Google today said that it's acquired API.ai, a startup with tools for speech recognition and natural language understanding. Terms of the deal weren't disclosed. In addition to its developers tools, Api.ai offers a conversational assistant app with more than 20 million users. Google did not disclose its plans for integrating the startup's technology. That will be important, as Google already has tools for natural language understanding and speech recognition, and it has unveiled a Google Assistant that will be available through text messaging interface and the Google Home smart speaker.

But the upcoming innovation in chat is about being more human, not less. With the proliferation of adequate speech recognition, AI assistants, and wireless headphones, the tech is ready to unlock the potential of our most basic form of communication. Soon, we'll talk and listen to our messaging apps when it's more convenient than typing or reading. The age of voice is about to arrive. When we've got our hands full.

The launch of Google's app called Google Trips is, on the surface, just another travel app helping you organize your trip. But, really this is not what it is at all. Google's universe, these days, is being powered by machine learning algorithms everywhere. Being what we can best imagine as localized artificial intelligence programs they also inform each other and sync seamlessly from different regions of the Googleverse to provide a seamless experience. So Gmail (AI enhanced, these days), talks to Google Maps and Google Search, Google Now and even Chrome to better understand what the end user is doing it provides a helpful AI assistant in the guise of an app that aims to take the stress away from working out the details of travel so that you can focus instead on what is truly important: the content of your trip.

Business tech companies are going to get an overdose of AI marketing. Your friendly neighborhood enterprise software provider has a window into much of your corporate data. And now it wants to provide you with artificial intelligence-fueled insights in what'll equate to a barrage of characters -- Watson, Einstein, Alexa, Siri, Cortana -- a lot of jargon and with any luck some actual automated digital processes. Rest assured you may wind up with the former before getting to the latter destination. There are some things that machines are simply better at doing than humans, but humans still have plenty going for them.

Since blogging that I Need an AI BS-Meter a number of people have sent me pointers to a subset of AI I loosely think of as Result Explainers -- everything from pending government regulations (EU's Global Data Protection Regulations -- GDPR) to the latest in academic research (Local Interpretable Model-agnostic Explanations -- LIME). As the authors of the EU's GDPR state, widespread adoption of AI cannot occur until vendors are able to communicate results in a "concise, intelligible and easily accessible form, using clear and plain language." This got me thinking, "What should Result Explainers look like?" Should they generate trust scores, a series of Google-Maps like directions that get you from data to results, a series of diagrams? And as my colleague Patrick at Lab41 has pointed out, "Why should we trust a Result Explainer if we don't trust AI to begin with? As you might expect there isn't one right answer. That said, recent advances in recommenders, digital assistants, user interface design and initiatives like DARPA's recently announced Explainable Artificial Intelligence (XAI) grand challenge suggest we may be on the brink of a few breakthroughs. Again, as the authors of the EU's General Data Protection Regulations note, while the resulting classifiers, models, predictors, etc. can be very powerful they also frequently confound explanation -- e.g., the output of SVMs and Gaussian processes can be difficult to render, ensemble methods hide information as a result of aggregation and averaging, neural nets create high data dimensionality, and so on. End users care a lot more about results than they do about models. Unfortunately assessing result quality takes us right back to the models, as nonparametric models are only as good as the data used to train them (along with the type of model structure and associated parameters that were selected). But these models frequently hide information. Part of the magic of AI is that it finds stuff based on features that previously may not have been well understood. Unfortunately, the features models train on are frequently unclear. Assigning labels to pre-trained models can help mitigate some of this ambiguity -- e.g., "This model was trained with over 100,000 high-res color images of cats." These labels may be misleading though, as the model may contain feature biases that are not well understood -- e.g., "the training data is dominated by images of "well-fed, indoor cats from Japan."

In fairly short order, robots have begun taking over in the corporate world. This is nothing like the feared "singularity," that prophesied (if dubious) moment when machines become smarter than humans and then, to prove it, commence wiping us out. But robots are indeed infiltrating finance departments, some other functions, and operational areas in a number of industries. For the most part, robots are being deployed to automate repeatable, standardized, or logical tasks historically handled by people. In finance and accounting, think procure-to-pay, order-to-cash, and record-to-report processes.

Echo Dot is a hands-free, voice-controlled device that uses Alexa to play & control music (either on its own, or through a connected speaker/receiver), control smart home devices, provide information, read the news, set alarms, and more. If you're looking to buy them as gifts, or for different homes or rooms, Amazon will throw in a free one ( 50 value) when you buy 5, or two free ones when you buy 10 (a 100 value). To take advantage of this limited time offer, select 6 or 12 in the quantity dropdown and add to your Shopping Cart. Enter promo code DOT6PACK or DOT12PACK at checkout where you will see the discount applied. The new Amazon Echo Dot comes in black, and now also white.

Business tech companies are going to get an overdose of AI marketing. Your friendly neighborhood enterprise software provider has a window into much of your corporate data. And now it wants to provide you with artificial intelligence-fueled insights in what'll equate to a barrage of characters -- Watson, Einstein, Alexa, Siri, Cortana -- a lot of jargon and with any luck some actual automated digital processes. Rest assured you may wind up with the former before getting to the latter destination. There are some things that machines are simply better at doing than humans, but humans still have plenty going for them.

Over the past year, I've read countless "privacy guides" for Windows 10. Most are well-intentioned, but they invariably take a simplistic approach to privacy: Just turn off every switch in the Privacy section of the Settings app. If you do that, you're not understanding the privacy landscape, which encompasses far more than just those settings. Windows 10 is a mix of software and services. Microsoft's chief rivals, Google and Apple, are also blending services into their software, with the goal of making your life easier and making that software more reliable.

Salesforce Inc., a global computing company, announced on Sunday, an initiative that integrates Artificial Intelligence (AI) technology into its software for enterprises. Called Salesforce Einstein, the company came up with such an initiative to streamline the sales, services and marketing processes of a workplace. Artificial intelligence has the capabilities to function with human-like abilities and hence its implementation for CRM will make the sales and marketing tasks automatic. This new offering has a set of online AI services that will ease the sales tasks and improve productivity. It will help sales people to predict market behavior and focus on the relevant information.