Reflections on “Inside Amazon’s artificial intelligence flywheel” [Levy]

Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.

Excerpt (emphasis DSC):

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

 

 

From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

  • Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
  • AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
  • Voice-driven interfaces.
  • Matching employees to employers.
  • Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
  • From cradle to grave. Lifelong learning.
  • Multimedia-based, interactive content.
  • Asynchronously and synchronously connecting with others learning about the same content.
  • Online-based tutoring/assistance; remote assistance.
  • Reinvent. Staying relevant. Surviving.
  • Competency-based learning.

 

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

 

 

 

 

 

 

 

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Bill Triant and Ryan Craig

 

 

 

Also relevant/see:

Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson

Dive Brief:

  • Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
  • Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
  • Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

 

 

 

 

In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.

 

OBJECTIVES FOR CONVENINGS

  • Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
  • Develop implications for work, workers, students, working learners, employers, and policymakers.
  • Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.

Three key questions guided the discussions:

  1. What are the LEAST and MOST essential skills needed for the future?
  2. Where and how will tomorrow’s workers and learners acquire the skills they really need?
  3. Who is accountable for making sure individuals can thrive in this new economy?

This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.

 

In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.

 

In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.

Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.

Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:

  • Coding. Systems will be self-programming.
  • Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
  • Calendaring, scheduling, and organizing. There won’t be need for email triage.
  • Planning and even decision-making. AI assistants will pick this up.
  • Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
  • Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
  • Language translation and localization. This will happen in real time using translator apps.
  • Legal research and writing. Many of our legal systems will be automated.
  • Validation skills. Machines will check people’s work to validate their skills.
  • Driving. Driverless vehicles will replace the need to learn how to drive.

Here’s a list of the most essential skills needed for the future:

  • Quantitative and algorithmic thinking.  
  • Managing reputation.  
  • Storytelling and interpretive skills.  
  • First principles thinking.  
  • Communicating with machines as machines.  
  • Augmenting high-skilled physical tasks with AI.
  • Optimization and debugging frame of mind.
  • Creativity and growth mindset.
  • Adaptability.
  • Emotional intelligence.
  • Truth seeking.
  • Cybersecurity.

 

The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.

 

 

 

Benchmarking Higher Ed AV Staffing Levels — Revisited — from campustechnology.com by Mike Tomei
As AV-equipped classrooms on campus increase in both numbers and complexity, have AV departments staffed up accordingly? A recent survey sheds some light on how AV is managed in higher education.

Excerpt:

I think we can all agree that new AV system installs have a much higher degree of complexity compared to AV systems five or 10 years ago. The obvious culprits are active learning classrooms that employ multiple displays and matrix switching backends, and conferencing systems of varying complexity being installed in big and small rooms all over campus. But even if today’s standard basic classrooms are offering the same presentation functionality as they were five years ago, the backend AV technology running those systems has still increased in complexity. We’re trying to push very high resolution video signals around the room; copyright-protected digital content is coming into play; there are myriad BYOD devices and connectors that need to be supported; and we’re making a strong push to connect our AV devices to the enterprise network for monitoring and troubleshooting. This increase in AV system complexity just adds to the system design, installation and support burdens placed upon an AV department. Without an increase in FTE staff beyond what we’re seeing, there’s just no way that AV support can truly flourish on campuses.

Today we’re reopening the survey to continue to gather data about AV staffing levels, and we’ll periodically tabulate and publish the results for those that participate. Visit www.AV-Survey.com to take the survey. If you would like to request the full 2018 AV staffing survey results, including average AV department budgets, staffing levels by position, breakouts by public/private/community colleges and small/medium/large schools, please send an e-mail to me (mike@tomeiav.com) and to Craig Park from The Sextant Group (cpark@thesextantgroup.com).

 

 

 

Choice: The key to reaching every student — from flr.flglobal.org by Terra Graves

Excerpt:

Who doesn’t like to have a choice?  This seems like a no-brainer to me. Whenever teachers can give their students choices in their learning process, everyone wins. When we have options, we tend to have more ownership of that experience. It also provides us with a sense of control, which most students do not experience in school. In her article on facultyfocus.com, Elizabeth Betsy Lasley EdD writes, “When students are asked to interpret, construct, and demonstrate their concepts or ideas regarding specific course concepts from a selection of product or performance options, content retention, commitment, motivation, and creativity increase.” Flipped Learning environments are ripe for offering choices to students in how they consume content and how they express their learning outcomes. Giving students choice allows us to reach every student, every day because it honors their individuality. Cassie Shoemaker explains it simply in her article Let it go: Giving students choices, “When teachers give students choices as to how they will show what they have learned, students become better problems solvers, more creative, and more engaged.” Problem-solving: It’s not just for math! Students NEED to have opportunities to make decisions in school to learn to make decisions in life. If we continue to spoonfeed and micromanage our students, they won’t learn to figure things out on their own.  Teachers by nature tend to be control freaks (including me). However, when we allow our students to try/fail/try again, we support their growth and confidence.

 

 

 

NEW: The Top Tools for Learning 2018 [Jane Hart]

The Top Tools for Learning 2018 from the 12th Annual Digital Learning Tools Survey -- by Jane Hart

 

The above was from Jane’s posting 10 Trends for Digital Learning in 2018 — from modernworkplacelearning.com by Jane Hart

Excerpt:

[On 9/24/18],  I released the Top Tools for Learning 2018 , which I compiled from the results of the 12th Annual Digital Learning Tools Survey.

I have also categorised the tools into 30 different areas, and produced 3 sub-lists that provide some context to how the tools are being used:

  • Top 100 Tools for Personal & Professional Learning 2018 (PPL100): the digital tools used by individuals for their own self-improvement, learning and development – both inside and outside the workplace.
  • Top 100 Tools for Workplace Learning (WPL100): the digital tools used to design, deliver, enable and/or support learning in the workplace.
  • Top 100 Tools for Education (EDU100): the digital tools used by educators and students in schools, colleges, universities, adult education etc.

 

3 – Web courses are increasing in popularity.
Although Coursera is still the most popular web course platform, there are, in fact, now 12 web course platforms on the list. New additions this year include Udacity and Highbrow (the latter provides daily micro-lessons). It is clear that people like these platforms because they can chose what they want to study as well as how they want to study, ie. they can dip in and out if they want to and no-one is going to tell them off – which is unlike most corporate online courses which have a prescribed path through them and their use is heavily monitored.

 

 

5 – Learning at work is becoming personal and continuous.
The most significant feature of the list this year is the huge leap up the list that Degreed has made – up 86 places to 47th place – the biggest increase by any tool this year. Degreed is a lifelong learning platform and provides the opportunity for individuals to own their expertise and development through a continuous learning approach. And, interestingly, Degreed appears both on the PPL100 (at  30) and WPL100 (at 52). This suggests that some organisations are beginning to see the importance of personal, continuous learning at work. Indeed, another platform that underpins this, has also moved up the list significantly this year, too. Anders Pink is a smart curation platform available for both individuals and teams which delivers daily curated resources on specified topics. Non-traditional learning platforms are therefore coming to the forefront, as the next point further shows.

 

 

From DSC:
Perhaps some foreshadowing of the presence of a powerful, online-based, next generation learning platform…?

 

 

 

Microsoft's conference room of the future

 

From DSC:
Microsoft’s conference room of the future “listens” to the conversations of the team and provides a transcript of the meeting. It also is using “artificial intelligence tools to then act on what meeting participants say. If someone says ‘I’ll follow up with you next week,’ then they’ll get a notification in Microsoft Teams, Microsoft’s Slack competitor, to actually act on that promise.”

This made me wonder about our learning spaces in the future. Will an #AI-based device/cloud-based software app — in real-time — be able to “listen” to the discussion in a classroom and present helpful resources in the smart classroom of the future (i.e., websites, online-based databases, journal articles, and more)?

Will this be a feature of a next generation learning platform as well (i.e., addressing the online-based learning realm)? Will this be a piece of an intelligent tutor or an intelligent system?

Hmmm…time will tell.

 

 


 

Also see this article out at Forbes.com entitled, “There’s Nothing Artificial About How AI Is Changing The Workplace.” 

Here is an excerpt:

The New Meeting Scribe: Artificial Intelligence

As I write this, AI has already begun to make video meetings even better. You no longer have to spend time entering codes or clicking buttons to launch a meeting. Instead, with voice-based AI, video conference users can start, join or end a meeting by simply speaking a command (think about how you interact with Alexa).

Voice-to-text transcription, another artificial intelligence feature offered by Otter Voice Meeting Notes (from AISense, a Zoom partner), Voicefox and others, can take notes during video meetings, leaving you and your team free to concentrate on what’s being said or shown. AI-based voice-to-text transcription can identify each speaker in the meeting and save you time by letting you skim the transcript, search and analyze it for certain meeting segments or words, then jump to those mentions in the script. Over 65% of respondents from the Zoom survey said they think AI will save them at least one hour a week of busy work, with many claiming it will save them one to five hours a week.

 

 

To higher ed: When the race track is going 180mph, you can’t walk or jog onto the track. [Christian]

From DSC:
When the race track is going 180mph, you can’t walk or jog onto the track.  What do I mean by that? 

Consider this quote from an article that Jeanne Meister wrote out at Forbes entitled, “The Future of Work: Three New HR Roles in the Age of Artificial Intelligence:”*

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more. 

 

From Robert Half’s 2019 Technology Salary Guide 

 

 

How many of us have those kinds of skills? Did we get that training in the community colleges, colleges, and universities that we went to? Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace. 

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies. 

 

 

The below graphic is from:
Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages

 

 

 


 

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

  1. IBM: Vice President, Data, AI & Offering Strategy, HR
  2. Kraft Heinz Senior Vice President Global HR, Performance and IT
  3. SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

 


 

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy 

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

 


 

 

This Android app lets you search for specific words in books & documents via augmented reality — from mobile-ar.reality.news by Tommy Palladino

Excerpt:

One of the neatest tricks available in Google Lens, an app that can identify and interpret real world information, is the ability to copy text from the app’s camera view and paste it into a digital document.

And while the computer vision assistance of Google Lens takes care of the copy and paste function in augmented reality, a new mobile app from Find It Software fulfills the find function directly on printed documents in real time.

 

 

 

Production Values for Audio Podcasts, Part I — from learningsolutionsmag.com by Jeff D’Anza

Excerpts:

There are a number of production values that narrative podcasters find effective for grabbing listener attention and keeping their audiences engaged in the story; you could think of these as technical elements of professional audio quality. They range from techniques for improving content when applied to script writing to methods applied to audio recording and editing. The most successful professional podcasters use these elements to create immersion in the audio environment and to eliminate audio distraction. The result is the creation of a kind of audio theater. Here are four basic practices to embrace while creating your narrative podcasts.

  1. Set the scene first
  2. Hook the audience
  3. Vary character voices
  4. Talk like real people

 

Production Values for Audio Podcasts, Part II — from learningsolutionsmag.com by Jeff D’Anza

Excerpts:

In this article, I will continue with more production tricks that can substantially increase the quality of your narrative podcasts.

Use music to reset scenes
It’s not revolutionary to suggest that learners tend to have short attention spans, and the case is no different when it comes to narrative podcasts. Every so often you need to reset your learners’ brains in order to keep their attention level high.

One excellent way to accomplish this is through the use of musical breaks. Music breaks can function as a type of auditory palate cleanser, allowing the brain a few moments to stop focusing on information that is being presented and prepare the learner to be ready for the next section of content.

Also:

  • Host/producer structure
  • Get out of the studio
  • Don’t fear insignificant details

 


From DSC:

Seems to me there’s some wisdom here for instructional designers as well as professors, teachers, and trainers who are creating learning/training related content and/or who are flipping their classrooms.

 

 

 

The Mobile AR Leaders of 2018 — from next.reality.news

Excerpt:

This time last year, we were getting our first taste of what mobile app developers could do in augmented reality with Apple’s ARKit, and most people had never heard of Animojis. Google’s AR platform was still Tango. Snapchat had just introduced its World Lens AR experiences. Most mobile AR experiences existing in the wild were marker-based offerings from the likes of Blippar and Zappar, or generic Pokémon GO knock-offs.

In last year’s NR50, published before the introduction of ARKit, only two of the top 10 professionals worked directly with mobile AR, and Apple CEO Tim Cook was ranked number 26, based primarily on his forward-looking statements about AR.

This year, Cook comes in at number one, with five others categorized under mobile AR in the overall top 10 of the NR30.

What a difference a year makes.

In just 12 months, we’ve seen mobile AR grow at a breakneck pace. Since Apple launched its AR toolkit, users have downloaded more than 13 million ARKit apps from the App Store, not including existing apps updated with ARKit capabilities. Apple has already updated its platform and will introduce even more new features to the public with the release of ARKit 2.0 this fall. Last year’s iPhone X also introduced a depth-sensing camera and AR Animojis that captured the imaginations of its users.

 

 

The Weather Channel forecasts more augmented reality for its live broadcasts with Unreal Engine — from next.reality.news by Tommy Palladino

Excerpt:

Augmented reality made its live broadcast debut for The Weather Channel in 2015. The technology helps on-air talent at the network to explain the science behind weather phenomena and tell more immersive stories. Powered by Unreal Engine, The Future Group’s Frontier platform will enable The Weather Channel to be able to show even more realistic AR content, such as accurately rendered storms and detailed cityscapes, all in real time.

 

 

 

From DSC:
Imagine this type of thing in online-based learning, MOOCs, and/or even in blended learning based learning environments (i.e., in situations where learning materials are designed/created by teams of specialists). If that were the case, who needs to be trained to create these pieces? Will students be creating these types of pieces in the future? Hmmm….

 

 

Winners announced of the 2018 Journalism 360 Challenge — from vrfocus.com
The question of “How might we experiment with immersive storytelling to advance the field of journalism?” looks to be answered by 11 projects.

Excerpt:

The eleven winners were announced on 9/11/18 of a contest being held by the Google News Initiative, Knight Foundation and Online News Association. The 2018 Journalism 360 Challenge asked people the question “How might we experiment with immersive storytelling to advance the field of journalism?” and it generated over 400 responses.

 

 

 

 

 



 

Addendum:

Educause Explores Future of Extended Reality on Campus — from campustechnology.com by Dian Schaffhauser

Among the findings:

  • VR makes people feel like they’re really there. The “intellectual and physiological reactions” to constructs and events in VR are the same — “and sometimes identical” — to a person’s reactions in the real world;
  • 3D technologies facilitate active and experiential learning. AR, for example, lets users interact with an object in ways that aren’t possible in the physical world — such as seeing through surfaces or viewing data about underlying objects. And with 3D printing, learners can create “physical objects that might otherwise exist only simulations”; and
  • Simulations allow for scaling up of “high-touch, high-cost learning experiences.” Students may be able to go through virtual lab activities, for instance, even when a physical lab isn’t available.

Common challenges included implementation learning curves, instructional design, data storage of 3D images and effective cross-departmental collaboration.

“One significant result from this research is that it shows that these extended reality technologies are applicable across a wide spectrum of academic disciplines,” said Malcolm Brown, director of learning initiatives at Educause, in a statement. “In addition to the scientific disciplines, students in the humanities, for example, can re-construct cities and structures that no longer exist. I think this study will go a long way in encouraging faculty, instructional designers and educational technologists across higher education to further experiment with these technologies to vivify learning experiences in nearly all courses of study.”

 



 

 

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