Don’t discount the game-changing power of the morphing “TV” when coupled with AI, NLP, and blockchain-based technologies! [Christian]

From DSC:

Don’t discount the game-changing power of the morphing “TV” when coupled with artificial intelligence (AI), natural language processing (NLP), and blockchain-based technologies!

When I saw the article below, I couldn’t help but wonder what (we currently know of as) “TVs” will morph into and what functionalities they will be able to provide to us in the not-too-distant future…?

For example, the article mentions that Seiki, Westinghouse, and Element will be offering TVs that can not only access Alexa — a personal assistant from Amazon which uses artificial intelligence — but will also be able to provide access to over 7,000 apps and games via the Amazon Fire TV Store.

Some of the questions that come to my mind:

  • Why can’t there be more educationally-related games and apps available on this type of platform?
  • Why can’t the results of the assessments taken on these apps get fed into cloud-based learner profiles that capture one’s lifelong learning? (#blockchain)
  • When will potential employers start asking for access to such web-based learner profiles?
  • Will tvOS and similar operating systems expand to provide blockchain-based technologies as well as the types of functionality we get from our current set of CMSs/LMSs?
  • Will this type of setup become a major outlet for competency-based education as well as for corporate training-related programs?
  • Will augmented reality (AR), virtual reality (VR), and mixed reality (MR) capabilities come with our near future “TVs”?
  • Will virtual tutoring be one of the available apps/channels?
  • Will the microphone and the wide angle, HD camera on the “TV” be able to be disconnected from the Internet for security reasons? (i.e., to be sure no hacker is eavesdropping in on their private lives)

 

Forget a streaming stick: These 4K TVs come with Amazon Fire TV inside — from techradar.com by Nick Pino

Excerpt:

The TVs will not only have access to Alexa via a microphone-equipped remote but, more importantly, will have access to the over 7,000 apps and games available on the Amazon Fire TV Store – a huge boon considering that most of these Smart TVs usually include, at max, a few dozen apps.

 

 

 

 

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 


Addendums


 

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider.

.

  • Once thought to be a fad, MOOCs showed staying power in 2016 — from educationdive.com
    Dive Brief:

    • EdSurge profiles the growth of massive online open courses in 2016, which attracted more than 58 million students in over 700 colleges and universities last year.
    • The top three MOOC providers — Coursera, Udacity and EdX — collectively grossed more than $100 million last year, as much of the content provided on these platforms shifted from free to paywall guarded materials.
    • Many MOOCs have moved to offering credentialing programs or nanodegree offerings to increase their value in industrial marketplaces.
 

Wall Street Jobs Won’t Be Spared from Automation — from hbr.stfi.re by Thomas H. Davenport

Excerpt:

Some conference participants were concerned that this beleaguered region might grow. In fact, one attendee — an old friend who strategizes about technology for a big New York bank — commented that perhaps Wall Street would become “the new Rust Belt.” His concern was that automation of the finance industry would hollow out jobs in that field in the same way that robotics and other technologies have reduced manufacturing employment.

This is a sobering prospect, but there is plenty of evidence that it’s a real possibility. Key aspects of the finance industry have already been automated to a substantial degree. Jobs in the New York finance field have been declining for several years. According to data from research firm Coalition Ltd., more than 10,000 “front-office producer” jobs have been lost within the top 10 banks since 2011. Coalition also suggests that global fixed-income headcount has fallen 31% since 2011.

 

 

Predictions for 2017: How Will the Digital World of Work Transform HR? — from hrdailyadvisor.blr.com

Excerpt:

According to a new report, organizations are moving away from hierarchies, focusing on improving the employee experience, redesigning training, and reinventing the role of HR.

Business and HR leaders should rethink almost all of their management and HR practices as the proliferation of digital technologies transform the way organizations work, according to predictions for 2017 from Bersin by Deloitte, Deloitte Consulting LLP.

This year’s report includes 11 predictions about rapid technological, structural, and cultural changes that will reshape the world of work, including management, HR, and the markets for HR and workplace technology.

 

 

Artificial intelligence has a big year ahead — from cnet.com by Stepehn Shankland
In 2017, AI won’t just be for the nerdy companies. Machine learning can help with mortgage applications and bridge safety, too.

Excerpt:

Get ready for AI to show up where you’d least expect it.

In 2016, tech companies like Google, Facebook, Apple and Microsoft launched dozens of products and services powered by artificial intelligence. Next year will be all about the rest of the business world embracing AI.

Artificial intelligence is a 60-year-old term, and its promise has long seemed like it was forever over the horizon. But new hardware, software, services and expertise means it’s finally real — even though companies will still need plenty of human brain power to get it working.

 

 

AI was one of the hottest trends in tech this year, and it’s only poised to get bigger. You’ve already brushed up against AI: It screens out spam, organizes your digital photos and transcribes your spoken text messages. In 2017, it will spread beyond digital doodads to mainstream businesses.

 

 

 

2017 Design Trends: Predictions from Top Creatives — howdesign.com by Callie Budrick

Excerpt:

The design world has seen its own changes and updates as well. And as we know, change is the only constant. We’ve asked some of the top creatives to share what 2017 design trends they think will be headed our way.

 

 

MapR Executive Chairman and Founder John Schroeder Identifies 6 Big Data Predictions for 2017 — from businesswire.com

Excerpt:

SAN JOSE, Calif.–(BUSINESS WIRE)–The market has evolved from technologists looking to learn and understand new big data technologies to customers who want to learn about new projects, new companies and most importantly, how organizations are actually benefitting from the technology. According to John Schroeder, executive chairman and founder of MapR Technologies, Inc., the acceleration in big data deployments has shifted the focus to the value of the data. John has crystallized his view of market trends into these six major predictions for 2017…

 

 

The Most Exciting Medical Technologies of 2017 — from medicalfuturist.com

Excerpt:

2016 was a rich year for medical technology. Virtual Reality. Augmented Reality. Smart algorithms analysing wearable data. Amazing technologies arrived in our lives and on the market almost every day. And it will not stop in the coming year. The role of a futurist is certainly not making bold predictions about the future. No such big bet has taken humanity forward. Instead, our job is constantly analysing the trends shaping the future and trying to build bridges between them and what we have today. Still, people expect me to come up with predictions about medical technologies every year, and thus here they are.

 

 

2017 Predictions For AI, Big Data, IoT, Cybersecurity, And Jobs From Senior Tech Executives — from forbes.com by Gil Press

Excerpt:

Artificial intelligence (and machine/deep learning) is the hottest trend, eclipsing, but building on, the accumulated hype for the previous “new big thing,” big data. The new catalyst for the data explosion is the Internet of Things, bringing with it new cybersecurity vulnerabilities. The rapid fluctuations in the relative temperature of these trends also create new dislocations and opportunities in the tech job market.

The hottest segment of the hottest trend—artificial intelligence—is the market for chatbots. “The movement towards conversational interfaces will accelerate,” says Stuart Frankel, CEO, Narrative Science. “The recent, combined efforts of a number of innovative tech giants point to a coming year when interacting with technology through conversation becomes the norm. Are conversational interfaces really a big deal? They’re game-changing. Since the advent of computers, we have been forced to speak the language of computers in order to communicate with them and now we’re teaching them to communicate in our language.”

 

 

Allen Institute for AI Eyes the Future of Scientific Search — from wired.com by Cade Metz

Excerpt:

Google changed the world with its PageRank algorithm, creating a new kind of internet search engine that could instantly sift through the world’s online information and, in many cases, show us just what we wanted to see. But that was a long time ago. As the volume of online documents continues to increase, we need still newer ways of finding what we want.

That’s why Google is now running its search engine with help from machine learning, augmenting its predetermined search rules with deep neural networks that can learn to identify the best search results by analyzing vast amounts of existing search data. And it’s not just Google. Microsoft is pushing its Bing search engine in the same direction, and so are others beyond the biggest names in tech.

 

 

3 Forces Shaping Ed Tech in 2017 — from campustechnology.com by Dian Schaffhauser
Ovum’s latest report examines the key trends that are expected to impact higher education in the new year.

Excerpts:

  1. Institutions Will Support the Use of More Innovative Tech in Teaching and Learning
  2. Schools Will Leverage Technology for Improving the Student Experience
  3. The Next-Generation IT Strategy Will Focus More on IT Agility

 

 

Virtual Reality, AI Top Predictions for 2017 — from techzone360.com by Alicia Young

Excerpt:

We’ve seen a lot of exciting new innovations take place over the course of 2016. This year has introduced interesting new uses for virtual reality—like using VR to help burn victims in hospitals mentally escape from the pain during procedures—and even saw the world’s first revolutionary augmented reality game in the form of Pokémon Go. The iPhone 7 was also introduced, leaving millions of people uncertain of their feelings regarding Apple, while Samsung loyalists just prayed that their smartphones would stay in one piece.

Undoubtedly, there have been quite a few ups and downs in technology over the past year. With any luck, 2017 will provide us with even more new innovations and advancements in tech. But what exactly do we have to look forward to? TMC recently caught up with Jordan Edelson, CEO of Appetizer Mobile, to discuss his thoughts on 2016 and his predictions for what’s to come in the future. You can find the entire exchange below.

 

 

 

The Fourth Transformation: Augmented Reality & Artificial Intelligence — from forbes.com by John Koetsier

Excerpt:

Since then, we’ve seen three transformations. The latest, augmented reality plus artificial intelligence, will change more than the previous three combined.  At least, that’s what tech evangelist Robert Scoble and author Shel Israel say in their new book: The Fourth Transformation: How Augmented Reality & Artificial Intelligence Will Change Everything.

 

 

 

15 Virtual Reality Trends We’re Predicting for 2017 — from appreal-vr.com by Yariv Levski

 

Excerpt:

2016 is fast drawing to a close. And while many will be glad to see the back of it, for those of us who work and play with Virtual Reality, it has been a most exciting year. By the time the bells ring out signalling the start of a new year, the total number of VR users will exceed 43 million. This is a market on the move, projected to be worth $30bn by 2020. If it’s to meet that valuation, then we believe 2017 will be an incredibly important year in the lifecycle of VR hardware and software development. VR will be enjoyed by an increasingly mainstream audience very soon, and here we take a quick look at some of the trends we expect to develop over the next 12 months for that to happen.

 

 

Our Tech Predictions for 2017 — from medium.com

Excerpts:

Every December, we take a look back at big ideas from the past twelve months that promise to gain momentum in the new year. With more than eleven thousand projects launched between our Design and Tech categories in 2016, we have a nice sample to draw from. More importantly, we have a community of forward-thinking backers who help creators figure out which versions of the future to pursue. Here are some of the emerging trends we expect to see more of in 2017.

Everyday artificial intelligence
Whether chatting with a device as if it’s a virtual assistant strikes you as a sci-fi dream come true or a dystopian nightmare, we’re going to see an increasing number of products that use voice-controlled artificial intelligence interfaces to fit into users’ lives more seamlessly. Among the projects leading the way in this arena are Vi, wireless earphones that double as a personal trainer; Bonjour, an alarm clock that wakes you up with a personalized daily briefing; and Dashbot, a talking car accessory that recalls Kit, David Hasselhoff’s buddy from Knight Rider. One of the factors driving this talking AI boom is the emergence of platforms like Microsoft’s Cognitive Service, Amazon’s Alexa, and Google’s Speech API, which allow product developers to focus on user experience rather than low-level speech processing. For the DIY set, Seeed’s ReSpeaker offers a turnkey devkit for working with these services, and we’ll surely see more tools for integrating AI voice interfaces into all manner of products.

 

 

3 reasons 2017 is the year to develop a company chatbot — from thenextweb.com by Ellie Martin

Excerpt:

During Microsoft’s Build Conference earlier this year, CEO Satya Nadella delivered the three-hour keynote address, in which he highlighted his belief that the future of technology lies in human language. In this new wave of technology, conversation is the new interface, and “bots are the new apps.” While not as flashy as virtual reality nor as immediately practical as 3D printing, chatbots are nevertheless gaining major traction this year, with support coming from across the entire tech industry. The big tech enterprises are all entering the chatbot space, and many startups are too.

 

Out with the apps, in with the chatbots. The reason for the attention is simple: The power of the natural language processor, software that processes and parses human language, creating a simple and universal means of interacting with technology.

 

 

 

When kids toys come to life: How AR is transforming play — from thememo.com by Kitty Knowles
We asked three entrepreneurs to explain why AR toys are going to be the next big trend.

 

 

 

 

 

By 2030, this is what computers will be able to do — from medium.com by the World Economic Forum

Excerpt:

Developments in computing are driving the transformation of entire systems of production, management, and governance. In this interview Justine Cassell, Associate Dean, Technology, Strategy and Impact, at the School of Computer Science, Carnegie Mellon University, and co-chair of the Global Future Council on Computing, says we must ensure that these developments benefit all society, not just the wealthy or those participating in the “new economy”.

 

 

 

 

 

Artificial Intelligence will drive innovation and development in 2017, says Ericsson — from tech.firstpost.com

Excerpt:

Artificial Intelligence (AI) is an important development and consumers globally will see it playing a much more prominent role — both in society and at work — next year, a new report said on Tuesday. Ericsson ConsumerLab, in its annual trend report titled “The 10 Hot Consumer Trends for 2017 and beyond”, said that 35 percent of advanced internet users want an AI advisor at work and one in four would like AI as their manager.At the same time, almost half of the respondents were concerned that AI robots will soon make a lot of people lose their jobs.

 

 

21 technology tipping points we will reach by 2030 — from businessinsider.com by Cadie Thompson

Excerpt:

From driverless cars to robotic workers, the future is going to be here before you know it. Many emerging technologies you hear about today will reach a tipping point by 2025, according to a report from The World Economic Forum’s Global Agenda Council on the Future of Software & Society. The council surveyed more than 800 executives and experts from the technology sector to share their respective timelines for when technologies would become mainstream. From the survey results, the council identified 21 defining moments, all of which they predict will occur by 2030. Here’s a look at the technological shifts you can expect during the next 14 years.
…
The first robotic pharmacist will arrive in the US 2021.

 

 

 

 

 

 

 

The Chatbot Revolution: Rise of the Conversational User Interface — from tech.economictimes.indiatimes.com by Aakrit Vaish

Excerpt:

At Haptik, we have now been working on chatbots for over 3 years, and this post will attempt to make some sense of where we are as an industry.

 

 

AI, VR, Chatbots to Take Off in 2017 Microsoft Researchers Predict — from eweek.com by Pedro Hernandez
Prominent Microsoft researchers share their tech predictions for an AI-enabled future that blurs the line between physical and virtual experiences.

Excerpt:

A new year is quickly approaching and Microsoft Research is offering a glimpse at what the tech scene has in store for 2017 along with some hints at the Redmond, Wash., tech giant’s own priorities for the coming year. This year, the company gathered prominent women researchers to share their thoughts on what to expect next year. Surprising nobody’s who’s been following Microsoft’s software and cloud computing strategy of late, the company is betting big on artificial intelligence (AI).

 

 

11 IoT Predictions for 2017 — from ioti.com by Brian Buntz

Excerpt:

It’s still early days for the Internet of Things. As recently as 2014, 87 percent of consumers had never heard of the technology, according to Accenture. In 2016, and 19% of business and government professionals reported that they had never heard of the Internet of Things while 18% were only vaguely familiar with it, according to research from the Internet of Things Institute. Although the technology is getting the most traction in the industrial space, the most promising use cases for the technology are just starting to come to light. To get a sense of what to expect as we head into 2017, we spoke with Stanford lecturer and IoT author Timothy Chou, Ph.D.; Thulium.co CEO Tamara McCleary; industry observer and influencer Evan Kirstel; and Sandy Carter, CEO and founder of Silicon-Blitz.

 

 

 

 


Addendums:


 

 

 

New journal Science Robotics is established to chronicle the rise of the robots — from techcrunch.com by Devin Coldewey

Excerpt:

Robots have been a major focus in the technology world for decades and decades, but they and basic science, and for that matter everyday life, have largely been non-overlapping magisteria. That’s changed over the last few years, as robotics and every other field have come to inform and improve each other, and robots have begun to infiltrate and affect our lives in countless ways. So the only surprise in the news that the prestigious journal group Science has established a discrete Robotics imprint is that they didn’t do it earlier.

Editor Guang-Zhong Yang and president of the National Academy of Sciences Marcia McNutt introduce the journal:

In a mere 50 years, robots have gone from being a topic of science fiction to becoming an integral part of modern society. They now are ubiquitous on factory floors, build complex deep-sea installations, explore icy worlds beyond the reach of humans, and assist in precision surgeries… With this growth, the research community that is engaged in robotics has expanded globally. To help meet the need to communicate discoveries across all domains of robotics research, we are proud to announce that Science Robotics is open for submissions.

Today brought the inaugural issue of Science Robotics, Vol.1 Issue 1, and it’s a whopper. Despite having only a handful of articles, each is deeply interesting and shows off a different aspect of the robotics research world — though by no means do these few articles hit all the major regions of the field.

 

 

See also:

 

Excerpt:

Science Robotics has been launched to cover the most important advances in the development and application of robots, with interest in hardware and software as well as social interactions and implications.

From molecular machines to large-scale systems, from outer space to deep-sea exploration, robots have become ubiquitous, and their impact on our lives and society is growing at an accelerating pace. Science Robotics has been launched to cover the most important advances in robot design, theory, and applications. Science Robotics promotes the communication of new ideas, general principles, and original developments. Its content will reflect broad and important new applications of robots (e.g., medical, industrial, land, sea, air, space, and service) across all scales (nano to macro), including the underlying principles of robotic systems covering actuation, sensor, learning, control, and navigation. In addition to original research articles, the journal also publishes invited reviews. There are also plans to cover opinions and comments on current policy, ethical, and social issues that affect the robotics community, as well as to engage with robotics educational programs by using Science Robotics content. The goal of Science Robotics is to move the field forward and cross-fertilize different research applications and domains.

 

 

Amazon Opening Store That Will Eliminate Checkout — and Lines — from bloomberg.com by Jing Cao
At Amazon Seattle location items get charged to Prime account | New technology combines artificial intelligence and sensors

Excerpt:

Amazon.com Inc. unveiled technology that will let shoppers grab groceries without having to scan and pay for them — in one stroke eliminating the checkout line.

The company is testing the new system at what it’s calling an Amazon Go store in Seattle, which will open to the public early next year. Customers will be able to scan their phones at the entrance using a new Amazon Go mobile app. Then the technology will track what items they pick up or even return to the shelves and add them to a virtual shopping cart in real time, according a video Amazon posted on YouTube. Once the customers exit the store, they’ll be charged on their Amazon account automatically.

 

 

 

Amazon Introduces ‘Amazon Go’ Retail Stores, No Checkout, No Lines — from investors.com

Excerpt:

Online retail king Amazon.com (AMZN) is taking dead aim at the physical-store world Monday, introducing Amazon Go, a retail convenience store format it is developing that will use computer vision and deep-learning algorithms to let shoppers just pick up what they want and exit the store without any checkout procedure.

Shoppers will merely need to tap the Amazon Go app on their smartphones, and their virtual shopping carts will automatically tabulate what they owe, and deduct that amount from their Amazon accounts, sending you a receipt. It’s what the company has deemed “just walk out technology,” which it said is based on the same technology used in self-driving cars. It’s certain to up the ante in the company’s competition with Wal-Mart (WMT), Target (TGT) and the other retail leaders.

 

 

Google DeepMind Makes AI Training Platform Publicly Available — from bloomberg.com by Jeremy Kahn
Company is increasingly embracing open-source initiatives | Move comes after rival Musk’s OpenAI made its robot gym public

Excerpt:

Alphabet Inc.’s artificial intelligence division Google DeepMind is making the maze-like game platform it uses for many of its experiments available to other researchers and the general public.

DeepMind is putting the entire source code for its training environment — which it previously called Labyrinth and has now renamed as DeepMind Lab — on the open-source depository GitHub, the company said Monday. Anyone will be able to download the code and customize it to help train their own artificial intelligence systems. They will also be able to create new game levels for DeepMind Lab and upload these to GitHub.

 

Related:
Alphabet DeepMind is inviting developers into the digital world where its AI learns to explore — from qz.com by Dave Gershgorn

 

 

 

After Retail Stumble, Beacons Shine From Banks to Sports Arenas — from bloomberg.com by Olga Kharif
Shipments of the devices expected to grow to 500 million

Excerpt (emphasis DSC):

Beacon technology, which was practically left for dead after failing to deliver on its promise to revolutionize the retail industry, is making a comeback.

Beacons are puck-size gadgets that can send helpful tips, coupons and other information to people’s smartphones through Bluetooth. They’re now being used in everything from bank branches and sports arenas to resorts, airports and fast-food restaurants. In the latest sign of the resurgence, Mobile Majority, an advertising startup, said on Monday that it was buying Gimbal Inc., a beacon maker it bills as the largest independent source of location data other than Google and Apple Inc.
…
Several recent developments have sparked the latest boom. Companies like Google parent Alphabet Inc. are making it possible for people to use the feature without downloading any apps, which had been a major barrier to adoption, said Patrick Connolly, an analyst at ABI. Introduced this year, Google Nearby Notifications lets developers tie an app or a website to a beacon to send messages to consumers even when they have no app installed.
…
But in June, Cupertino, California-based Mist Systems began shipping a software-based product that simplified the process. Instead of placing 10 beacons on walls and ceilings, for example, management using Mist can install one device every 2,000 feet (610 meters), then designate various points on a digital floor plan as virtual beacons, which can be moved with a click of a mouse.

 

 

Google’s Hand-Fed AI Now Gives Answers, Not Just Search Results — from wired.com by Cade Metz

Excerpt:

Ask the Google search app “What is the fastest bird on Earth?,” and it will tell you.

“Peregrine falcon,” the phone says. “According to YouTube, the peregrine falcon has a maximum recorded airspeed of 389 kilometers per hour.”

That’s the right answer, but it doesn’t come from some master database inside Google. When you ask the question, Google’s search engine pinpoints a YouTube video describing the five fastest birds on the planet and then extracts just the information you’re looking for. It doesn’t mention those other four birds. And it responds in similar fashion if you ask, say, “How many days are there in Hanukkah?” or “How long is Totem?” The search engine knows that Totem is a Cirque de Soleil show, and that it lasts two-and-a-half hours, including a thirty-minute intermission.

Google answers these questions with the help from deep neural networks, a form of artificial intelligence rapidly remaking not just Google’s search engine but the entire company and, well, the other giants of the internet, from Facebook to Microsoft. Deep neutral nets are pattern recognition systems that can learn to perform specific tasks by analyzing vast amounts of data. In this case, they’ve learned to take a long sentence or paragraph from a relevant page on the web and extract the upshot—the information you’re looking for.

 

 

Deep Learning in Production at Facebook — from re-work.co by Katie Pollitt

Excerpt:

Facebook is powered by machine learning and AI. From advertising relevance, news feed and search ranking to computer vision, face recognition, and speech recognition, they run ML models at massive scale, computing trillions of predictions every day.

At the 2016 Deep Learning Summit in Boston, Andrew Tulloch, Research Engineer at Facebook, talked about some of the tools and tricks Facebook use for scaling both the training and deployment of some of their deep learning models at Facebook. He also covered some useful libraries that they’d open-sourced for production-oriented deep learning applications. Tulloch’s session can be watched in full below.

 

 

The Artificial Intelligence Gold Rush — from foresightr.com by Mark Vickers
Big companies, venture capital firms and governments are all banking on AI

Excerpt:

Let’s start with some of the brand-name organizations laying down big bucks on artificial intelligence.

  • Amazon: Sells the successful Echo home speaker, which comes with the personal assistant Alexa.
  • Alphabet (Google): Uses deep learning technology to power Internet searches and developed AlphaGo, an AI that beat the world champion in the game of Go.
  • Apple: Developed the popular virtual assistant Siri and is working on other phone-related AI applications, such as facial recognition.
  • Baidu: Wants to use AI to improve search, recognize images of objects and respond to natural language queries.
  • Boeing: Works with Carnegie Mellon University to develop machine learning capable of helping it design and build planes more efficiently.
  • Facebook: Wants to create the “best AI lab in the world.” Has its personal assistant, M, and focuses heavily on facial recognition.
    IBM: Created the Jeopardy-winning Watson AI and is leveraging its data analysis and natural language capabilities in the healthcare industry.
  • Intel: Has made acquisitions to help it build specialized chips and software to handle deep learning.
  • Microsoft: Works on chatbot technology and acquired SwiftKey, which predicts what users will type next.
  • Nokia: Has introduced various machine learning capabilities to its portfolio of customer-experience software.
    Nvidia: Builds computer chips customized for deep learning.
  • Salesforce: Took first place at the Stanford Question Answering Dataset, a test of machine learning and comprehension, and has developed the Einstein model that learns from data.
  • Shell: Launched a virtual assistant to answer customer questions.
  • Tesla Motors: Continues to work on self-driving automobile technologies.
  • Twitter: Created an AI-development team called Cortex and acquired several AI startups.

 

 

 

IBM Watson and Education in the Cognitive Era — from i-programmer.info by Nikos Vaggalis

Excerpt:

IBM’s seemingly ubiquitous Watson is now infiltrating education, through AI powered software that ‘reads’ the needs of individual  students in order to engage them through tailored learning approaches.

This is not to be taken lightly, as it opens the door to a new breed of technologies that will spearhead the education or re-education of the workforce of the future.

As outlined in the 2030 report, despite robots or AI displacing a big chunk of the workforce, they will also play a major role in creating job opportunities as never before.In such a competitive landscape, workers of all kinds, white or blue collar to begin with, should come readied with new, versatile and contemporary skills.

The point is, the very AI that will leave someone jobless, will also help him to re-adapt into a new job’s requirements.It will also prepare the new generations through the use of such optimal methodologies that will once more give meaning to the aging  and counter-productive schooling system which has the  students’ skills disengaged from the needs of the industry and which still segregates students into ‘good’ and ‘bad’. Might it be that ‘bad’ students become just like that due to the system’s inability to stimulate their interest?

 

 

 

 

From DSC:
When I saw the article below, I couldn’t help but wonder…what are the teaching & learning-related ramifications when new “skills” are constantly being added to devices like Amazon’s Alexa?

What does it mean for:

  • Students / learners
  • Faculty members
  • Teachers
  • Trainers
  • Instructional Designers
  • Interaction Designers
  • User Experience Designers
  • Curriculum Developers
  • …and others?

Will the capabilities found in Alexa simply come bundled as a part of the “connected/smart TV’s” of the future? Hmm….

 

 

NASA unveils a skill for Amazon’s Alexa that lets you ask questions about Mars — from geekwire.com by Kevin Lisota

Excerpt:

Amazon’s Alexa has gained many skills over the past year, such as being able to read tweets or deliver election results and fantasy football scores. Starting on Wednesday, you’ll be able to ask Alexa about Mars.

The new skill for the voice-controlled speaker comes courtesy of NASA’s Jet Propulsion Laboratory. It’s the first Alexa app from the space agency.

Tom Soderstrom, the chief technology officer at NASA’s Jet Propulsion Laboratory was on hand at the AWS re:invent conference in Las Vegas tonight to make the announcement.

 

 

nasa-alexa-11-29-16

 

 


Also see:


 

What Is Alexa? What Is the Amazon Echo, and Should You Get One? — from thewirecutter.com by Grant Clauser

 

side-by-side2

 

 

Amazon launches new artificial intelligence services for developers: Image recognition, text-to-speech, Alexa NLP — from geekwire.com by Taylor Soper

Excerpt (emphasis DSC):

Amazon today announced three new artificial intelligence-related toolkits for developers building apps on Amazon Web Services

At the company’s AWS re:invent conference in Las Vegas, Amazon showed how developers can use three new services — Amazon Lex, Amazon Polly, Amazon Rekognition — to build artificial intelligence features into apps for platforms like Slack, Facebook Messenger, ZenDesk, and others.

The idea is to let developers utilize the machine learning algorithms and technology that Amazon has already created for its own processes and services like Alexa. Instead of developing their own AI software, AWS customers can simply use an API call or the AWS Management Console to incorporate AI features into their own apps.

 

 

Amazon announces three new AI services, including a text-to-voice service, Amazon Polly  — from by D.B. Hebbard

 

 

AWS Announces Three New Amazon AI Services
Amazon Lex, the technology that powers Amazon Alexa, enables any developer to build rich, conversational user experiences for web, mobile, and connected device apps; preview starts today

Amazon Polly transforms text into lifelike speech, enabling apps to talk with 47 lifelike voices in 24 languages

Amazon Rekognition makes it easy to add image analysis to applications, using powerful deep learning-based image and face recognition

Capital One, Motorola Solutions, SmugMug, American Heart Association, NASA, HubSpot, Redfin, Ohio Health, DuoLingo, Royal National Institute of Blind People, LingApps, GoAnimate, and Coursera are among the many customers using these Amazon AI Services

Excerpt:

SEATTLE–(BUSINESS WIRE)–Nov. 30, 2016– Today at AWS re:Invent, Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced three Artificial Intelligence (AI) services that make it easy for any developer to build apps that can understand natural language, turn text into lifelike speech, have conversations using voice or text, analyze images, and recognize faces, objects, and scenes. Amazon Lex, Amazon Polly, and Amazon Rekognition are based on the same proven, highly scalable Amazon technology built by the thousands of deep learning and machine learning experts across the company. Amazon AI services all provide high-quality, high-accuracy AI capabilities that are scalable and cost-effective. Amazon AI services are fully managed services so there are no deep learning algorithms to build, no machine learning models to train, and no up-front commitments or infrastructure investments required. This frees developers to focus on defining and building an entirely new generation of apps that can see, hear, speak, understand, and interact with the world around them.

To learn more about Amazon Lex, Amazon Polly, or Amazon Rekognition, visit:
https://aws.amazon.com/amazon-ai

 

 

 

 

 

Explosive IoT growth could produce skills shortage — from rtinsights.com by Joe McKendrick

Excerpts:

CIO’s Sharon Florentine took a look at data from global freelance marketplace Upwork, based on annual job posting growth and skills demand. The following are leading IoT skills Florentine identified that will be demand as the IoT proliferates, with level the growth seen over a one-year period:

Circuit design (231% growth): Builds miniaturized circuit boards for sensors and devices.

Microcontroller programming (225% growth): Writes code that provides intelligence to microcontrollers, the embedded chips within IoT devices.

AutoCAD (216% growth): Designs the devices.

Machine learning (199% growth): Writes the algorithms that recognize data patterns within devices.

Security infrastructure (194% growth): Identifies and integrates the standards, protocols and technologies that protect devices, as well as the data inside.

Big data (183% growth): Data scientists and engineers “who can collect, organize, analyze and architect disparate sources of data.” Hadoop and Apache Spark are two areas with particularly strong demand.

 

Some brief reflections from DSC:

will likely be used by colleges, universities, bootcamps, MOOCs, and others to feed web-based learner profiles, which will then be queried by people and/or organizations who are looking for freelancers and/or employees to fill their project and/or job-related needs.

As of the end of 2016, Microsoft — with their purchase of LinkedIn — is strongly positioned as being a major player in this new landscape. But it might turn out to be an open-sourced solution/database.

Data mining, algorithm development, and Artificial Intelligence (AI) will likely have roles to play here as well. The systems will likely be able to tell us where we need to grow our skillsets, and provide us with modules/courses to take. This is where the Learning from the Living [Class] Room vision becomes highly relevant, on a global scale. We will be forced to continually improve our skillsets as long as we are in the workforce. Lifelong learning is now a must. AI-based recommendation engines should be helpful here — as they will be able to analyze the needs, trends, developments, etc. and present us with some possible choices (based on our learner profiles, interests, and passions).

 

 

Google, Facebook, and Microsoft are remaking themselves around AI — from wired.com by Cade Metz

Excerpt (emphasis DSC):

Alongside a former Stanford researcher—Jia Li, who more recently ran research for the social networking service Snapchat—the China-born Fei-Fei will lead a team inside Google’s cloud computing operation, building online services that any coder or company can use to build their own AI. This new Cloud Machine Learning Group is the latest example of AI not only re-shaping the technology that Google uses, but also changing how the company organizes and operates its business.

Google is not alone in this rapid re-orientation. Amazon is building a similar group cloud computing group for AI. Facebook and Twitter have created internal groups akin to Google Brain, the team responsible for infusing the search giant’s own tech with AI. And in recent weeks, Microsoft reorganized much of its operation around its existing machine learning work, creating a new AI and research group under executive vice president Harry Shum, who began his career as a computer vision researcher.

 

But Etzioni says this is also part of very real shift inside these companies, with AI poised to play an increasingly large role in our future. “This isn’t just window dressing,” he says.

 

 

Intelligence everywhere! Gartner’s Top 10 Strategic Technology Trends for 2017 — from which-50.com

Excerpt (emphasis DSC):

AI and Advanced Machine Learning
Artificial intelligence (AI) and advanced machine learning (ML) are composed of many technologies and techniques (e.g., deep learning, neural networks, natural-language processing [NLP]). The more advanced techniques move beyond traditional rule-based algorithms to create systems that understand, learn, predict, adapt and potentially operate autonomously. This is what makes smart machines appear “intelligent.”

“Applied AI and advanced machine learning give rise to a spectrum of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as apps and services (virtual personal assistants [VPAs], smart advisors), ” said David Cearley, vice president and Gartner Fellow. “These implementations will be delivered as a new class of obviously intelligent apps and things as well as provide embedded intelligence for a wide range of mesh devices and existing software and service solutions.”

 

gartner-toptechtrends-2017

 

 

 

 

aiexperiments-google-nov2016

 

Google’s new website lets you play with its experimental AI projects — from mashable.com by Karissa Bell

Excerpt:

Google is letting users peek into some of its most experimental artificial intelligence projects.

The company unveiled a new website Tuesday called A.I. Experiments that showcases Google’s artificial intelligence research through web apps that anyone can test out. The projects include a game that guesses what you’re drawing, a camera app that recognizes objects you put in front of it and a music app that plays “duets” with you.

 

Google unveils a slew of new and improved machine learning APIs — from digitaltrends.com by Kyle Wiggers

Excerpt:

On Tuesday, Google Cloud chief Diane Greene announced the formation of a new team, the Google Cloud Machine Learning group, that will manage the Mountain View, California-based company’s cloud intelligence efforts going forward.

 

Found in translation: More accurate, fluent sentences in Google Translate — from blog.google by Barak Turovsky

Excerpt:

In 10 years, Google Translate has gone from supporting just a few languages to 103, connecting strangers, reaching across language barriers and even helping people find love. At the start, we pioneered large-scale statistical machine translation, which uses statistical models to translate text. Today, we’re introducing the next step in making Google Translate even better: Neural Machine Translation.

Neural Machine Translation has been generating exciting research results for a few years and in September, our researchers announced Google’s version of this technique. At a high level, the Neural system translates whole sentences at a time, rather than just piece by piece. It uses this broader context to help it figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar. Since it’s easier to understand each sentence, translated paragraphs and articles are a lot smoother and easier to read. And this is all possible because of end-to-end learning system built on Neural Machine Translation, which basically means that the system learns over time to create better, more natural translations.

 

 

‘Augmented Intelligence’ for Higher Ed — from insidehighered.com by Carl Straumsheim
IBM picks Blackboard and Pearson to bring the technology behind the Watson computer to colleges and universities.

Excerpts:

[IBM] is partnering with a small number of hardware and software providers to bring the same technology that won a special edition of the game show back in 2011 to K-12 institutions, colleges and continuing education providers. The partnerships and the products that might emerge from them are still in the planning stage, but the company is investing in the idea that cognitive computing — natural language processing, informational retrieval and other functions similar to the ones performed by the human brain — can help students succeed in and outside the classroom.

Chalapathy Neti, vice president of education innovation at IBM Watson, said education is undergoing the same “digital transformation” seen in the finance and health care sectors, in which more and more content is being delivered digitally.
…
IBM is steering clear of referring to its technology as “artificial intelligence,” however, as some may interpret it as replacing what humans already do.

“This is about augmenting human intelligence,” Neti said. “We never want to see these data-based systems as primary decision makers, but we want to provide them as decision assistance for a human decision maker that is an expert in conducting that process.”

 

 

What a Visit to an AI-Enabled Hospital Might Look Like — from hbr.org by R “Ray” Wang

Excerpt (emphasis DSC):

The combination of machine learning, deep learning, natural language processing, and cognitive computing will soon change the ways that we interact with our environments. AI-driven smart services will sense what we’re doing, know what our preferences are from our past behavior, and subtly guide us through our daily lives in ways that will feel truly seamless.

Perhaps the best way to explore how such systems might work is by looking at an example: a visit to a hospital.
…
The AI loop includes seven steps:

  1. Perception describes what’s happening now.
  2. Notification tells you what you asked to know.
  3. Suggestion recommends action.
  4. Automation repeats what you always want.
  5. Prediction informs you of what to expect.
  6. Prevention helps you avoid bad outcomes.
  7. Situational awareness tells you what you need to know right now.

 

 

Japanese artificial intelligence gives up on University of Tokyo admissions exam — from digitaltrends.com by Brad Jones

Excerpt:

Since 2011, Japan’s National Institute of Informatics has been working on an AI, with the end goal of having it pass the entrance exam for the University of Tokyo, according to a report from Engadget. This endeavor, dubbed the Todai Robot Project in reference to a local nickname for the school, has been abandoned.

It turns out that the AI simply cannot meet the exact requirements of the University of Tokyo. The team does not expect to reach their goal of passing the test by March 2022, so the project is being brought to an end.

 

 

“We are building not just Azure to have rich compute capability, but we are, in fact, building the world’s first AI supercomputer,” he said.

— from Microsoft CEO Satya Nadella spruiks power of machine learning,
smart bots and mixed reality at Sydney developers conference

 

Why it’s so hard to create unbiased artificial intelligence — from techcrunch.com by Ben Dickson

Excerpt:

As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we’ve become somewhat expectant that robots can succeed where humans have failed — namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society.

While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make.

 

 

 

The Non-Technical Guide to Machine Learning & Artificial Intelligence — from medium.com by Sam DeBrule

Excerpt:

This list is a primer for non-technical people who want to understand what machine learning makes possible.

To develop a deep understanding of the space, reading won’t be enough. You need to: have an understanding of the entire landscape, spot and use ML-enabled products in your daily life (Spotify recommendations), discuss artificial intelligence more regularly, and make friends with people who know more than you do about AI and ML.

News: For starters, I’ve included a link to a weekly artificial intelligence email that Avi Eisenberger and I curate (machinelearnings.co). Start here if you want to develop a better understanding of the space, but don’t have the time to actively hunt for machine learning and artificial intelligence news.

Startups: It’s nice to see what startups are doing, and not only hear about the money they are raising. I’ve included links to the websites and apps of 307+ machine intelligence companies and tools.

People: Here’s a good place to jump into the conversation. I’ve provided links to Twitter accounts (and LinkedIn profiles and personal websites in their absence) of the founders, investors, writers, operators and researchers who work in and around the machine learning space.

Events: If you enjoy getting out from behind your computer, and want to meet awesome people who are interested in artificial intelligence in real life, there is one place that’s best to do that, more on my favorite place below.

 

 

 

How one clothing company blends AI and human expertise — from hbr.org by H. James Wilson, Paul Daugherty, & Prashant Shukla

Excerpt:

When we think about artificial intelligence, we often imagine robots performing tasks on the warehouse or factory floor that were once exclusively the work of people. This conjures up the specter of lost jobs and upheaval for many workers. Yet, it can also seem a bit remote — something that will happen in “the future.” But the future is a lot closer than many realize. It also looks more promising than many have predicted.

Stitch Fix provides a glimpse of how some businesses are already making use of AI-based machine learning to partner with employees for more-effective solutions. A five-year-old online clothing retailer, its success in this area reveals how AI and people can work together, with each side focused on its unique strengths.

 

 

 

 

he-thinkaboutai-washpost-oc2016

 

Excerpt (emphasis DSC):

As the White House report rightly observes, the implications of an AI-suffused world are enormous — especially for the people who work at jobs that soon will be outsourced to artificially-intelligent machines. Although the report predicts that AI ultimately will expand the U.S. economy, it also notes that “Because AI has the potential to eliminate or drive down wages of some jobs … AI-driven automation will increase the wage gap between less-educated and more-educated workers, potentially increasing economic inequality.”

Accordingly, the ability of people to access higher education continuously throughout their working lives will become increasingly important as the AI revolution takes hold. To be sure, college has always helped safeguard people from economic dislocations caused by technological change. But this time is different. First, the quality of AI is improving rapidly. On a widely-used image recognition test, for instance, the best AI result went from a 26 percent error rate in 2011 to a 3.5 percent error rate in 2015 — even better than the 5 percent human error rate.

Moreover, as the administration’s report documents, AI has already found new applications in so-called “knowledge economy” fields, such as medical diagnosis, education and scientific research. Consequently, as artificially intelligent systems come to be used in more white-collar, professional domains, even people who are highly educated by today’s standards may find their livelihoods continuously at risk by an ever-expanding cybernetic workforce.

 

As a result, it’s time to stop thinking of higher education as an experience that people take part in once during their young lives — or even several times as they advance up the professional ladder — and begin thinking of it as a platform for lifelong learning.

 

Colleges and universities need to be doing more to move beyond the array of two-year, four-year, and graduate degrees that most offer, and toward a more customizable system that enables learners to access the learning they need when they need it. This will be critical as more people seek to return to higher education repeatedly during their careers, compelled by the imperative to stay ahead of relentless technological change.

 

 

From DSC:
That last bolded paragraph is why I think the vision of easily accessible learning — using the devices that will likely be found in one’s apartment or home — will be enormously powerful and widespread in a few years. Given the exponential pace of change that we are experiencing — and will likely continue to experience for some time — people will need to reinvent themselves quickly.

Higher education needs to rethink our offerings…or someone else will.

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

 

 

From DSC:
We are hopefully creating the future that we want — i.e., creating the future of our dreams, not nightmares.  The 14 items below show that technology is often waaay out ahead of us…and it takes time for other areas of society to catch up (such as areas that involve making policies, laws, and/or if we should even be doing these things in the first place). 

Such reflections always make me ask:

  • Who should be involved in some of these decisions?
  • Who is currently getting asked to the decision-making tables for such discussions?
  • How does the average citizen participate in such discussions?

Readers of this blog know that I’m generally pro-technology. But with the exponential pace of technological change, we need to slow things down enough to make wise decisions.

 


 

Google AI invents its own cryptographic algorithm; no one knows how it works — from arstechnica.co.uk by Sebastian Anthony
Neural networks seem good at devising crypto methods; less good at codebreaking.

Excerpt:

Google Brain has created two artificial intelligences that evolved their own cryptographic algorithm to protect their messages from a third AI, which was trying to evolve its own method to crack the AI-generated crypto. The study was a success: the first two AIs learnt how to communicate securely from scratch.

 

 

IoT growing faster than the ability to defend it — from scientificamerican.com by Larry Greenemeier
Last week’s use of connected gadgets to attack the Web is a wake-up call for the Internet of Things, which will get a whole lot bigger this holiday season

Excerpt:

With this year’s approaching holiday gift season the rapidly growing “Internet of Things” or IoT—which was exploited to help shut down parts of the Web this past Friday—is about to get a lot bigger, and fast. Christmas and Hanukkah wish lists are sure to be filled with smartwatches, fitness trackers, home-monitoring cameras and other wi-fi–connected gadgets that connect to the internet to upload photos, videos and workout details to the cloud. Unfortunately these devices are also vulnerable to viruses and other malicious software (malware) that can be used to turn them into virtual weapons without their owners’ consent or knowledge.

Last week’s distributed denial of service (DDoS) attacks—in which tens of millions of hacked devices were exploited to jam and take down internet computer servers—is an ominous sign for the Internet of Things. A DDoS is a cyber attack in which large numbers of devices are programmed to request access to the same Web site at the same time, creating data traffic bottlenecks that cut off access to the site. In this case the still-unknown attackers used malware known as “Mirai” to hack into devices whose passwords they could guess, because the owners either could not or did not change the devices’ default passwords.

 

 

How to Get Lost in Augmented Reality — from inverse.com by Tanya Basu; with thanks to Woontack Woo for this resource
There are no laws against projecting misinformation. That’s good news for pranksters, criminals, and advertisers.

Excerpt:

Augmented reality offers designers and engineers new tools and artists and new palette, but there’s a dark side to reality-plus. Because A.R. technologies will eventually allow individuals to add flourishes to the environments of others, they will also facilitate the creation of a new type of misinformation and unwanted interactions. There will be advertising (there is always advertising) and there will also be lies perpetrated with optical trickery.

Two computer scientists-turned-ethicists are seriously considering the problematic ramifications of a technology that allows for real-world pop-ups: Keith Miller at the University of Missouri-St. Louis and Bo Brinkman at Miami University in Ohio. Both men are dismissive of Pokémon Go because smartphones are actually behind the times when it comes to A.R.
…
A very important question is who controls these augmentations,” Miller says. “It’s a huge responsibility to take over someone’s world — you could manipulate people. You could nudge them.”

 

 

Can we build AI without losing control over it? — from ted.com by Sam Harris

Description:

Scared of superintelligent AI? You should be, says neuroscientist and philosopher Sam Harris — and not just in some theoretical way. We’re going to build superhuman machines, says Harris, but we haven’t yet grappled with the problems associated with creating something that may treat us the way we treat ants.

 

 

Do no harm, don’t discriminate: official guidance issued on robot ethics — from theguardian.com
Robot deception, addiction and possibility of AIs exceeding their remits noted as hazards that manufacturers should consider

Excerpt:

Isaac Asimov gave us the basic rules of good robot behaviour: don’t harm humans, obey orders and protect yourself. Now the British Standards Institute has issued a more official version aimed at helping designers create ethically sound robots.

The document, BS8611 Robots and robotic devices, is written in the dry language of a health and safety manual, but the undesirable scenarios it highlights could be taken directly from fiction. Robot deception, robot addiction and the possibility of self-learning systems exceeding their remits are all noted as hazards that manufacturers should consider.

 

 

World’s first baby born with new “3 parent” technique — from newscientist.com by Jessica Hamzelou

Excerpt:

It’s a boy! A five-month-old boy is the first baby to be born using a new technique that incorporates DNA from three people, New Scientist can reveal. “This is great news and a huge deal,” says Dusko Ilic at King’s College London, who wasn’t involved in the work. “It’s revolutionary.”

The controversial technique, which allows parents with rare genetic mutations to have healthy babies, has only been legally approved in the UK. But the birth of the child, whose Jordanian parents were treated by a US-based team in Mexico, should fast-forward progress around the world, say embryologists.

 

 

Scientists Grow Full-Sized, Beating Human Hearts From Stem Cells — from popsci.com by Alexandra Ossola
It’s the closest we’ve come to growing transplantable hearts in the lab

Excerpt:

Of the 4,000 Americans waiting for heart transplants, only 2,500 will receive new hearts in the next year. Even for those lucky enough to get a transplant, the biggest risk is the their bodies will reject the new heart and launch a massive immune reaction against the foreign cells. To combat the problems of organ shortage and decrease the chance that a patient’s body will reject it, researchers have been working to create synthetic organs from patients’ own cells. Now a team of scientists from Massachusetts General Hospital and Harvard Medical School has gotten one step closer, using adult skin cells to regenerate functional human heart tissue, according to a study published recently in the journal Circulation Research.

 

 

 

Achieving trust through data ethics — from sloanreview.mit.edu
Success in the digital age requires a new kind of diligence in how companies gather and use data.

Excerpt:

A few months ago, Danish researchers used data-scraping software to collect the personal information of nearly 70,000 users of a major online dating site as part of a study they were conducting. The researchers then published their results on an open scientific forum. Their report included the usernames, political leanings, drug usage, and other intimate details of each account.

A firestorm ensued. Although the data gathered and subsequently released was already publicly available, many questioned whether collecting, bundling, and broadcasting the data crossed serious ethical and legal boundaries.

In today’s digital age, data is the primary form of currency. Simply put: Data equals information equals insights equals power.

Technology is advancing at an unprecedented rate — along with data creation and collection. But where should the line be drawn? Where do basic principles come into play to consider the potential harm from data’s use?

 

 

“Data Science Ethics” course — from the University of Michigan on edX.org
Learn how to think through the ethics surrounding privacy, data sharing, and algorithmic decision-making.

About this course
As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias. Many data scientists learn the tools of the trade and get down to work right away, without appreciating the possible consequences of their work.

This course focused on ethics specifically related to data science will provide you with the framework to analyze these concerns. This framework is based on ethics, which are shared values that help differentiate right from wrong. Ethics are not law, but they are usually the basis for laws.

Everyone, including data scientists, will benefit from this course. No previous knowledge is needed.

 

 

 

Science, Technology, and the Future of Warfare — from mwi.usma.edu by Margaret Kosal

Excerpt:

We know that emerging innovations within cutting-edge science and technology (S&T) areas carry the potential to revolutionize governmental structures, economies, and life as we know it. Yet, others have argued that such technologies could yield doomsday scenarios and that military applications of such technologies have even greater potential than nuclear weapons to radically change the balance of power. These S&T areas include robotics and autonomous unmanned system; artificial intelligence; biotechnology, including synthetic and systems biology; the cognitive neurosciences; nanotechnology, including stealth meta-materials; additive manufacturing (aka 3D printing); and the intersection of each with information and computing technologies, i.e., cyber-everything. These concepts and the underlying strategic importance were articulated at the multi-national level in NATO’s May 2010 New Strategic Concept paper: “Less predictable is the possibility that research breakthroughs will transform the technological battlefield…. The most destructive periods of history tend to be those when the means of aggression have gained the upper hand in the art of waging war.”

 

 

Low-Cost Gene Editing Could Breed a New Form of Bioterrorism — from bigthink.com by Philip Perry

Excerpt:

2012 saw the advent of gene editing technique CRISPR-Cas9. Now, just a few short years later, gene editing is becoming accessible to more of the world than its scientific institutions. This new technique is now being used in public health projects, to undermine the ability of certain mosquitoes to transmit disease, such as the Zika virus. But that initiative has had many in the field wondering whether it could be used for the opposite purpose, with malicious intent.

Back in February, U.S. National Intelligence Director James Clapper put out a Worldwide Threat Assessment, to alert the intelligence community of the potential risks posed by gene editing. The technology, which holds incredible promise for agriculture and medicine, was added to the list of weapons of mass destruction.

It is thought that amateur terrorists, non-state actors such as ISIS, or rouge states such as North Korea, could get their hands on it, and use this technology to create a bioweapon such as the earth has never seen, causing wanton destruction and chaos without any way to mitigate it.

 

What would happen if gene editing fell into the wrong hands?

 

 

 

Robot nurses will make shortages obsolete — from thedailybeast.com by Joelle Renstrom
By 2022, one million nurse jobs will be unfilled—leaving patients with lower quality care and longer waits. But what if robots could do the job?

Excerpt:

Japan is ahead of the curve when it comes to this trend, given that its elderly population is the highest of any country. Toyohashi University of Technology has developed Terapio, a robotic medical cart that can make hospital rounds, deliver medications and other items, and retrieve records. It follows a specific individual, such as a doctor or nurse, who can use it to record and access patient data. Terapio isn’t humanoid, but it does have expressive eyes that change shape and make it seem responsive. This type of robot will likely be one of the first to be implemented in hospitals because it has fairly minimal patient contact, works with staff, and has a benign appearance.

 

 

 

partnershiponai-sept2016

 

Established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.

 

GOALS

Support Best Practices
To support research and recommend best practices in areas including ethics, fairness, and inclusivity; transparency and interoperability; privacy; collaboration between people and AI systems; and of the trustworthiness, reliability, and robustness of the technology.

Create an Open Platform for Discussion and Engagement
To provide a regular, structured platform for AI researchers and key stakeholders to communicate directly and openly with each other about relevant issues.

Advance Understanding
To advance public understanding and awareness of AI and its potential benefits and potential costs to act as a trusted and expert point of contact as questions/concerns arise from the public and others in the area of AI and to regularly update key constituents on the current state of AI progress.

 

 

 

IBM Watson’s latest gig: Improving cancer treatment with genomic sequencing — from techrepublic.com by Alison DeNisco
A new partnership between IBM Watson Health and Quest Diagnostics will combine Watson’s cognitive computing with genetic tumor sequencing for more precise, individualized cancer care.

 

 



Addendum on 11/1/16:



An open letter to Microsoft and Google’s Partnership on AI — from wired.com by Gerd Leonhard
In a world where machines may have an IQ of 50,000, what will happen to the values and ethics that underpin privacy and free will?

Excerpt:

Dear Francesca, Eric, Mustafa, Yann, Ralf, Demis and others at IBM, Microsoft, Google, Facebook and Amazon.

The Partnership on AI to benefit people and society is a welcome change from the usual celebration of disruption and magic technological progress. I hope it will also usher in a more holistic discussion about the global ethics of the digital age. Your announcement also coincides with the launch of my book Technology vs. Humanity which dramatises this very same question: How will technology stay beneficial to society?

This open letter is my modest contribution to the unfolding of this new partnership. Data is the new oil – which now makes your companies the most powerful entities on the globe, way beyond oil companies and banks. The rise of ‘AI everywhere’ is certain to only accelerate this trend. Yet unlike the giants of the fossil-fuel era, there is little oversight on what exactly you can and will do with this new data-oil, and what rules you’ll need to follow once you have built that AI-in-the-sky. There appears to be very little public stewardship, while accepting responsibility for the consequences of your inventions is rather slow in surfacing.

 

 

Some reflections/resources on today’s announcements from Apple

tv-app-apple-10-27-16

 

tv-app2-apple-10-27-16

From DSC:
How long before recommendation engines like this can be filtered/focused down to just display apps, channels, etc. that are educational and/or training related (i.e., a recommendation engine to suggest personalized/customized playlists for learning)?

That is, in the future, will we have personalized/customized playlists for learning on our Apple TVs — as well as on our mobile devices — with the assessment results of our taking the module(s) or course(s) being sent in to:

  • A credentials database on LinkedIn (via blockchain)
    and/or
  • A credentials database at the college(s) or university(ies) that we’re signed up with for lifelong learning (via blockchain)
    and/or
  • To update our cloud-based learning profiles — which can then feed a variety of HR-related systems used to find talent? (via blockchain)

Will participants in MOOCs, virtual K-12 schools, homeschoolers, and more take advantage of learning from home?

Will solid ROI’s from having thousands of participants paying a smaller amount (to take your course virtually) enable higher production values?

Will bots and/or human tutors be instantly accessible from our couches?

Will we be able to meet virtually via our TVs and share our computing devices?

 

bigscreen_rocket_league

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

 


Other items on today’s announcements:


 

 

macbookpro-10-27-16

 

 

All the big announcements from Apple’s Mac event — from amp.imore.com by Joseph Keller

  • MacBook Pro
  • Final Cut Pro X
  • Apple TV > new “TV” app
  • Touch Bar

 

Apple is finally unifying the TV streaming experience with new app — from techradar.com by Nick Pino

 

 

How to migrate your old Mac’s data to your new Mac — from amp.imore.com by Lory Gil

 

 

MacBook Pro FAQ: Everything you need to know about Apple’s new laptops — from amp.imore.com by Serenity Caldwell

 

 

Accessibility FAQ: Everything you need to know about Apple’s new accessibility portal — from imore.com by Daniel Bader

 

 

Apple’s New MacBook Pro Has a ‘Touch Bar’ on the Keyboard — from wired.com by Brian Barrett

 

 

Apple’s New TV App Won’t Have Netflix or Amazon Video — from wired.com by Brian Barrett

 

 

 

 

Apple 5th Gen TV To Come With Major Software Updates; Release Date Likely In 2017 — from mobilenapps.com

 

 

 

 

whydeeplearningchangingyourlife-sept2016

 

Why deep learning is suddenly changing your life — from fortune.com by Roger Parloff

Excerpt:

Most obviously, the speech-recognition functions on our smartphones work much better than they used to. When we use a voice command to call our spouses, we reach them now. We aren’t connected to Amtrak or an angry ex.

In fact, we are increasingly interacting with our computers by just talking to them, whether it’s Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, or the many voice-responsive features of Google. Chinese search giant Baidu says customers have tripled their use of its speech interfaces in the past 18 months.

Machine translation and other forms of language processing have also become far more convincing, with Google, Microsoft, Facebook, and Baidu unveiling new tricks every month. Google Translate now renders spoken sentences in one language into spoken sentences in another for 32 pairs of languages, while offering text translations for 103 tongues, including Cebuano, Igbo, and Zulu. Google’s Inbox app offers three ready-made replies for many incoming emails.
…
But what most people don’t realize is that all these breakthroughs are, in essence, the same breakthrough. They’ve all been made possible by a family of artificial intelligence (AI) techniques popularly known as deep learning, though most scientists still prefer to call them by their original academic designation: deep neural networks.

 

Even the Internet metaphor doesn’t do justice to what AI with deep learning will mean, in Ng’s view. “AI is the new electricity,” he says. “Just as 100 years ago electricity transformed industry after industry, AI will now do the same.”

 

 

ai-machinelearning-deeplearning-relationship-roger-fall2016

 

 

Graphically speaking:

 

ai-machinelearning-deeplearning-relationship-fall2016

 

 

 

“Our sales teams are using neural nets to recommend which prospects to contact next or what kinds of product offerings to recommend.”

 

 

One way to think of what deep learning does is as “A to B mappings,” says Baidu’s Ng. “You can input an audio clip and output the transcript. That’s speech recognition.” As long as you have data to train the software, the possibilities are endless, he maintains. “You can input email, and the output could be: Is this spam or not?” Input loan applications, he says, and the output might be the likelihood a customer will repay it. Input usage patterns on a fleet of cars, and the output could advise where to send a car next.

 

 

 

 

From DSC:
The other day I had posted some ideas in regards to how artificial intelligence, machine learning, and augmented reality are coming together to offer some wonderful new possibilities for learning (see: “From DSC: Amazing possibilities coming together w/ augmented reality used in conjunction w/ machine learning! For example, consider these ideas.”) Here is one of the graphics from that posting:

 

horticulturalapp-danielchristian

These affordances are just now starting to be uncovered as machines are increasingly able to ascertain patterns, things, objects…even people (which calls for a separate posting at some point).

But mainly, for today, I wanted to highlight an excellent comment/reply from Nikos Andriotis @ Talent LMS who gave me permission to highlight his solid reflections and ideas:

 

nikosandriotisidea-oct2016

https://www.talentlms.com/blog/author/nikos-andriotis

 

From DSC:
Excellent reflection/idea Nikos — that would represent some serious personalized, customized learning!

Nikos’ innovative reflections also made me think about his ideas in light of their interaction or impact with web-based learner profiles, credentialing, badging, and lifelong learning.  What’s especially noteworthy here is that the innovations (that impact learning) continue to occur mainly in the online and blended learning spaces.

How might the ramifications of these innovations impact institutions who are pretty much doing face-to-face only (in terms of their course delivery mechanisms and pedagogies)?

Given:

  • That Microsoft purchased LinkedIn and can amass a database of skills and open jobs (playing a cloud-based matchmaker)
  • Everyday microlearning is key to staying relevant (RSS feeds and tapping into “streams of content” are important here, and so is the use of Twitter)
  • 65% of today’s students will be doing jobs that don’t even exist yet (per Microsoft & The Future Laboratory in 2016)

 

futureproofyourself-msfuturelab-2016

  • The exponential pace of technological change
  • The increasing level of experimentation with blockchain (credentialing)
  • …and more

…what do the futures look like for those colleges and universities that operate only in the face-to-face space and who are not innovating enough?

 

 

 

From DSC:
Consider the affordances that we will soon be experiencing when we combine machine learning — whereby computers “learn” about a variety of things — with new forms of Human Computer Interaction (HCI) — such as Augment Reality (AR)! 

The educational benefits — as well as the business/profit-related benefits will certainly be significant!

For example, let’s create a new mobile app called “Horticultural App (ML)” * — where ML stands for machine learning. This app would be made available on iOS and Android-based devices. (Though this is strictly hypothetical, I hope and pray that some entrepreneurial individuals and/or organizations out there will take this idea and run with it!)

 


Some use cases for such an app:


Students, environmentalists, and lifelong learners will be able to take some serious educationally-related nature walks once they launch the Horticultural App (ML) on their smartphones and tablets!

They simply hold up their device, and the app — in conjunction with the device’s camera — will essentially take a picture of whatever the student is focusing in on. Via machine learning, the app will “recognize” the plant, tree, type of grass, flower, etc. — and will then present information about that plant, tree, type of grass, flower, etc.

 

girl
Above image via shutterstock.com

 

horticulturalapp-danielchristian

 

In the production version of this app, a textual layer could overlay the actual image of the tree/plant/flower/grass/etc.  in the background — and this is where augmented reality comes into play. Also, perhaps there would be an opacity setting that would be user controlled — allowing the learner to fade in or fade out the information about the flower, tree, plant, etc.

 

horticulturalapp2-danielchristian

 

Or let’s look at the potential uses of this type of app from some different angles.

Let’s say you live in Michigan and you want to be sure an area of the park that you are in doesn’t have any Eastern Poison Ivy in it — so you launch the app and review any suspicious looking plants. As it turns out, the app identifies some Eastern Poison Ivy for you (and it could do this regardless of which season we’re talking about, as the app would be able to ascertain the current date and the current GPS coordinates of the person’s location as well, taking that criteria into account).

 

easternpoisonivy

 

 

Or consider another use of such an app:

  • A homeowner who wants to get rid of a certain kind of weed.  The homeowner goes out into her yard and “scans” the weed, and up pops some products at the local Lowe’s or Home Depot that gets rid of that kind of weed.
  • Assuming you allowed the app to do so, it could launch a relevant chatbot that could be used to answer any questions about the application of the weed-killing product that you might have.

 

Or consider another use of such an app:

  • A homeowner has a diseased tree, and they want to know what to do about it. The machine learning portion of the app could identify what the disease was and bring up information on how to eradicate it.
  • Again, if permitted to do so, a relevant chatbot could be launched to address any questions that you might have about the available treatment options for that particular tree/disease.

 

Or consider other/similar apps along these lines:

  • Skin ML (for detecting any issues re: acme, skin cancers, etc.)
  • Minerals and Stones ML (for identifying which mineral or stone you’re looking at)
  • Fish ML
  • Etc.

fish-ml-gettyimages

Image from gettyimages.com

 

So there will be many new possibilities that will be coming soon to education, businesses, homeowners, and many others to be sure! The combination of machine learning with AR will open many new doors.

 


*  From Wikipedia:

Horticulture involves nine areas of study, which can be grouped into two broad sections: ornamentals and edibles:

  1. Arboriculture is the study of, and the selection, plant, care, and removal of, individual trees, shrubs, vines, and other perennial woody plants.
  2. Turf management includes all aspects of the production and maintenance of turf grass for sports, leisure use or amenity use.
  3. Floriculture includes the production and marketing of floral crops.
  4. Landscape horticulture includes the production, marketing and maintenance of landscape plants.
  5. Olericulture includes the production and marketing of vegetables.
  6. Pomology includes the production and marketing of pome fruits.
  7. Viticulture includes the production and marketing of grapes.
  8. Oenology includes all aspects of wine and winemaking.
  9. Postharvest physiology involves maintaining the quality of and preventing the spoilage of plants and animals.

 

 

 

 

accenture-futuregrowthaisept2016

accenture-futurechannelsgrowthaisept2016

 

Why Artificial Intelligence is the Future of Growth — from accenture.com

Excerpt:

Fuel For Growth
Compelling data reveal a discouraging truth about growth today. There has been a marked decline in the ability of traditional levers of production—capital investment and labor—to propel economic growth.

Yet, the numbers tell only part of the story. Artificial intelligence (AI) is a new factor of production and has the potential to introduce new sources of growth, changing how work is done and reinforcing the role of people to drive growth in business.

Accenture research on the impact of AI in 12 developed economies reveals that AI could double annual economic growth rates in 2035 by changing the nature of work and creating a new relationship between man and machine. The impact of AI technologies on business is projected to increase labor productivity by up to 40 percent and enable people to make more efficient use of their time.

 

 

Also see:

 

 

 

Amazon is winning the race to the future — from bizjournals.com by

Excerpt:

This is the week when artificially intelligent assistants start getting serious.

On Tuesday, Google is expected to announce the final details for Home, its connected speaker with the new Google Assistant built inside.

But first Amazon, which surprised everyone last year by practically inventing the AI-in-a-can platform, will release a new version of the Echo Dot, a cheaper and smaller model of the full-sized Echo that promises to put the company’s Alexa assistant in every room in your house.

The Echo Dot has all the capabilities of the original Echo, but at a much cheaper price, and with a compact form factor that’s designed to be tucked away. Because of its size (it looks like a hockey puck from the future), its sound quality isn’t as good as the Echo, but it can hook up to an external speaker through a standard audio cable or Bluetooth.

 

amazon-newdot-oct2016

 

 

100 bot people to watch #BotWatch #1 — from chatbotsmagazine.com

Excerpt:

100 people to watch in the bot space, in no order.

I’ll publish a new list once a month. This one is #1 October 2016.
…
This is my personal top 100 for people to watch in the bot space.

 

 

Should We Give Chatbots Their Own Personalities? — from re-work.com by Sophie Curtis

Excerpt:

Today, we have machines that assemble cars, make candy bars, defuse bombs, and a myriad of other things. They can dispense our drinks, facilitate our bank deposits, and find the movies we want to watch with a touch of the screen.

Automation allows all kinds of amazing things, but it is all done with virtually no personality. Building a chatbot with the ability to be conversational with emotion is crucial to getting people to gain trust in the technology. And now there are plenty of tools and resources available to rapidly create and launch chatbots with the personality customers want and businesses needs.

Jordi Torras is CEO and Founder of Inbenta, a company that specializes in NLP, semantic search and chatbots to improve customer experience. We spoke to him ahead of his presentation at the Virtual Assistant Summit in San Francisco, to learn about the recent explosion of chatbots and virtual assistants, and what we can expect to see in the future.

 

 

 

How I built and launched my first chatbot in hours — from chatbotsmagazine.com by Max Pelzner
From idea to MVB (Minimum Viable Bot), and launched in 24 hours!

 

 

 

Developing a Chatbot? Do Not Make These Mistakes! — from chatbotsmagazine.com Hira Saeed

 

 

 

This is what an A.I.-powered future looks like — from venturebeat.com by Grayson Brulte

Excerpt:

Today, we are just beginning to scratch the surface of what is possible with artificial intelligence (A.I.) and how individuals will interact with its various forms. Every single aspect of our society — from cars to houses to products to services — will be reimagined and redesigned to incorporate A.I.

A child born in the year 2030 will not comprehend why his or her parents once had to manually turn on the lights in the living room. In the future, the smart home will seamlessly know the needs, wants, and habits of the individuals who live in the home prior to them taking an action.

Before we arrive at this future, it is helpful to take a step back and reimagine how we design cars, houses, products, and services. We are just beginning to see glimpses of this future with the Amazon Echo and Google Home smart voice assistants.

 

 

Artificial intelligence created to fold laundry for you — from geek.com by Matthew Humphries

Excerpt:

So, Seven Dreamers Laboratories, in collaboration with Panasonic and Daiwa House Industry, have created just such a machine. However, folding laundry correctly turns out to be quite a complicated task, and so an artificial intelligence was required to make it a reliable process.

Laundry folding is actually a five stage process, including:

Grabbing
Spreading
Recognizing
Folding
Sorting/Storing

The grabbing and spreading seems pretty easy, but then the machine needs to understand what type of clothing it needs to fold. That recognizing stage requires both image recognition and AI. The image recognition classifies the type of clothing, then the AI figures out which processes to use in order to start folding.

 

 

 

 

 

 

2 days of global chatbot experts at Talkabot in 12 minutes — from chatbotsmagazine.com by Alec Lazarescu

Excerpt:

During a delightful “cold spell” in Austin at the end of September, a few hundred chatbot enthusiasts joined together for the first talkabot.ai conference.

As a participant both writing about and building chatbots, I’m excited to share a mix of valuable actionable insights and strategic vision directions picked up from speakers and attendees as well as behind the scenes discussions with the organizers from Howdy.

In a very congenial and collaborative atmosphere, a number of valuable recurring themes stood out from a variety of expert speakers ranging from chatbot builders to tool makers to luminaries from adjacent industries.

 

 

 


Addendum:


 

alexaprize-2016

The Alexa Prize (emphasis DSC)

The way humans interact with machines is at an inflection point and conversational artificial intelligence (AI) is at the center of the transformation. Alexa, the voice service that powers Amazon Echo, enables customers to interact with the world around them in a more intuitive way using only their voice.

The Alexa Prize is an annual competition for university students dedicated to accelerating the field of conversational AI. The inaugural competition is focused on creating a socialbot, a new Alexa skill that converses coherently and engagingly with humans on popular topics and news events. Participating teams will advance several areas of conversational AI including knowledge acquisition, natural language understanding, natural language generation, context modeling, commonsense reasoning and dialog planning. Through the innovative work of students, Alexa customers will have novel, engaging conversations. And, the immediate feedback from Alexa customers will help students improve their algorithms much faster than previously possible.
…
Amazon will award the winning team $500,000. Additionally, a prize of $1 million will be awarded to the winning team’s university if their socialbot achieves the grand challenge of conversing coherently and engagingly with humans on popular topics for 20 minutes.

 

 

 
© 2025 | Daniel Christian