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Wednesday, August 16, 2017

QR Codes in China

Have not been using or reading about the use of QR codes of late, interesting how they are being used in China. See also links to previous pieces on QR.    Some good, straight forward examples. Key too is how ready the customer base is willing to scan them.

16 Ways QR Codes are Being Used in China
by Connie Chan,   In Andreessen Horowitz Blog

We’ve talked a lot about the rise of QR codes in Asia, but they may now finally be moving from being a “joke” to being more widely adopted in other places as well. Simply put, QR codes let you hyperlink and bookmark the physical world. Just as UPC barcodes allow machine-readable scanning of data (e.g., price) on items in stores, QR codes are a barcode-like vector between online and offline information. And unlike NFC (near-field communication), which is used for reading smart cards, keycards, and contactless payments, QR codes can be easily accessed by any phone in the world that has a camera. They enable everything from online to offline (O2O) marketplaces, which are huge in China, to augmented reality.

Some of the more obvious use cases for them include things like adding a WeChat friend in real life (IRL); subscribing to a WeChat official account (often representing media, stores, people, and others); paying a street vendor or at a convenience store; connecting to wi-fi in a shop; getting additional content from a magazine article; and learning more about styling or the brand from a clothing label. But there are also a number of less-obvious (or not as well covered) uses in China, which I share below, because they show the range of what’s possible everywhere when QR codes disintermediate existing use cases… and enable new ones.  .... 

Tuesday, August 15, 2017

Assistants Using Wikipedia

A conversation at Wikipediocracy discusses how personal assistants like Alexa, Google Home and Siri use and attribute (or not)  knowledge from the Wikipedia.   Back to the complicated world of licenses and copyrights.   Was also re-introduced to the considerable undercurrent of WP authors complaining about how their work is used.

Autonomous Video for the Home

IEEE Spectrum on 'friendly'  home robotics.   Still awaiting some more detailed looks at its in home use. Continue to cover this, but given the cost will likely not dive in without some convincing.

Kuri Robot Brings Autonomous Video to a Home Near You
Mayfield Robotics improves its home robot, Kuri, adding track wheels, structural updates, and “Kuri Vision,” an autonomous home video program

Most home robots are designed primarily for convenience and function. Not Kuri. Silicon Valley startup Mayfield Robotics designed Kuri specifically to be an adorable home companion. And that means it needed to have one quality you won’t find in most robotic vacuums and other home bots: cuteness. 

Mayfield introduced Kuri earlier this year at the Consumer Electronics Show in Las Vegas. Since then, the Mayfield team has made several updates to the robot. The most significant one is the home video feature called “Kuri Vision,” which allows Kuri to take video autonomously.

To do that, Kuri has two high definition 1080p cameras, one behind each eye. These cameras take videos intermittently throughout the day, capturing candid moments. You can then review those clips through the app, which runs on iOS and Android, and choose which ones you like best. Then Kuri’s machine learning and image processing kicks in: Based on which images you favorite or delete, Kuri learns to take videos that you’ll like. .... " 

The Dataset that Transformed AI Research

As in the emergence of Big Data, it has been pointed out that the large amount of the right kind of data can make the difference.  And it has, opening an entire industry of image recognition and understanding, by sculpting algorithms to interpret them.  Re opening the idea of AI, that had slumbered since the 80s.

It's not about the Algorithm  

The data that transformed AI research—and possibly the world  In QZ by Dave Gershgorn   @davegershgorn

In 2006, Fei-Fei Li started ruminating on an idea.

Li, a newly-minted computer science professor at University of Illinois Urbana-Champaign, saw her colleagues across academia and the AI industry hammering away at the same concept: a better algorithm would make better decisions, regardless of the data.

But she realized a limitation to this approach—the best algorithm wouldn’t work well if the data it learned from didn’t reflect the real world.

Her solution: build a better dataset.

“We decided we wanted to do something that was completely historically unprecedented,” Li said, referring to a small team who would initially work with her. “We’re going to map out the entire world of objects.”

The resulting dataset was called ImageNet. Originally published in 2009 as a research poster stuck in the corner of a Miami Beach conference center, the dataset quickly evolved into an annual competition to see which algorithms could identify objects in the dataset’s images with the lowest error rate. Many see it as the catalyst for the AI boom the world is experiencing today. ... " 

Google View of AI: Intelligence and Scale

Via O'Reilly: 

Jeff Dean is a Google senior fellow in the Research Group, where he leads the Google Brain project. Here is a video (and slides) of a talk he gave, "Intelligent Systems with Large Scale Deep Learning." It's a decent intro to AI, with some hints about how Google expects AI to move forward. ....

Monday, August 14, 2017

Identifying Plant Species

Another example of using many images to train via AI.   Also describes the data needs for such a process, done via Deep Learning neural methods.

From the CACM: 
Digitizing plant specimens is opening up a whole new world for researchers looking to mine collections from around the world.

Computer algorithms trained on the images of thousands of preserved plants have learned to automatically identify species that have been pressed, dried and mounted on herbarium sheets, researchers report. ....  " 
Artificial Intelligence Identifies Plant Species for Science  In Nature 
" .... Bonnet's team had already made progress automating plant identification through the Pl@ntNet project. It has accumulated millions of images of fresh plants — typically taken in the field by people using its smartphone app to identify specimens.

Researchers trained similar algorithms on more than 260,000 scans of herbarium sheets, encompassing more than 1,000 species. The computer program eventually identified species with nearly 80% accuracy: the correct answer was within the algorithms’ top 5 picks 90% of the time. That, says Wilf, probably out-performs a human taxonomist by quite a bit. .... " 

Infinite Pool Tables

We actually used this idea for solving cleaning coverage problems.   A rare case where advanced topology math principles came into play in industry.  This was the kind of math that I always liked, not too abstractly symbolic, but visually interesting.

New Shapes Solve the Infinite Pool-Table Problem

NASA and Virtual and Augmented Realities

NASA has been known for experimenting in this space, I have played with a few of their published capabilities.  Here is an overview of their future plans.

NASA’S Next Spacecraft  may launch from virtual and augmented realities.     By Dyllan Furness in Digital Trends.  ..... "

Time Series Insights in Azure

Time Series Insights PREVIEW
Instantly explore and analyze time-series data in IoT solutions
Azure Time Series Insights is a fully managed analytics, storage, and visualization service that makes it simple to explore and analyze billions of IoT events simultaneously. It gives you a global view of your data, letting you quickly validate your IoT solution and avoid costly downtime to mission-critical devices by helping you discover hidden trends, spot anomalies, and conduct root-cause analyses in near real-time.  .... " 

(Start for free at link, taking a look at the root cause example, always a great analytics place to start, because it concerns everyone) 

Cortana Predicting Future Travel Plans

Been watching virtual assistants for some time.    The key appears to be getting as many as possible out there,  on many kinds of hardware,  keep them cheap and for attentive use with voice,  something you use every day,  but not as part of your phone and computer,  link it to a few key common entertainment functions (like music), open them to external skill development and keep coming out with new capabilities.  

Cortana has been available for some time now, but I remain unimpressed.  Note I am a satisfied Windows 10 user, always up to date, so it should be an easy sell. It should be linking to all my office functions, building intelligence into their use, but does not.  I spend more time shutting Cortana off than using it.  Still awaiting its implementation on a stand-alone on what looks to be a premium price  a Harman-Kardon device.

Now word is out that Cortana will predict your future travel plans.    Nice idea, but still not something I do every day,  will try it, but suggest you would be better to get it out in many users and developers hands.   Soon.

More of my coverage of personal assistants. 

Video Detecting Infection Patterns

Looking for patterns in healthcare using video that lead to infection.

Researchers use AI to monitor hospital staff hygiene
The technology could be used to reduce rates of hospital-acquired infections.

By Mallory Locklear,   @mallorylocklear  in Engadget. 

Hospital-acquired infections are a pesky problem and around one in 25 hospital patients have at least one healthcare-associated illness at any given time. To combat this issue, a research team based at Stanford University turned to depth cameras and computer vision to observe activity on hospital wards -- a system that could be used to track hygienic practices of hospital staff and visitors in order to spot behaviors that might contribute to the spread of infection. The work is being presented at the Machine Learning in Healthcare Conference later this week.  ... " 

Text Summarization

A good AI challenge that has useful applications.

An Algorithm Summarizes Lengthy Text Surprisingly Well
Training software to accurately sum up information in documents could have great impact in many fields, such as medicine, law, and scientific research.

by Will Knight  May 12, 2017  in Technology Review.

Who has time to read every article they see shared on Twitter or Facebook, or every document that’s relevant to their job? As information overload grows ever worse, computers may become our only hope for handling a growing deluge of documents. And it may become routine to rely on a machine to analyze and paraphrase articles, research papers, and other text for you.

An algorithm developed by researchers at Salesforce shows how computers may eventually take on the job of summarizing documents. It uses several machine-learning tricks to produce surprisingly coherent and accurate snippets of text from longer pieces. And while it isn’t yet as good as a person, it hints at how condensing text could eventually become automated .... " 

Sunday, August 13, 2017

Exoskeleton Controlled by Voice

Adding the voice to being reactive to movements is an interesting approach, another case of multi channel interaction and control.

This exoskeleton can be controlled using Amazon’s Alexa
‘Alexa, let’s go for a walk’     by James Vincent   @jjvincent

Amazon’s Alexa is available on a lot of devices, from lamps to alarm clocks to fridges. But robotics company Bionik Laboratories says it’s the first to add the digital assistant to a powered exoskeleton. The company has integrated Alexa with its lower-body Arke exoskeleton, allowing users to give voice commands like “Alexa, I’m ready to stand” or “Alexa, take a step.”

Movement of the Arke, which is currently in clinical development, is usually controlled by an app on a tablet or by reacting automatically to users’ movements. Sensors in the exoskeleton detect when the wearer shifts their weight, activating the motors in the backpack that help the individual move. For Bionik, adding Alexa can help individuals going through rehabilitation get familiar with these actions.   ... "

On a Bias about First Impressions

A first impression knowledge Bias?

Why our brains lead us astray when we take things at face value   Article by Diana Gitig 
A new book looks at how we overestimate what we can tell from a first impression.

" ... Professor Alexander Todorov’s new book, Face Value: The Irresistible Influence of First Impressions, is about much more than 19th-century pseudoscience. It’s about first impressions more generally. We all form them instantly—within 30-40 milliseconds, before we can consciously register even seeing a face. And we start exceptionally early on, probably at around seven months of age. We also seem to agree on these impressions, which makes the physiognomists’ promise so appealing.  .... " 

Addressing the Analogy Gap

Reminiscent of using humans as a peripheral, here determining high level relationships, then having the deep learning sort out the lower level patterns.  Points to Mechanical Turk, which we used this way.  At what point are the results general?  The comment about scale is key.  Also the mapping involved, very useful for generalizing and testing.

Crowdsourcing may have just helped close the "analogy gap" for computers    It's vexed computer scientists for decades, but a huge roadblock for true AI is falling    By Greg Nichols for Robotics

Researchers at Carnegie Mellon University (CMU) and the Hebrew University of Jerusalem in Israel have used crowdsourcing to teach computers to generate analogies so they can mine datasets to address new challenges by repurposing old concepts. "After decades of attempts, this is the first time that anyone has gained traction computationally on the analogy problem at scale," says CMU professor Aniket Kittur. The researchers hired participants via Amazon Mechanical Turk, tasking them to look through products on an innovation website and find analogous products from the same source. The participants noted which words caused them to link disparate products, mapping each pathway. Computers with deep-learning algorithms used these insights to analyze additional product descriptions and find new analogies. The researchers say this strategy can be used to customize computer programs to identify analogies between patent applications and literature on global problems.  ... " 

China and AI

In the NYT, word on China investments in AI: 

" ... China has laid out a development plan to become the world leader in artificial intelligence (AI) by 2030, with the goal of surpassing its rivals technologically and establishing a domestic industry worth nearly $150 billion. The policy, released by the State Council, is a statement of intent from the upper levels of China's government that the country will be investing heavily to ensure its companies, government, and military jump to the forefront of AI technology. The plan comes while China prepares a multibillion-dollar national investment initiative to support "moonshot" projects, startups, and academic research in AI.  ... "

Saturday, August 12, 2017

IFTTT and Honeywell

Continue to be impressed about how companies are working with IFTTT data streams, most recently brought to my attention:  Honeywell.  Plus other methods using the IFTTT Open Platform.  I have several examples in operation.

From our partners: 
“IFTTT’s network of partners is so extensive that that one connection allows us to get a lot of connections to third-party devices… IFTTT gave us a way to get there very quickly and very inexpensively.”          Scott Harkins   VP, Honeywell Connected Home

Video

Multivariate Regression

In DSC, a good piece explaining multivariate regression.  Not very technical, addresses both the data and the results.  Every manager should understand this simple approach.   A very common kind of problem you run into.   A good thing to walk through with decision makers and their real data.   Also leads you naturally to the next question, how do I determine which variables create the best predictive model?   The next step.

Bikes Existing Among Cars

Troublesome thought that bicycles might need to become so complex to exist in an ecosystem with automobiles.

Bikes May Have to Talk to Self-Driving Cars for Safety's Sake     by Margaret J. Krauss

Researchers envision bicycles communicating with autonomous vehicles so the latter can predict cyclists' movements. Waymo's self-driving autos have honed their predictive abilities over many simulated and actual driven miles, notes Waymo's Nathaniel Fairfield. Waymo's vehicles are programmed to pass bikes in compliance with state laws, or to wait if such action is impossible. Carnegie Mellon University professor Anthony Rowe wants bikes to feed data to cars. "We're trying to...put as much instrumentation on a bike as we can to see if we can predict how it's going to move in the future, so that it could, for example, signal a collision-warning system on a car," Rowe says. His team wants to collect as much information as possible to determine the precise and constant position of a bike in the world, and then determine the least amount of data a car requires from a cyclist for it to trigger an automatic braking system .... " 

Handbook of Neural Computation

Handbook of Neural Computation - 1st Edition - ISBN: 9780128113189, 9780128113196Below book looks good, but very pricey.    Consider a free version via MIT, also being continually updated, don't have a copy to compare its coverage.    In general today, a book on 'Deep Learning' would cover similar topics than one on 'Neural Computing',  but that is not necessarily implied by the titles.   Artificial neurons do learn by computing,  but the neural computing by itself does not mean learning, yet likely does today.

Handbook of Neural Computation 1st Edition,   Elsevier,2017
Posted by Sanjiban Sekhar Roy 

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. .... " 

Debating Statistical Significance

A considerable look, both technical and non-technical about statistical significance. Have it has been used, and how that is being re-considered.    The original title says this is a nerdy debate, I disagree, it is very important.  Having replicable significance is essential.

The case for, and against, redefining “statistical significance.” 
Updated by Brian Resnick

 There’s a huge debate going on in social science right now. The question is simple, and strikes near the heart of all research: What counts as solid evidence?

The answer matters because many disciplines are currently in the midst of a “replication crisis” where even textbook studies aren’t holding up against rigorous retesting. The list includes: ego depletion, the idea that willpower is a finite resource; the facial feedback hypothesis, which suggested if we activate muscles used in smiling, we become happier; and many more.

Scientists are now figuring out how to right the ship, to ensure scientific studies published today won’t be laughed at in a few years.

One of the thorniest issues with this question is statistical significance. It’s one of the most influential metrics to determine whether a result is published in a scientific journal.  .... " 

Telepresence Robots

These robots should be called 'minimal presence portable robotics',  we looked at them to test the idea of having someone who was very remote introduced to a team in a unique way.   They have lots of problems.  We discovered most of these in our tests.  The article is quite good and complete, covering several devices, and exposing many of their issues.

In particular that the remote person has to be trained on the device and wastes most of their time just navigating and engaging.  And people don't engage well with them, end up just hiding.  Unless there is a very clear need to move about, like oberserving some detailed experience,  like a store layout, you are better off just having a stationary video camera somewhere.   This might seem like a cute idea, but test carefully before you buy a fleet.

The Best Telepresence Robot
After spending 20 hours researching telepresence robots and testing two of the most promising models in office and home settings, we don’t think these devices are ready for prime time. But if you want a telepresence robot to give remote employees a physical presence in your office, the Suitable Technologies Beam Enhanced is the only bot that’s reliable and user-friendly enough to consider. .... " 

Friday, August 11, 2017

Data as Asset: Deriving Knowledge from Data

Good thought, and a natural way to lead toward value based intelligence.  In O'Reilly.

A DevOps approach to data management
A multi-model approach to transforming data from a liability to an asset.

By Adam Michael Wood 

Download the free O’Reilly report "Defining Data-Driven Software Development," by Eric Laquer.
Deriving knowledge from data has become a key competency for many—if not most—businesses. With the right data, and the right tools to handle it, businesses can gain keen insights into a variety of metrics, including operations, customer activity, and employee productivity. .... " 

Making AI Explain Itself

Back to our maintenance problem. Unless you can explain a result, it is hard to maintain it under changing context.   Trust too can be lost if the methods are indistinguishable from magic.  

Inside DARPA's Push to Make Artificial Intelligence Explain Itself 
The Wall Street Journal, Sara Castellanos; Steven Norton

The U.S. Defense Advanced Research Projects Agency (DAPRA) is coordinating a project in which 100 researchers at more than 30 universities and private institutions are seeking to create deep-learning artificial intelligences (AIs) that can explain their decision-making to humans. DARPA program manager David Gunning says this advance is crucial as AI becomes more deeply entrenched in everyday life and a greater level of trust between humans and machines must be nurtured. Participants have spent the project's first phase working on focus areas of their choosing, and in the second phase each institution will be assigned one of two "challenge problems" to address. The challenges will either involve using AI to classify events in multimedia, or training a simulated autonomous system to conduct a series of missions. The final result will be a set of machine-learning methods and user interfaces that public- or private-sector groups could use to construct their own explainable AI systems.  ... " 

Platt Research Institute: Journal of Retail Analytics

Have begun to follow, details for sign-in and article download at the link:

Journal of Retail Analytics

PRI’s Journal of Retail Analytics is a comprehensive quarterly publication that includes news and case studies regarding retail analytics, digital customer-facing technologies, and related topics. The Journal provides a snapshot of the economy as it impacts retailers and consumers. In addition, the Journal examines trends in the use of retail analytics and details developments in the digital communications industry. Authors include industry thought leaders and leading academics, among others.

PRI’s offices, projects, and extensive contacts in North America and Europe enable the firm to report on cutting-edge global events. Furthermore, the Journal features distinguished guest columnists, thought-provoking case studies, network profiles, and more.

If you are interested in submitting an article for publication in the Journal, please review the current Submission Guidelines.

The most recent edition of the Journal of Retail Analytics is available for free download below. Articles in the 2Q 2017 issue include:

Audio Management and Delivery Strategies for Retail Environments by Reto Brader, Vice President, Sales and Marketing, Barix

Building a Relationship That Online Shopping Can’t Replace by Richard Ventura, Vice President of Product Marketing and Solutions, NEC Display Solutions

Comparison of Traditional Predictive Analytics Tools Versus Artificial Intelligence-Based Solutions by Gary Saarenvirta, CEO, Daisy Intelligence

How Online Reviews Influence Sales by Spiegel Research Center, Northwestern University
Strategic Data Management in Retail Labeling Systems by Elizabeth Sinclair, Vertical Marketing Manager, Seagull Scientific

The Apple Store versus the Microsoft Store: Using Retail Analytics to Measure Customer Behavior Case Study — Part I by D. Anthony Miles, Founder and CEO, Miles Development Industries Corporation

The Role of Emerging Technologies in Retail: A Retail Roundtable   ... " 

The AI Nose

Have followed the idea of an 'Artificial Nose' for decades, we were first interested in using it as a automatic way to to evaluate and duplicate coffee blends and their components in the supply chain.  

Also, the argument was if we could digitize  such analyses, we could use that to deliver scents where we wanted to.  We did that in places like the retail store shelf and even the store aisle.   The solutions were never completely satisfactory.   The method here claims to use deep learning.  Continue to follow related tech, see the scent tag below.

An AI ‘nose’ can remember different scents
It can also detect potentially silent but deadly gas mixtures.    by Timothy J. Seppala, @timseppala  .... " 

Working in a Digitally Disrupted World

In McKinsey:

Do American workers feel they can ‘make it’?
Whether people in the United States believe they can thrive economically in a digitally disrupted world depends strongly on the amount of education they’ve attained, according to a new survey. ... " 

Thursday, August 10, 2017

How AI is Already Changing Business


An HBR Ideacast ...

How AI Is Already Changing Business

Erik Brynjolfsson, MIT Sloan School professor, explains how rapid advances in machine learning are presenting new opportunities for businesses. He breaks down how the technology works and what it can and can’t do (yet). He also discusses the potential impact of AI on the economy, how workforces will interact with it in the future, and suggests managers start experimenting now. Brynjolfsson is the co-author, with Andrew McAfee, of the HBR Big Idea article, “The Business of Artificial Intelligence.” They’re also the co-authors of the new book, Machine, Platform, Crowd: Harnessing Our Digital Future.

 Welcome to the HBR IdeaCast from Harvard Business Review. I’m Sarah Green Carmichael.
It’s a pretty sad photo when you look at it. A robot, just over a meter tall and shaped kind of like a pudgy rocket ship, laying on its side in a shallow pool in the courtyard of a Washington, D.C. office building. Workers – human ones – stand around, trying to figure out how to rescue it.

The security robot had just been on the job for a few days when the mishap occurred. One entrepreneur who works in the office complex wrote: “We were promised flying cars. Instead we got suicidal robots.”

For many people online, the snapshot symbolized something about the autonomous future that awaits. Robots are coming, and computers can do all kinds of new work for us. Cars can drive themselves. For some people this is exciting, but there is also clearly fear out there about dystopia. Tesla CEO Elon Musk calls artificial intelligence an existential threat.

But our guest on the show today is cautiously optimistic. He’s been watching how businesses are using artificial intelligence and how advances in machine learning will change how we work. Erik Brynjolfsson teaches at MIT Sloan School and runs the MIT Initiative on the Digital Economy. And he’s the co-author with Andrew McAfee of the new HBR article, “The Business of Artificial Intelligence.”

Erik, thanks for talking with the HBR IdeaCast.  ....    "

Marketing and AI

How will marketing adapt?
With AI, marketing is needed but marketers might not be
By Christine Coudert on SAS Voices ... " 

Robot Restocking

Includes a good expert discussion, usually the best parts of these pieces.   Also an approach we did much experimenting with, starting with Blackberry devices.

Can robots keep shelves stocked at Schnucks?  in Retailwire,  by George Anderson

Schnuck Markets, the 100-store supermarket chain based in St. Louis, announced it will run a six-week pilot program at three locations to test robots that will move up and down store aisles to make sure shelves remain properly stocked. The robots will also scan shelves to make sure that each item is in its proper place, aligned with the correct shelf tag.


The robots, which will be deployed three times a day (morning, afternoon and night), will send real-time information to store associates, helping them keep shelves stocked for customers. Each unit, named Tally by the manufacturer, Simbe Robotics, stands 38 inches high and weighs about 30 pounds. The devices use sensors to navigate around the store. The St. Louis Post-Dispatch reports that the units are programmed to avoid busy aisles and stop moving if a customer approaches.


Dave Steck, vice president of IT – infrastructure at Schnucks, said the data the robots collect will also be shared with vendors to help them improve their supply levels to stores. The initial emphasis of the pilot is to see if the chain can improve its stock positions through automation. Later, the technology may be used to reduce pricing errors and address other issues.  .... " 

Facebook Translates with Neural Nets

Another example  of how the power of this tech is expanding.  Some interesting details here.

Two versions of a Facebook post Facebook Translations Now Rely Entirely on Neural Networks in SiliconANGLE  by Eric David

" ... Facebook on Wednesday announced its translations are now wholly dependent on state-of-the-art machine-learning neural networks. A team of Facebook researchers says these networks manage more than 2,000 translation directions and 4.5 billion translations daily, generating more accurate translations than Facebook's previous system, which used phrase-based machine translation models. Neural machine translation gauges the complete content of a message together, which is more resource-intensive than phrase-based translation but typically results in a more fluent translation. Facebook also says neural machine translation can handle unknown or misspelled words with greater proficiency, as it can examine contextual clues to determine a word's intended meaning. Facebook thinks convolutional neural networks (CNN) can realize the same accuracy in translation as recurrent neural networks, but significantly faster. In May, the company announced that its CNN-based system was nine times faster than existing networks, and Facebook researchers note CNNs are a better fit for the newest machine-learning hardware. ... " 

Content Marketing in the Era of Voice-Controlled Devices

A number of interesting retail marketing examples are shown in this medium.

Content Marketing in the Era of Voice-Controlled Devices  in Flipboard
By Dawn Papandrea/Aug 9, 2017
Via John Frazier   BBA News - BizBuzz America

Voice-controlled devices are today’s hottest technology. 
Amazon Alexa now has more than 15,000 skills (which can range from basic functions to more robust experiences, akin to apps.) And each day, we’re hearing about new capabilities or big announcements for similar devices. Apple, for one, will release a Siri-based HomePod this fall. 

As a content marketer, you should be keeping your ears (and eyes) open to these new audio channels to ensure that your brand voice is heard. 

“If a brand doesn’t have a presence on voice platforms, then they are literally silent when a consumer asks to engage with them,” says Bret Kinsella, Editor and Publisher of Voicebot.ai, a publication about the voice and AI revolution.  

Are you ready to be an early adopter and develop audio content to expand your reach? If so, listen up: Here’s what you need to know about the voice-controlled device space.  .... "