The smartphone boom upended Google's advertising profit engine and it took years for the Internet giant to adjust to the new mobile world. The next wave of computing will be an even bigger challenge. At Google's I/O developer conference this week near its Silicon Valley headquarters, the company unveiled new technology that will rely less and less on physical devices with screens to deliver information and services to consumers. Google hopes these advances will capture the human attention its business depends upon, and then it can figure out how to make money later, one executive said. Google Home will sit in living rooms sucking in voice-based queries and delivering verbal answers from an artificially intelligent "Google assistant."

If you're a man who's tried (or considered trying) online dating, chances are you've worried you might meet a woman looking to use you for a free expensive dinner. It seems trivial in comparison to what women have to worry about when they filter through men on dating sites, but it's still a concern, and it still happens to the best of us. My online dating profile doesn't mention my dad's accomplishments, but in moments of insecurity, I've been known to name-drop in order to keep the woman interested. It's never gone well, and it's never attracted the right women. The women who see me as "Giorgio the teacher" or "Giorgio the writer" have never tried to use me for a free dinner.

Artificial intelligence and voice-based computing are likely two of the main components of the smart devices of the future, and Amazon's surprisingly popular Echo is certainly one device to beat. The home assistant can offer fast responses to some of your immediate needs, like playing music, or giving you the information you require the most, including weather, traffic, sports scores, to name just a few. To many people, the Alexa assistant that powers Echo is about as robust as Siri. Apple's voice-assistant that resides inside the iPhone, iPad, Apple Watch, Apple TV, and iPod touch, can easily do the same things. But Alexa does things better and faster than Siri not because Amazon is better than Apple at processing voice requests, but because the devices offer vastly different experiences.

In a promotional video for Amazon's Echo virtual assistant device, a young girl no older than 12 asks excitedly: "Is it for me?". The voice-controlled speaker can search the web for information, answer questions and even tell kids' jokes. An investigation by the Guardian has found that despite Amazon marketing the Echo to families with young children, the device is likely to contravene the US Children's Online Privacy Protection Act (COPPA), set up to regulate the collection and use of personal information from anyone younger than 13. Along with Google, Apple and others promoting voice-activated artificial intelligence systems to young children, the company could now face multimillion-dollar fines. "This is part of the initial wave of marketing to children using the internet of things," says Jeff Chester, executive director of the Center for Digital Democracy, a privacy advocacy group that helped write the law.

There's an article going around that claims Apple could be the next BlackBerry as it gets left behind in the AI arms race. Yes, Google is better than Apple at some kinds of AI. If the tech giants were playing in Go, then Google would win by a mile. The thing is, Apple doesn't have to match Google in all kinds of AI, only the things that matter to Apple. How does Apple use AI today?

The secret to Viv is the system actually writes it's own code. In contrast to any other similar system, It is a profound and monumental giant leap forward. The structure of the Voice First world is held together by Intelligent Agents. Intelligent Agents use AI (Artificial Intelligence) and ML (Machine Learning) to decode volition and intent from an analyzed phrase or sentence. The AI in most current generation systems like Siri, Echo and Cortana focuses on speaker independent word recognition and to some extent the intent of predefined words or phrases that have a hard coded connection to a domain expertise.

Siri seemed pretty futuristic when Apple first released the voice activated virtual assistant. But with Google, Facebook, Amazon and a slew of promising startups pushing the limits of interactive interfaces, the original app for making your phone talk back to you is seeming like a bit of a relic. Leading thinkers in the world of tech are a little concerned. Influential Apple developer Marco Arment wrote in a blog post over the weekend that Apple was falling so far behind in developing artificial intelligence interfaces, the company could fall off the map like Blackberry did. The concern could soon be--and Apple surely hopes already is--irrelevant.

We've seen a big rise of apps and bots, and a lot of them have something in common besides being based on artificial intelligence and machine learning: they are written for English-speaking users.

Alphabet's Google Inc unveiled its answer to Amazon's Alexa virtual assistant along with new messaging and virtual reality products at its annual I/O developer conference on Wednesday, doubling down on artificial intelligence and machine learning as the keys to its future. Google Chief Executive Sundar Pichai introduced Google Assistant, a virtual personal assistant, along with the tabletop speaker appliance Google Home. He also unveiled Allo, a new messaging service that will compete with Facebook's WhatsApp and Messenger products and feature a chatbot powered by the Google Assistant. Allo, like WhatsApp, will also have end-to-end encryption when it is rolled out this summer. Amazon's Echo, a surprise hit that has other tech giants racing to match it, uses a virtual assistant called Alexa, a cloud-based system that controls the Echo speaker and responds to voice-controlled commands by users.

Matrix completion, where we wish to recover a low rank matrix by observing a few entries from it, is a widely studied problem in both theory and practice with wide applications. Most of the provable algorithms so far on this problem have been restricted to the offline setting where they provide an estimate of the unknown matrix using all observations simultaneously. However, in many applications, the online version, where we observe one entry at a time and dynamically update our estimate, is more appealing. While existing algorithms are efficient for the offline setting, they could be highly inefficient for the online setting. In this paper, we propose the first provable, efficient online algorithm for matrix completion. Our algorithm starts from an initial estimate of the matrix and then performs non-convex stochastic gradient descent (SGD). After every observation, it performs a fast update involving only one row of two tall matrices, giving near linear total runtime. Our algorithm can be naturally used in the offline setting as well, where it gives competitive sample complexity and runtime to state of the art algorithms. Our proofs introduce a general framework to show that SGD updates tend to stay away from saddle surfaces and could be of broader interests for other non-convex problems to prove tight rates.