Amazon’s Alexa passes 15,000 skills, up from 10,000 in February — from techcrunch.com by Sarah Perez

Excerpt:

Amazon’s Alexa voice platform has now passed 15,000 skills — the voice-powered apps that run on devices like the Echo speaker, Echo Dot, newer Echo Show and others. The figure is up from the 10,000 skills Amazon officially announced back in February, which had then represented a 3x increase from September.

The new 15,000 figure was first reported via third-party analysis from Voicebot, and Amazon has now confirmed to TechCrunch that the number is accurate.

According to Voicebot, which only analyzed skills in the U.S., the milestone was reached for the first time on June 30, 2017. During the month of June, new skill introductions increased by 23 percent, up from the less than 10 percent growth that was seen in each of the prior three months.

The milestone also represents a more than doubling of the number of skills that were available at the beginning of the year, when Voicebot reported there were then 7,000 skills. That number was officially confirmed by Amazon at CES.

 

 


From DSC:
Again, I wonder…what are the implications for learning from this new, developing platform?


 

 

From DSC:
I thought the article below was a good one. But I’m not sure I arrived at the same conclusion. Rather than putting the business of leadership & development training squarely on the shoulders of team leaders, I would put it on each individual employee and inform/empower them to seek out what works best for them in fulfilling their role.  

The L&D team can work with introducing the best tools and examples of streams of content to tap into for any given role or topic.

I’m thinking here of tools like Twitter, streams of content from LinkedIn or from relevant blogs and websites. The team leaders can follow up with their team members and check in with them to see how things are going. If an employee says, “I don’t know who to connect with or follow” then perhaps the team leader can say, I’ve found these particular people, blogs, websites, streams of content from LinkedIn (or other sources) to be effective for what we do within our organization. Introduce them to communities of practice and/or to other individuals that do X, Y or Z really well.

It brings in the social element that this article discusses, but it also serves each individual’s best interests — each one of us needs to know how and where to keep learning. If it’s in their best interests to keep learning, then give them the tools and potential streams of content to tap into. Give them:

 

 

Let them own it. They’re likely creating their own learning pathways anyway. L&D become a consulting organization. L&D can consult with each group (or even individual employees) re: potential streams of content and possible/effective connections for that group (or individual).

 



Revive.  — from revive.zaglearning.com

How enterprise learning for leadership and team development is tripping up human potential, and slowly sending the L&D brand into irrelevance. This is the story of how to save it, step by radical step.

Excerpts:

Over 18 months of research with 65 one-on-one interviews, 511 managers surveyed, and 900 teams representing 8K people, we witnessed the unintentional damage: marginalized learning and development people (L&D), learners who see leadership and team development as a necessary but random and usually disappointing transaction, and executives who line-item “soft skills” training (labeled decades ago by, no surprise, a hard-skills proponent) as a tax or necessary benefit, as if it were a dental plan.

If you’re curious, it can’t help but spark a few questions:

  • How can something so strategically important be so realistically unimportant?
  • How did L&D pros, who make such a compelling psychological and organizational case for the most pivotal kind of learning, get so minimized and, in the process, drag down human potential and the social intelligence of corporate culture?
  • How are smart, passionate L&D people who are in it for the greater good—and not the big payday—getting stuck with a brand that’s as sexy as K-Mart?

The problems are systemic, and the curiosity and ambition to fix them have received as little attention as any problem in enterprise history.

 

So, what’s the big switch? Learning for leadership and team development doesn’t belong with L&D. It belongs squarely with the team leader, the person who is 70% of the variance in her team’s engagement. Learning belongs fundamentally, not loosely, where it’s always in context and relevant: the leader and her team.

 

 

 

Google is turning Street View imagery into pro-level landscape photographs using artificial intelligence — from businessinsider.com by Edoardo Maggio

Excerpt:

A new experiment from Google is turning imagery from the company’s Street View service into impressive digital photographs using nothing but artificial intelligence (AI).

Google is using machine learning algorithms to train a deep neural network to roam around places such as Canada’s and California’s national parks, look for potentially suitable landscape images, and then work on them with special post-processing techniques.

The idea is to “mimic the workflow of a professional photographer,” and to do so Google is relying on so-called generative adversarial networks (GAN), which essentially pit two neural networks against one another.

 

See also:

Using Deep Learning to Create Professional-Level Photographs — from research.googleblog.com by Hui Fang, Software Engineer, Machine Perception

 

 

Want to Build a Culture of Learning? You Need to Embrace Failure — from learning.linkedin.com by Paul Petrone

Excerpt:

Six questions that determine how your company really feels about failure
It’s great to say your company welcomes people experimenting and failing. But does that actually happen in practice?

To assess how your company really feels about failure, Andreatta suggests asking yourself these six questions about your culture:

  • Do people admit when they don’t know something or ask for help?
  • What happens when someone makes a mistake or fails? Are they teased or shamed or are they encouraged to look at what happened and try again?
  • When people make mistakes or challenge ideas, do they ultimately get sidelined, demoted or red?
  • Do people admit their mistakes and take responsibility for fixing them or do they blame others?
  • Do managers and leaders share stories of how they took risks or recovered from a failure?

 

“All of the amazing training programs in the world won’t help if people don’t feel safe enough to stretch and grow,” Andreatta said.

 

 

 

Amazon relaunches Inspire after a year of re-tooling — from edscoop.com/ by Emily Tate
The content repository offers tens of thousands of downloadable educational resources. The “upload and share” feature is expected to follow soon.

Excerpts:

More than a year after Amazon debuted — and then suddenly retracted — its free library of open educational resources, Amazon Inspire is back.

The content repository — seen by many as Amazon’s first major attempt to edge into the competitive education technology space that tech giants like Google and Microsoft now comfortably occupy — was quietly reintroduced to educators on Monday [7/17/17] as a way to store and find tens of thousands of downloadable educational materials that teachers can use in their classrooms.

Over the last year, groups across the country have been working with Amazon to vet digital content to ensure it complies with state standards, quality indicators and, perhaps most importantly, intellectual property and copyright laws.

Similarly, if you want to teach a lesson on Romeo and Juliet, for example, you could search Inspire by grade, subject, content format and standards to begin pulling “ingredients,” or resources, off the shelves and putting them in your “grocery cart,” or your collection.

 

 

 

 

 

 

Robots and AI are going to make social inequality even worse, says new report — from theverge.com by
Rich people are going to find it easier to adapt to automation

Excerpt:

Most economists agree that advances in robotics and AI over the next few decades are likely to lead to significant job losses. But what’s less often considered is how these changes could also impact social mobility. A new report from UK charity Sutton Trust explains the danger, noting that unless governments take action, the next wave of automation will dramatically increase inequality within societies, further entrenching the divide between rich and poor.

The are a number of reasons for this, say the report’s authors, including the ability of richer individuals to re-train for new jobs; the rising importance of “soft skills” like communication and confidence; and the reduction in the number of jobs used as “stepping stones” into professional industries.

For example, the demand for paralegals and similar professions is likely to be reduced over the coming years as artificial intelligence is trained to handle more administrative tasks. In the UK more than 350,000 paralegals, payroll managers, and bookkeepers could lose their jobs if automated systems can do the same work.

 

Re-training for new jobs will also become a crucial skill, and it’s individuals from wealthier backgrounds that are more able to do so, says the report. This can already be seen in the disparity in terms of post-graduate education, with individuals in the UK with working class or poorer backgrounds far less likely to re-train after university.

 

 

From DSC:
I can’t emphasize this enough. There are dangerous, tumultuous times ahead if we can’t figure out ways to help ALL people within the workforce reinvent themselves quickly, cost-effectively, and conveniently. Re-skilling/up-skilling ourselves is becoming increasingly important. And I’m not just talking about highly-educated people. I’m talking about people whose jobs are going to be disappearing in the near future — especially people whose stepping stones into brighter futures are going to wake up to a very different world. A very harsh world.

That’s why I’m so passionate about helping to develop a next generation learning platform. Higher education, as an industry, has some time left to figure out their part/contribution out in this new world. But the window of time could be closing, as another window of opportunity / era could be opening up for “the next Amazon.com of higher education.”

It’s up to current, traditional institutions of higher education as to how much they want to be a part of the solution. Some of the questions each institution ought to be asking are:

  1. Given our institutions mission/vision, what landscapes should we be pulse-checking?
  2. Do we have faculty/staff/members of administration looking at those landscapes that are highly applicable to our students and to their futures? How, specifically, are the insights from those employees fed into the strategic plans of our institution?
  3. What are some possible scenarios as a result of these changing landscapes? What would our response(s) be for each scenario?
  4. Are there obstacles from us innovating and being able to respond to the shifting landscapes, especially within the workforce?
  5. How do we remove those obstacles?
  6. On a scale of 0 (we don’t innovate at all) to 10 (highly innovative), where is our culture today? Where do we hope to be 5 years from now? How do we get there?

…and there are many other questions no doubt. But I don’t think we’re looking into the future nearly enough to see the massive needs — and real issues — ahead of us.

 

 

The report, which was carried out by the Boston Consulting Group and published this Wednesday [7/12/17], looks specifically at the UK, where it says some 15 million jobs are at risk of automation. But the Sutton Trust says its findings are also relevant to other developed nations, particularly the US, where social mobility is a major problem.

 

 

 

 

Career Pathways: Five Ways to Connect College and Careers calls for states to help students, their families, and employers unpack the meaning of postsecondary credentials and assess their value in the labor market.

Excerpt:

If students are investing more to go to college, they need to have answers to basic questions about the value of postsecondary education. They need better information to make decisions that have lifelong economic consequences.

Getting a college education is one of the biggest investments people will make in their lives, but the growing complexity of today’s economy makes it difficult for higher education to deliver efficiency and consistent quality. Today’s economy is more intricate than those of decades past.

 

From this press release:

It’s Time to Fix Higher Education’s Tower of Babel, Says Georgetown University Report
The lack of transparency around college and careers leads to costly, uninformed decisions

(Washington, D.C., July 11, 2017) — A new report from the Georgetown University Center on Education and the Workforce (Georgetown Center), Career Pathways: Five Ways to Connect College and Careers, calls for states to help students, their families, and employers unpack the meaning of postsecondary credentials and assess their value in the labor market.

Back when a high school-educated worker could find a good job with decent wages, the question was simply whether or not to go to college. That is no longer the case in today’s economy, which requires at least some college to enter the middle class. The study finds that:

  • The number of postsecondary programs of study more than quintupled between 1985 and 2010 — from 410 to 2,260;
  • The number of colleges and universities more than doubled from 1,850 to 4,720 between 1950 and 2014; and
  • The number of occupations grew from 270 in 1950 to 840 in 2010.

The variety of postsecondary credentials, providers, and online delivery mechanisms has also multiplied rapidly in recent years, underscoring the need for common, measurable outcomes.

College graduates are also showing buyer’s remorse. While they are generally happy with their decision to attend college, more than half would choose a different major, go to a different college, or pursue a different postsecondary credential if they had a chance.

The Georgetown study points out that the lack of information drives the higher education market toward mediocrity. The report argues that postsecondary education and training needs to be more closely aligned to careers to better equip learners and workers with the skills they need to succeed in the 21st century economy and close the skills gap.

The stakes couldn’t be higher for students to make the right decisions. Since 1980, tuition and fees at public four year colleges and universities have grown 19 times faster than family incomes. Students and families want — and need — to know the value they are getting for their investment.

 

 



Also see:

  • Trumping toward college transparency — from linkedin.com by Anthony Carnevale
    The perfect storm is gathering around the need to increase transparency around college and careers. And in accordance with how public policy generally comes about, it might just happen. 


 

 

 

AI is making it extremely easy for students to cheat — from wired.com by Pippa Biddle

Excerpt (emphasis DSC):

For years, students have turned to CliffsNotes for speedy reads of books, SparkNotes to whip up talking points for class discussions, and Wikipedia to pad their papers with historical tidbits. But today’s students have smarter tools at their disposal—namely, Wolfram|Alpha, a program that uses artificial intelligence to perfectly and untraceably solve equations. Wolfram|Alpha uses natural language processing technology, part of the AI family, to provide students with an academic shortcut that is faster than a tutor, more reliable than copying off of friends, and much easier than figuring out a solution yourself.

 

Use of Wolfram|Alpha is difficult to trace, and in the hands of ambitious students, its perfect solutions are having unexpected consequences.

 

 

 

 

McKinsey’s State Of Machine Learning & AI, 2017 — from forbes.com by Louis Columbus

Excerpts:

These and other findings are from the McKinsey Global Institute Study, and discussion paper, Artificial Intelligence, The Next Digital Frontier (80 pp., PDF, free, no opt-in) published last month. McKinsey Global Institute published an article summarizing the findings titled   How Artificial Intelligence Can Deliver Real Value To Companies. McKinsey interviewed more than 3,000 senior executives on the use of AI technologies, their companies’ prospects for further deployment, and AI’s impact on markets, governments, and individuals.  McKinsey Analytics was also utilized in the development of this study and discussion paper.

 

Video: 4 FAQs about Watson as tutor — from er.educause.edu by Satya Nitta

Excerpt:

How is IBM using Watson’s intelligent tutoring system? So we are attempting to mimic the best practices of human tutoring. The gold standard will always remain one on one human to human tutoring. The whole idea here is an intelligent tutoring system as a computing system that works autonomously with learners, so there is no human intervention. It’s basically pretending to be the teacher itself and it’s working with the learner. What we’re attempting to do is we’re attempting to basically put conversational systems, systems that understand human conversation and dialogue, and we’re trying to build a system that, in a very natural way, interacts with people through conversation. The system basically has the ability to ask questions, to answer questions, to know who you are and where you are in your learning journey, what you’re struggling with, what you’re strong on and it will personalize its pedagogy to you.

There’s a natural language understanding system and a machine learning system that’s trying to figure out where you are in your learning journey and what the appropriate intervention is for you. The natural language system enables this interaction that’s very rich and conversation-based, where you can basically have a human-like conversation with it and, to a large extent, it will try to understand and to retrieve the right things for you. Again the most important thing is that we will set the expectations appropriately and we have appropriate exit criteria for when the system doesn’t actually understand what you’re trying to do.

 

 

 
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