Artificial Intelligence/Agents/LLMs/and Related

Introducing several new ideas to provide personalized, customized learning experiences for all kinds of learners! [Christian]

On 11/06/2018, in 21st century, 24x7x365 access, accessibility / UDL, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, attention, blended learning, bots, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, Daniel S. Christian, digital learning, e-books, e-publishing related items (EPUB and more), e-readers, education, education technology, elearning, engagement / engaging students, face-to-face, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), hybrid learning, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interaction design, interactivity, interface design, internet, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning from the Living [Class] Room, learning preferences, library / librarians, memory, more voice more choice more control, neurodivergent/special needs, personalized/customized learning, platforms, productivity / tips and tricks, reading, society, student-related, teachers, teaching & learning, technology (general), tools, traditional / tradition, training / L&D, universities, user experience (UX), user interface design, using teams, vendors, vision/possibilities, visualizing information, writing, youth, by Daniel Christian

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
Or learners that have different physical capabilities or restrictions
Or learners that have different backgrounds and/or levels of prior knowledge
Etc., etc., etc.

Educators and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc. On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples
of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

Show me just the main points
Then add on the sub points
Then fill in the details
OR
Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience.

To recap:

“Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
Publishers create “overlays” or various layers that can be turned on or off by the learners
Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
Can instantly collapse chapters to main ideas/outlines.

“The global companies that failed to adapt to change.” [Rao] | DC: Higher ed likely has something to learn here.

On 11/05/2018, in 21st century, 24x7x365 access, active learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, colleges, community colleges, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, future, future of higher education, game-changing environment, global / globalization, ideas, innovation, intelligent systems, internet, law schools, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, MBA, new business models, organizational change, pace of change, reinvent, society, staying relevant, strategy, student-related, surviving, training / L&D, universities, vendors, vision/possibilities, workplace, by Daniel Christian

The global companies that failed to adapt to change. — from trainingmag.com by Professor M.S. Rao, Ph.D.

Excerpt:

Eastman Kodak, a leader for many years, filed for bankruptcy in 2012. Blockbuster Video became defunct in 2013. Similarly, Borders — one of the largest book retailers in the U.S. — went out of business in 2011. Why did these companies, which once had great brands, ultimately fail? It is because they failed to adapt to change. Additionally, they failed to unlearn and relearn.
…
Former GE CEO Jack Welch once remarked, “If the rate of change on the outside exceeds the rate of change on the inside, the end is near.” Thus, accept change before the change is thrust on you.
…
Leaders must adopt tools and techniques to adapt to change. Here is a blueprint to embrace change effectively:

Keep the vision right and straight, and articulate it effectively.
Create organizational culture conducive to bring about change.
Communicate clearly about the need to change.
Enlighten people about the implications of the status quo.
Show them benefits once the change is implemented.
Coordinate all stakeholders effectively.
Remove the roadblocks by allaying their apprehensions.
Show them small gains to ensure that entire change takes place smoothly without any resistance.

From DSC:
Though I’m not on board with all of the perspectives in that article, institutions of traditional higher education likely have something to learn from the failures of these companies….while there’s still time to change and to innovate.

2 items re: AI’s potential impact/place within education

On 11/03/2018, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, career development, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, Daniel S. Christian, data related items, digital learning, distance education, education, education technology, elearning, future, game-changing environment, global / globalization, higher education, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, internet, IT in HE, languages and translation, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, microlearning, mobile learning, more voice more choice more control, Natural Language Processing (NLP), online learning, online media, organizational change, pace of change, personalized/customized learning, platforms, professional development, reinvent, universities, user experience (UX), using teams, vendors, by Daniel Christian

Robots won’t replace instructors, 2 Penn State educators argue. Instead, they’ll help them be ‘more human.’ — from edsurge.com by Tina Nazerian

Excerpt:

Specifically, it will help them prepare for and teach their courses through several phases—ideation, design, assessment, facilitation, reflection and research. The two described a few prototypes they’ve built to show what that might look like.

Also see:

The future of education: Online, free, and with AI teachers? — from fool.com by Simon Erickson
Duolingo is using artificial intelligence to teach 300 million people a foreign language for free. Will this be the future of education?

Excerpts:

While it might not get a lot of investor attention, education is actually one of America’s largest markets.

The U.S. has 20 million undergraduates enrolled in colleges and universities right now and another 3 million enrolled in graduate programs. Those undergrads paid an average of $17,237 for tuition, room, and board at public institutions in the 2016-17 school year and $44,551 for private institutions. Graduate education varies widely by area of focus, but the average amount paid for tuition alone was $24,812 last year.

Add all of those up, and America’s students are paying more than half a trillion dollars each year for their education! And that doesn’t even include the interest amassed for student loans, the college-branded merchandise, or all the money spent on beer and coffee.

Keeping the costs down
Several companies are trying to find ways to make college more affordable and accessible.

But after we launched, we have so many users that nowadays if the system wants to figure out whether it should teach plurals before adjectives or adjectives before plurals, it just runs a test with about 50,000 people. So for the next 50,000 people that sign up, which takes about six hours for 50,000 new users to come to Duolingo, to half of them it teaches plurals before adjectives. To the other half it teaches adjectives before plurals. And then it measures which ones learn better. And so once and for all it can figure out, ah it turns out for this particular language to teach plurals before adjectives for example.

So every week the system is improving. It’s making itself better at teaching by learning from our learners. So it’s doing that just based on huge amounts of data. And this is why it’s become so successful I think at teaching and why we have so many users.

From DSC:
I see AI helping learners, instructors, teachers, and trainers. I see AI being a tool to help do some of the heavy lifting, but people still like to learn with other people…with actual human beings. That said, a next generation learning platform could be far more responsive than what today’s traditional institutions of higher education are delivering.

Amazon’s new goal: Teach 10 million kids a year to code [Pisani]

On 11/03/2018, in Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, computer science, programming, society, student-related, youth, by Daniel Christian

Amazon’s new goal: Teach 10 million kids a year to code — from businessinsider.com by Joseph Pisani

Excerpt:

NEW YORK (AP) — Amazon wants to get more kids thinking about becoming computer engineers.

The company launched a program Thursday that aims to teach more than 10 million students a year how to code. Amazon said it will pay for summer camps, teacher training and other initiatives to benefit kids and young adults from low-income families who might not have learned to code otherwise. It hopes the programs spur more black, Hispanic and female students to study computer science.

From DSC:
It will be interesting to see how artificial intelligence impacts the demand for programmers as the years progress.

Virtual digital assistants in the workplace: Still nascent, but developing [Brans]

On 11/03/2018, in 21st century, Amazon, Apple, Artificial Intelligence/Agents/LLMs/and Related, bots, business, corporate / business world, emerging technologies, Google, human-computer interaction (HCI), tools, usability, user experience (UX), vendors, workplace, by Daniel Christian

Virtual digital assistants in the workplace: Still nascent, but developing — from cisco.com by Pat Brans
As workers get overwhelmed with daily tasks, they want virtual digital assistants in the workplace that can alleviate some of the burden.

Excerpts:

As life gets busier, knowledge workers are struggling with information overload.

They’re looking for a way out, and that way, experts say, will eventually involve virtual digital assistants (VDAs). Increasingly, workers need to complete myriad tasks, often seemingly simultaneously. And as the pace of business continues to drive ever faster, hands-free, intelligent technology that can speed administrative tasks holds obvious appeal.
…
So far, scenarios in which digital assistants in the workplace enhance productivity fall into three categories: scheduling, project management, and improved interfaces to enterprise applications. “Using digital assistants to perform scheduling has clear benefits,” Beccue said.

“Scheduling meetings and managing calendars takes a long time—many early adopters are able to quantify the savings they get when the scheduling is performed by a VDA. Likewise, when VDAs are used to track project status through daily standup meetings, project managers can easily measure the time saved.”

Perhaps the most important change we’ll see in future generations of VDA technology for workforce productivity will be the advent of general-purpose VDAs that help users with all tasks. These VDAs will be multi-channel (providing interfaces through mobile apps, messaging, telephone, and so on) and they will be bi-modal (enlisting text and voice).

Google already knows what you did next summer [Ekstein]

On 11/03/2018, in analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, data related items, emerging technologies, future, geography / geology, Google, innovation, society, by Daniel Christian

Google already knows what you did next summer — from bloomberg.com by Nikki Ekstein
The company’s new travel tools put the focus on artificial intelligence, helping to best predict what you’re going to love—no matter where you go.

Excerpt:

But it’s not a hotel or travel agency that’s cracking the golden acorn. It’s Google. The tech titan is leveraging its immense artificial intelligence and machine-learning capabilities to boost its travel offerings, which currently cover everything from flight and hotel search to activity recommendations, destination guides, and mapping services

The proof is in the pudding. Over the past few months, Google has quietly launched an array of travel-focused features and updates that highlight just how intuitive its AI technology has become. Put them all together and you’ll have enough reason to believe your next travel agent might just be a Google-powered bot.

Microsoft to tackle AI skills shortage with two new training programs [Heath]

On 10/31/2018, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, computer science, corporate / business world, corporate universities / corporate training, higher education, human-computer interaction (HCI), Microsoft, platforms, programming, tools, workplace, by Daniel Christian

Microsoft to tackle AI skills shortage with two new training programs — from zdnet.com by Nick Heath
The tech giant reveals two new training programs to boost AI-related skills in business and in universities.

Excerpts:

The first of the two programs, Microsoft AI Academy, will run face-to-face and online training sessions for business and public-sector leaders, IT professionals, developers, and startups.
…
Microsoft is also funding a program to help train the next generation of data scientists and machine-learning engineers. Professor Chris Bishop, director of Microsoft’s Research Lab in Cambridge, said the Microsoft Research-Cambridge University Machine Learning Initiative is designed to address the stream of leading machine-learning researchers moving from universities to the private sector.

“Affordable and at-scale” [Schroeder] + “Trends for the future of education with Jeff Selingo” [Steelcase]

On 10/31/2018, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, business side of he, career development, change, colleges, communities of practice, community colleges, computer science, cost of getting a degree, dangers of the status quo, digital learning, disruption, distance education, education, education reform, education technology, emerging technologies, face-to-face, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning spaces, lifelong learning, MOOCs -- Massive Open Online Courses, new business models, online learning, United States, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

Affordable and at-scale — from insidehighered.com by Ray Schroeder
Affordable degrees at scale have arrived. The momentum behind this movement is undeniable, and its impact will be significant, Ray Schroeder writes.

Excerpt (emphasis DSC):

How many times have we been told that major change in our field is on the near horizon? Too many times, indeed.

The promises of technologies and practices have fallen short more often than not. Just seven years ago, I was part of the early MOOC movement and felt the pulsating potential of teaching thousands of students around the world in a single class. The “year of the MOOC” was declared in 2012. Three years later, skeptics declared that the MOOC had died an ignominious death with high “failure” rates and relatively little recognition by employers.

However, the skeptics were too impatient, misunderstood the nature of MOOCs and lacked the vision of those at Georgia Tech, the University of Illinois, Arizona State University, Coursera, edX and scores of other institutions that have persevered in building upon MOOCs’ premises to develop high-quality, affordable courses, certificates and now, degrees at scale.

No, these degrees are not free, but they are less than half the cost of on-campus versions. No, they are not massive in the hundreds of thousands, but they are certainly at large scale with many thousands enrolled. In computer science, the success is felt across the country.

Georgia Tech alone has enrolled 10,000 students over all in its online master’s program and is adding thousands of new students each semester in a top 10-ranked degree program costing less than $7,000. Georgia Tech broke the new ground through building collaborations among several partners. Yet, that was just the beginning, and many leading universities have followed.

Also see:

Trends for the future of education with Jeff Selingo — from steelcase.com
How the future of work and new technology will make place more important than ever.

Excerpt:

Selingo sees artificial intelligence and big data as game changers for higher education. He says AI can free up professors and advisors to spend more time with students by answering some more frequently-asked questions and handling some of the grading. He also says data can help us track and predict student performance to help them create better outcomes. “When they come in as a first-year student, we can say ‘People who came in like you that had similar high school grades and took similar classes ended up here. So, if you want to get out of here in four years and have a successful career, here are the different pathways you should follow.’”

Should self-driving cars have ethics? [Wamsley]

On 10/31/2018, in Artificial Intelligence/Agents/LLMs/and Related, bots, data related items, emerging technologies, ethics, innovation, intelligent systems, morals/values, pace of change, platforms, society, by Daniel Christian

Should self-driving cars have ethics? — from npr.org by Laurel Wamsley

Excerpt:

In the not-too-distant future, fully autonomous vehicles will drive our streets. These cars will need to make split-second decisions to avoid endangering human lives — both inside and outside of the vehicles.

To determine attitudes toward these decisions a group of researchers created a variation on the classic philosophical exercise known as “the Trolley problem.” They posed a series of moral dilemmas involving a self-driving car with brakes that suddenly give out…

Reflections on “Are ‘smart’ classrooms the future?” [Johnston]

On 10/31/2018, in 21st century, A/V -- audio/visual, adjunct faculty, Amazon, Apple, Artificial Intelligence/Agents/LLMs/and Related, attention, blended learning, bots, Bring your own device (BYOD), cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, Daniel S. Christian, design, digital learning, distance education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, future, future of higher education, Google, higher education, human-computer interaction (HCI), hybrid learning, ideas, innovation, internet, IT in HE, law schools, learning, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, machine-to-machine communications, Microsoft, mobile technologies, multimedia, Natural Language Processing (NLP), Near Field Communication (NFC), personalized/customized learning, platforms, productivity / tips and tricks, second screen apps, smart classrooms, social learning / networks, student teaching/teacher education, student-related, tablets, teachers, teaching & learning, technology (general), tools, trends, TVs, United States, usability, user experience (UX), using teams, vendors, videoconferencing, Virtual Reality (VR) / worlds / learning, voice recognition / voice enabled interfaces, wearables, web-based collaboration, XR - extended reality, by Daniel Christian

Are ‘smart’ classrooms the future? — from campustechnology.com by Julie Johnston
Indiana University explores that question by bringing together tech partners and university leaders to share ideas on how to design classrooms that make better use of faculty and student time.

Excerpt:

To achieve these goals, we are investigating smart solutions that will:

Untether instructors from the room’s podium, allowing them control from anywhere in the room;
Streamline the start of class, including biometric login to the room’s technology, behind-the-scenes routing of course content to room displays, control of lights and automatic attendance taking;
Offer whiteboards that can be captured, routed to different displays in the room and saved for future viewing and editing;
Provide small-group collaboration displays and the ability to easily route content to and from these displays; and
Deliver these features through a simple, user-friendly and reliable room/technology interface.

…

Activities included collaborative brainstorming focusing on these questions:

What else can we do to create the classroom of the future?
What current technology exists to solve these problems?
What could be developed that doesn’t yet exist?
What’s next?

From DSC:
Though many peoples’ — including faculty members’ — eyes gloss over when we start talking about learning spaces and smart classrooms, it’s still an important topic. Personally, I’d rather be learning in an engaging, exciting learning environment that’s outfitted with a variety of tools (physically as well as digitally and virtually-based) that make sense for that community of learners. Also, faculty members have very limited time to get across campus and into the classroom and get things setup…the more things that can be automated in those setup situations the better!

I’ve long posted items re: machine-to-machine communications, voice recognition/voice-enabled interfaces, artificial intelligence, bots, algorithms, a variety of vendors and their products including Amazon’s Alexa / Apple’s Siri / Microsoft’s Cortana / and Google’s Home or Google Assistant, learning spaces, and smart classrooms, as I do think those things are components of our future learning ecosystems.

Global installed base of smart speakers to surpass 200 million in 2020, says GlobalData

The global installed base for smart speakers will hit 100 million early next year, before surpassing the 200 million mark at some point in 2020, according to GlobalData, a leading data and analytics company.

The company’s latest report: ‘Smart Speakers – Thematic Research’ states that nearly every leading technology company is either already producing a smart speaker or developing one, with Facebook the latest to enter the fray (launching its Portal device this month). The appetite for smart speakers is also not limited by geography, with China in particular emerging as a major marketplace.

Ed Thomas, Principal Analyst for Technology Thematic Research at GlobalData, comments: “It is only four years since Amazon unveiled the Echo, the first wireless speaker to incorporate a voice-activated virtual assistant. Initial reactions were muted but the device, and the Alexa virtual assistant it contained, quickly became a phenomenon, with the level of demand catching even Amazon by surprise.”

Smart speakers give companies like Amazon, Google, Apple, and Alibaba access to a vast amount of highly valuable user data. They also allow users to get comfortable interacting with artificial intelligence (AI) tools in general, and virtual assistants in particular, increasing the likelihood that they will use them in other situations, and they lock customers into a broader ecosystem, making it more likely that they will buy complementary products or access other services, such as online stores.

Thomas continues: “Smart speakers, particularly lower-priced models, are gateway devices, in that they give consumers the opportunity to interact with a virtual assistant like Amazon’s Alexa or Google’s Assistant, in a “safe” environment. For tech companies serious about competing in the virtual assistant sector, a smart speaker is becoming a necessity, hence the recent entry of Apple and Facebook into the market and the expected arrival of Samsung and Microsoft over the next year or so.”

In terms of the competitive landscape for smart speakers, Amazon was the pioneer and is still a dominant force, although its first-mover advantage has been eroded over the last year or so. Its closest challenger is Google, but neither company is present in the fastest-growing geographic market, China. Alibaba is the leading player there, with Xiaomi also performing well.

Thomas concludes: “With big names like Samsung and Microsoft expected to launch smart speakers in the next year or so, the competitive landscape will continue to fluctuate. It is likely that we will see two distinct markets emerge: the cheap, impulse-buy end of the spectrum, used by vendors to boost their ecosystems; and the more expensive, luxury end, where greater focus is placed on sound quality and aesthetics. This is the area of the market at which Apple has aimed the HomePod and early indications are that this is where Samsung’s Galaxy Home will also look to make an impact.”

Information based on GlobalData’s report: Smart Speakers – Thematic Research

Academics Propose a ‘Blockchain University,’ Where Faculty (and Algorithms) Rule — from edsurge.com by Jeff Young

Excerpt:

A group of academics affiliated with Oxford University have proposed a new model of higher education that replaces traditional administrators with “smart contracts” on the blockchain, the same technology that drives Bitcoin and other cryptocurrencies.

“Our aim is to create a university in which the bulk of administrative tasks are either eliminated or progressively automated,” said the effort’s founders in a white paper released earlier this year. Those proposing the idea added the university would be “a decentralised, non-profit, democratic community in which the use of blockchain technology will provide the contractual stability needed to pursue a full course of study.”

Experiments with blockchain in higher education are underway at multiple campuses around the country, and many of researchers are looking into how to use the technology to verify and deliver credentials. Massachusetts Institute for Technology, for example, began issuing diplomas via blockchain last year.

The plan by Oxford researchers goes beyond digital diplomas—and beyond many typical proposals to disrupt education in general. It argues for a completely new framework for how college is organized, how professors are paid, and how students connect with learning. In other words, it’s a long shot.

But even if the proposed platform never emerges, it is likely to spur debates about whether blockchain technology could one day allow professors to reclaim greater control of how higher education operates through digital contracts.

The platform would essentially allow professors to organize their own colleges, and teach and take payments from students directly. “

Gartner: Immersive experiences among top tech trends for 2019 [Schaffhauser]

On 10/23/2018, in 21st century, A/V -- audio/visual, analytics, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), Blockchain, bots, business, career development, change, cloud-based computing / apps / other cloud-related, computer science, corporate / business world, data related items, emerging technologies, ethics, future, human-computer interaction (HCI), ideas, immersion, innovation, intelligent systems, interaction design, machine-to-machine communications, Mixed Reality (MR), morals/values, Natural Language Processing (NLP), platforms, programming, smart classrooms, society, strategy, technology (general), tools, trends, usability, user experience (UX), vendors, Virtual Reality (VR) / worlds / learning, voice recognition / voice enabled interfaces, workplace, XR - extended reality, by Daniel Christian

Gartner: Immersive experiences among top tech trends for 2019 — from campustechnology.com by Dian Schaffhauser

Excerpt:

IT analyst firm Gartner has named its top 10 trends for 2019, and the “immersive user experience” is on the list, alongside blockchain, quantum computing and seven other drivers influencing how we interact with the world. The annual trend list covers breakout tech with broad impact and tech that could reach a tipping point in the near future.

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

On 10/19/2018, in 21st century, 24x7x365 access, A/V -- audio/visual, Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, colleges, communities of practice, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, distance education, e-books, e-publishing related items (EPUB and more), e-readers, education, education reform, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, future, future of higher education, game-changing environment, generational differences, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interactivity, internet, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, library / librarians, lifelong learning, microlearning, mobile learning, MOOCs -- Massive Open Online Courses, more voice more choice more control, multimedia, Natural Language Processing (NLP), new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, reinvent, second screen apps, social learning / networks, society, staying relevant, streams of content, student-related, surviving, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vision/possibilities, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

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.

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.

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