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.

 

 

 

What will be important in the learn and work ecosystem in 2030? How do we prepare? — from evolllution.com by Holly Zanville | Senior Advisor for Credentialing and Workforce Development, Lumina Foundation

Excerpt:

These seven suggested actions—common to all scenarios—especially resonated with Lumina:

  1. Focus on learning: All learners will need a range of competencies and skills, most critically: learning how to learn; having a foundation in math, science, IT and cross-disciplines; and developing the behaviors of grit, empathy and effective communication.
  2. Prepare all “systems”: Schools will continue to be important places to teach competencies and skills. Parents will be important teachers for children. Workplaces will also be important places for learning, and many learners will need instruction on how to work effectively as part of human/machine teams.
  3. Integrate education and work: Education systems will need to be integrated with work in an education/work ecosystem. To enable movement within the ecosystem, credentials will be useful, but only if they are transparent and portable. The competencies and skills that stand behind credentials will need to be identifiable, using a common language to enable (a) credential providers to educate/train for an integrated education/work system; (b) employers to hire people and upgrade their skills; and (c) governments (federal/state/local) to incentivize and regulate programs and policies that support the education/work system.
  4. Assess learning: Assessing competencies and skills acquired in multiple settings and modes (including artificial reality and virtual reality tools), will be essential. AI will enable powerful new assessment tools to collect and analyze data about what humans know and can do.
  5. Build fair, moral AI: There will be a high priority on ensuring that AI has built-in checks and balances that reflect moral values and honor different cultural perspectives.
  6. Prepare for human/machine futures: Machines will join humans in homes, schools and workplaces. Machines will likely be viewed as citizens with rights. Humans must prepare for side-by-side “relationships” with machines, especially in situations in which machines will be managing aspects of education, work and life formerly managed by humans. Major questions will also arise about the ownership of AI structures—what ownership looks like, and who profits from ubiquitous AI structures.
  7. Build networks for readiness/innovation: Open and innovative partnerships will be needed for whatever future scenarios emerge. In a data-rich world, we won’t solve problems alone; networks, partnerships and communities will be key.

 

 

Also see:

 

 

Three shifts as big as print to digital — from gettingsmart.com by Tom Vander Ark

Excerpts (emphasis DSC):

We just lived through the biggest shift in learning since the printing press—a 25-year shift from print to digital. While it extended access and options to billions, it didn’t prove as transformational as many of us expected. It did, however, set the stage for three shifts that will change what and how people learn.

  1. Basic to broader aims.
  2. Passive to active learning.
  3. Time to demonstrated learning.

 

 

 
 

What does the Top Tools for Learning 2018 list tell us about the future direction of L&D? — from modernworkplacelearning.com by Jane Hart

Excerpt:

But for me 3 key things jump out:

  1. More and more people are learning for themselves – in whatever way that suits them best – whether it is finding resources or online courses on the Web or interacting with their professional network. And they do all this for a variety of reasons: to solve problems, self-improve and prepare themselves for the future, etc.
  2. Learning at work is becoming more personal and continuous in that it is a key part of many professional’s working day. And what’s more people are not only organising their own learning activities, they are also indeed managing their own development too – either with (informal) digital notebooks, or with (formal) personal learning platforms.
  3. But it is in team collaboration where most of their daily learning takes place, and many now recognise and value the social collaboration platforms that underpin their daily interactions with colleagues as part of their daily work.

In other words, many people now see workplace learning as not just something that happens irregularly in corporate training, but as a continuous and on demand activity.

 


From DSC:
Reminds me of tapping into — and contributing towards — streams of content. All the time. Continuous, lifelong learning.

 

 


 

 

 

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…?

 

 

 

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.

 


 

 

How professionals learn for work — from jarche.com by Harold Jarche

Excerpt:

On the image below the methods are colour-coded to Experience (70%), Exposure (20%), and Education (10%). The size of text indicates the importance as ranked by the survey respondents. Note that some of these methods cross boundaries, such as team knowledge sharing & conferences.

 

 

Also see:

 

Training strategies should consider the reality of how people learn; content should always be available remotely – increasingly via mobile – and at the learner’s convenience in bite-sized chunks, making use of video, gamification and collaboration.

 

 

 

50 Twitter accounts lawyers should follow — from postali.com

Excerpt:

Running a successful law practice is about much more than being an excellent attorney. A law firm is a business, and those who stay informed on trends in legal marketing, business development and technology are primed to run their practice more efficiently.

Law firms are a competitive business. In order to stay successful, you need to stay informed. The industry trends can often move at lightning speed, and you want to be ahead of them.

Twitter is a great place for busy attorneys to stay informed. Many thought leaders in the legal industry are eager and willing to share their knowledge in digestible, 280-character tweets that lawyers on-the-go can follow.

We’ve rounded up some of the best Twitter accounts for lawyers (in no particular order.) To save you even more time, we’ve also added all of these account to a Twitter List that you can follow with one click. (You can use some of the time you’ll save to follow Postali on Twitter as well.)

Click here to view the Twitter List of Legal Influencers.

 

 

From DSC:
I find Twitter to be an excellent source of learning, and it is one of the key parts of my own learning ecosystem. I’m not the only one. Check out these areas of Jane Hart’s annual top tools for learning.

Twitter is in the top 10 lists for learning tools no matter whether you are looking at education, workplace learning, and/or for personal and professional learning

 

 

 


Also see/relevant:

  • Prudenti: Law schools facing new demands for innovative education— from libn.com
    Excerpt:
    Law schools have always taught the law and the practice thereof, but in the 21st century that is not nearly enough to provide students with the tools to succeed. Clients, particularly business clients, are not only looking for an “attorney” in the customary sense, but a strategic partner equipped to deal with everything from project management to metrics to process enhancement. Those demands present law schools with both an opportunity for and expectation of innovation in legal education.

 

 

 

A more strategic approach to arranging students into groups — from facultyfocus.com by Maryellen Weimer

Excerpt:

What’s the best way to put students into groups? It’s the first task that confronts teachers who want students to work together. And the best reply is one of those “it depends” answers. Here are the questions on which it depends.

 

If the group work is a project that requires extended collaboration and will benefit from a variety of opinions and perspectives, letting students form the groups may not be the best approach. On the other hand, for short, ad-hoc group work and for students who may be shy and not used to working with peers, knowing others in the group makes the experience less intimidating.

 

If one of the goals of the group work is getting students acquainted with others in the course or providing the experience of learning to work with peers they don’t know (which frequently occurs in professional contexts), then teachers should consider forming the groups.

 

What criteria should teachers use when forming groups? There’s a range of options. Here’s some of the more common criteria.

  • No criteria
  • Ability
  • Personality traits
  • Skills and experiences

 

 

 

Can we design online learning platforms that feel more intimate than massive? — from edsurge.com by Amy Ahearn

Excerpt:

This presents a challenge and an opportunity: How can we design online learning environments that achieve scale and intimacy? How do we make digital platforms feel as inviting as well-designed physical classrooms?

The answer may be that we need to balance massiveness with miniaturization. If the first wave of MOOCs was about granting unprecedented numbers of students access to high-quality teaching and learning materials, Wave 2 needs to focus on creating a sense of intimacy within that massiveness.

We need to be building platforms that look less like a cavernous stadium and more like a honeycomb. This means giving people small chambers of engagement where they can interact with a smaller, more manageable and yet still diverse groups. We can’t meaningfully listen to the deafening roar of the internet. But we can learn from a collection of people with perspectives different than ours.

 

 

What will it take to get MOOC platforms to begin to offer learning spaces that feel more inviting and intimate? Perhaps there’s a new role that needs to emerge in the online learning ecosystem: a “learning architect” who sits between the engineers and the instructional designers.

 

 

 

 

 

 

What is a learning ecosystem? And how does it support corporate strategy? — from ej4.com by Ryan Eudy

Excerpt:

learning ecosystem is a system of people, content, technology, culture, and strategy, existing both within and outside of an organization, all of which has an impact on both the formal and informal learning that goes on in that organization.

The word “ecosystem” is worth paying attention to here. It’s not just there to make the term sound fancy or scientific. A learning ecosystem is the L&D equivalent of an ecosystem out in the wild. Just as a living ecosystem has many interacting species, environments, and the complex relationships among them, a learning ecosystem has many people and pieces of content, in different roles and learning contexts, and complex relationships.

Just like a living ecosystem, a learning ecosystem can be healthy or sick, nurtured or threatened, self-sustaining or endangered. Achieving your development goals, then, requires an organization to be aware of its own ecosystem, including its parts and the internal and external forces that shape them.

 

From DSC:
Yes, to me, the concept/idea of a learning ecosystem IS important. Very important. So much so, I named this blog after it.

Each of us as individuals have a learning ecosystem, whether we officially recognize it or not. So do the organizations that we work for. And, like an ecosystem out in nature, a learning ecosystem is constantly morphing, constantly changing.

We each have people in our lives that help us learn and grow, and the people that were in our learning ecosystems 10 years ago may or may not still be in our current learning ecosystems. Many of us use technologies and tools to help us learn and grow. Then there are the spaces where we learn — both physical and virtual spaces. Then there are the processes and procedures we follow, formally and/or informally. Any content that helps us learn and grow is a part of that ecosystem. Where we get that content can change, but obtaining up-to-date content is a part of our learning ecosystems. I really appreciate streams of content in this regard — and tapping into blogs/websites, especially via RSS feeds and Feedly (an RSS aggregator that took off when Google Reader left the scene).

The article brings up a good point when it states that a learning ecosystem can be “healthy or sick, nurtured or threatened, self-sustaining or endangered.” That’s why I urge folks to be intentional about maintaining and, better yet, consistently enhancing their learning ecosystems. In this day and age where lifelong learning is now a requirement to remain in the workforce, each of us needs to be intentional in this regard.

 

 
 

With great tech success, comes even greater responsibility — from techcrunch.com by Ron Miller

Excerpts:

As we watch major tech platforms evolve over time, it’s clear that companies like Facebook, Apple, Google and Amazon (among others) have created businesses that are having a huge impact on humanity — sometimes positive and other times not so much.

That suggests that these platforms have to understand how people are using them and when they are trying to manipulate them or use them for nefarious purposes — or the companies themselves are. We can apply that same responsibility filter to individual technologies like artificial intelligence and indeed any advanced technologies and the impact they could possibly have on society over time.

We can be sure that Twitter’s creators never imagined a world where bots would be launched to influence an election when they created the company more than a decade ago. Over time though, it becomes crystal clear that Twitter, and indeed all large platforms, can be used for a variety of motivations, and the platforms have to react when they think there are certain parties who are using their networks to manipulate parts of the populace.

 

 

But it’s up to the companies who are developing the tech to recognize the responsibility that comes with great economic success or simply the impact of whatever they are creating could have on society.

 

 

 

 

Why the Public Overlooks and Undervalues Tech’s Power — from morningconsult.com by Joanna Piacenza
Some experts say the tech industry is rapidly nearing a day of reckoning

Excerpts:

  • 5% picked tech when asked which industry had the most power and influence, well behind the U.S. government, Wall Street and Hollywood.
  • Respondents were much more likely to say sexual harassment was a major issue in Hollywood (49%) and government (35%) than in Silicon Valley (17%).

It is difficult for Americans to escape the technology industry’s influence in everyday life. Facebook Inc. reports that more than 184 million people in the United States log on to the social network daily, or roughly 56 percent of the population. According to the Pew Research Center, nearly three-quarters (73 percent) of all Americans and 94 percent of Americans ages 18-24 use YouTube. Amazon.com Inc.’s market value is now nearly three times that of Walmart Inc.

But when asked which geographic center holds the most power and influence in America, respondents in a recent Morning Consult survey ranked the tech industry in Silicon Valley far behind politics and government in Washington, finance on Wall Street and the entertainment industry in Hollywood.

 

 

 

 

Faculty Learning Communities: Making the Connection, Virtually — from by Angela Atwell, Cristina Cottom, Lisa Martino, and Sara Ombres

Excerpt (emphasis DSC):

Research has shown that interactions with peers promotes faculty engagement (McKenna, Johnson, Yoder, Guerra, & Pimmel, 2016). Faculty learning communities (FLC) have become very popular in recent years. FLCs focus on improving teaching and learning practice through collaboration and community building (Cox, 2001). Usually, FLCs are face-to-face meetings hosted at a physical location at a specific date and time. We understand the benefit of this type of experience. However, we recognize online instructors will likely find it difficult to participate in a traditional FLC. So, we set out to integrate FLC principles to provide our faculty, living and working all over the globe, a similar experience.

Recently, our Center for Teaching and Learning Excellence took the plunge and offered a Virtual Faculty Learning Community (V-FLC) for instructors at our Worldwide Campus. The first experience was open only to adjunct instructors teaching online. The experience was asynchronous, lasted eight weeks, and focused on best practices for online teaching and learning. Within our Learning Management System, faculty led and participated in discussions around the topics that were of interest to them. Most topics focused on teaching practices and ways to enhance the online experience. However, other topics bridged the gap between teaching online and general best teaching practices. 

 

 

 

Looking for something?

Use the form below to search the site:

Still not finding what you're looking for? Drop a comment on a post or contact us so we can take care of it!

© 2019 | Daniel Christian