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.

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.

This approach tends to teach to machines what humans like to listen to, without understanding what is recommended. It is a deaf approach that's trying to mimic the record dealer's behavior. It's not a DJ that builds a listening experience. It doesn't capture what the soundtrack of your life is. Collaborative filtering also tends to make predictable and familiar recommendations. This favors the rise of a popular artist dictatorship, harmful for the beautiful versatility of music.

For decades, futurists and science fiction writers predicted that smart machines would someday rival the intelligence of humans. Now, their forecasts seem to be coming true. Artificial intelligence, or AI, already exceeds human capability in certain fields. Machines can send and receive signals and analyze vast quantities of data faster than humans. They have learned to drive cars, manage stock portfolios and, through personal assistants such as Siri and Alexa, talk to us.

What's all the fuss about the voice-activated home speaker that Amazon is due to release in the UK and Germany in late September? This gadget has been available in the US for over a year and has proven a minor hit, with sales estimates between 1.6m and 3m. But these figures belie the potential impact this kind of artificial intelligence device could have on our lives in the near future. Echo doesn't just let you switch on your music by voice command. It's the first of what will be several types of smart home appliances that work beyond simple tasks like playing music or turning on a light. It uses an artificial intelligence assistant app called Alexa to allow users to access the information and services of the internet and control personal organisation tools.

Salesforce.com Inc. CRM -0.95 % said it would embed artificial intelligence technology into its software for salespeople, making it the latest in a gaggle of companies racing to enhance workplace tools with human-like abilities. The company will demonstrate the new software at its annual user conference next month in San Francisco. Called Einstein, the new offering is a set of online AI services designed to automate tasks, predict behavior and spotlight relevant information. Einstein is the latest in a long line of AI products branded with human-sounding names including Alexa from Amazon.com Inc., Cortana from Microsoft Corp. MSFT 0.10 % Siri from Apple Inc., and Watson from International Business Machines Corp. IBM -1.17 % IBM and Microsoft, in particular, have spearheaded a push to offer AI services aimed at corporate users.

SAN FRANCISCO - In the consumer universe, artificial intelligence is best known as a nice-to-have if stealthy feature that can suggest movies or book rides. But AI's greater worth could well be in the money-making enterprise arena, where sales, service and marketing initiatives stand to be streamlined by the data-crunching deductive power of machine learning. That's certainly the bet customer relationship management giant Salesforce is making by unveiling Einstein, the no-brainer name given to a suite of advanced AI capabilities. With Einstein, salespeople can focus on leads that statistically show the most promise of becoming clients, and customer service reps may be better prepared to answer a rainbow of consumer queries. "The strongest aspect of Einstein is that it is deeply embedded in the platform, it's just working automatically," says Salesforce CEO Marc Benioff, whose company officially rolled out the base product Sunday.

Virtual reality may be generating most of the buzz today, but another major tech shift looms much closer on the horizon: machine learning. The technology has already made inroads with the public through platforms such as Amazon's Echo and Google's Deep Dream Generator. But its influence will extend beyond voice-controlled speakers and AI-enhanced art, effecting a sea of change for businesses of all sizes. It will be a few years before we witness machine learning's breakthrough moment, but it's coming -- and it will change everything. Humans could be incredibly effective given endless timelines, budget, and energy.