveraging this innovative implementation style.

When Google unveiled its new smart assistant earlier this week, it revealed the most basic name possible: Assistant. You don't even really call it that -- to summon it from Google's new smart speaker, you'd address it with a simple "Hey, Google" or the same "OK, Google" that you'd use to activate its voice search and predictive service, Google Now. But Assistant's lack of personality was quite intentional, according to Jonathan Jarvis, a former creative director on Google's Labs team. While at the company, he led a team doing concept, strategy, and design on products like the Search app and even Alphabet's logo rebrand. Jarvis worked on Assistant only up until February, so he wasn't there for the final decision to use "Assistant" as the platform's name.

Last month, law firm Baker & Hostetler announced that it would employ IBM's artificially intelligent lawyer, Ross, to help ease its tedious workload. In a statement, the firm's chief technology officer said, "we believe that emerging technologies like cognitive computing and other forms of machine learning can help enhance the services we deliver to our clients." Ross, a system built on the back of IBM's Watson, claims to be able to interpret questions lawyers ask it, and read "through the entire body of law and returns a cited answer and topical readings from legislation, case law and secondary sources to get you up-to-speed quickly." But the first thing I noticed about Ross wasn't how many legal documents it can search at once, or how accurate it claims to be. It was the name: Ross.

Google is set to allow its Chromebook laptops to run Android apps in a bit to take on Apple and Microsoft. The laptops run a version of Google's Chrome browser instead of an operating system like Windows - but until now have been unable to download apps. According to market research firm IDC, in Q1 of this year Chromebook shipments overtook Macs in the U.S. The laptops run a version of Google's Chrome browser instead of an operating system like Windows - but until now have been unable to download apps. Later this year, they will be able to run all android apps, Google said. The machine uses Google's Chrome OS, which is based on the firm's web browser.

Built-in search, artificial intelligence, machine learning and a knowledge graph connecting billions of entities is how Google plans to ultimately compete and win in many markets where it isn't first today. It's easy to note the me-too items outlined at Google I/O. Android N has a few new features, but doesn't advance the ball that much. Mobile platforms have hit the service pack, incremental update mode. Google Home is Google's answer to Amazon's Echo.

MindMeld, a pioneer in conversational AI technology, is today releasing the MindMeld for TV platform, which the company bills as the first solution designed for television and over-the-top content providers -- like Netflix and Hulu -- to deliver best in class discovery through a conversational interface. That company boasts investors and customers like Google, Samsung, Intel, Telefonica, IDG, Spotify, and other major global brands. Since MindMeld provides data services and the underlying tech-for-voice interface, the company couldn't explain exactly which products in market are 100 percent powered by their technology. But the company's voice platform is fast, alarmingly accurate, and likely baked into tons of products we interact with in some form or another. MindMeld was founded in 2011 and is backed by over 15 million in funding.

Google Inc.'s latest technological marvels point to a future where you'll never need to visit websites, write a term paper or stress over what to buy for your mother's birthday. For consumers seeking convenience and speed, it all sounds great. But how will any of it make Google money? The Mountain View, Calif., company's apparent transition from go-to search engine to omnipresent virtual assistant probably will require rethinking its advertising business. By tracking Web browsing, emails, chats and more, Google has become a dominant force in digital ads.

Silicon Valley companies have long battled one another for your money, your attention, and your data. Now they are fighting one another over a new battleground: Your living room. Google on Wednesday unveiled Google Home, a voice-activated, Internet-connected speaker with a built-in virtual assistant powered by Google's smarts. Home is Google's answer to the Echo, a similar device from Amazon that has become a surprise hit with shoppers. For consumers, Google Home and the Amazon Echo can answer questions about the weather, set alarms, and manage appointments, among other tasks.

Alphabet Inc.'s (NASDAQ:GOOG) Google is reputed as having one of the most intelligent artificial intelligence infrastructure globally. Its wide reach via its Chrome browser and Android mobile operating system means its influence runs deep. The main issue is whether the company can really find the right mix to convert these enviable advantages into the next in-demand product. This is the question most attendees at the company's annual I/O developer conference. This question was partly answered by Google CEO Sundar Pichai.

After a group of researchers scraped up a dataset using open profiles on OkCupid, they argued that the data was "public" and therefore fair game. Not so, writes professor of law Woodrow Hartzog. "This justification is fundamentally wrong. Not just because we should be able to expect a certain amount of privacy in public, but because, despite frequency of use and seeming self-evidence, we actually don't even know what the term public even means," Hartzog argues. "It has no set definition in privacy law or policy."