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).

 

 

 

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:

 

 

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

Excerpt:

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

 

In a world where machines may have an IQ of 50,000 and the Internet of Things may encompass 500 billion devices, what will happen with those important social contracts, values and ethics that underpin crucial issues such as privacy, anonymity and free will?

 

 

My book identifies what I call the “Megashifts”. They are changing society at warp speed, and your organisations are in the eye of the storm: digitization, mobilisation and screenification, automation, intelligisation, disintermediation, virtualisation and robotisation, to name the most prominent. Megashifts are not simply trends or paradigm shifts, they are complete game changers transforming multiple domains simultaneously.

 

 

If the question is no longer about if technology can do something, but why…who decides this?

Gerd Leonhard

 

 

From DSC:
Though this letter was written 2 years ago back in October of 2016, the messages, reflections, and questions that Gerd puts on the table are very much still relevant today.  The leaders of these powerful companies have enormous power — power to do good, or to do evil. Power to help or power to hurt. Power to be a positive force for societies throughout the globe and to help create dreams, or power to create dystopian societies while developing a future filled with nightmares. The state of the human heart is extremely key here — though many will hate me saying that. But it’s true. At the end of the day, we need to very much care about — and be extremely aware of — the characters and values of the leaders of these powerful companies. 

 

 

Also relevant/see:

Spray-on antennas will revolutionize the Internet of Things — from networkworld.com by Patrick Nelson
Researchers at Drexel University have developed a method to spray on antennas that outperform traditional metal antennas, opening the door to faster and easier IoT deployments.

 From DSC:
Again, it’s not too hard to imagine in this arena that technologies can be used for good or for ill.

 

 
 

The 11 coolest announcements Google made at its biggest product event of the year — from businessinsider.com by Dave Smith

Excerpt:

On Tuesday (10/9), Google invited journalists to New York City to debut its newest smartphone, the Pixel 3, among several other hardware goodies.

Google made dozens of announcements in its 75-minute event, but a handful of “wow” moments stole the show.

Here are the 11 coolest announcements Google made at its big hardware event…

 

 

 

Google’s Pixel 3 event in 6 minutes — from businessinsider.com

 

 

Google unveiled its new Home Hub but it might be ‘late to the market’ — from barrons.com by Emily Bary

Excerpt:

Alphabet ’s Google has sold millions of voice-enabled speakers, but it inched toward the future at a Tuesday launch event when it introduced the Home Hub smart screen.

Google isn’t the first company to roll out a screen-enabled home device with voice-assistant technology— Amazon.com released its Echo Show in July 2017. Meanwhile, Lenovo has gotten good reviews for its Smart Display, and Facebook introduced the Portal on Monday.

For the most part, though, consumers have stuck to voice-only devices, and it will be up to Google and its rivals to convince them that an added screen is worth paying for. They’ll also have to reassure consumers that they can trust big tech to maintain their privacy, an admittedly harder task these days after recent security issues at Google and Facebook.

 

Amazon was right to realize early on that consumers aren’t always comfortable buying items they can’t even see pictures of, and that it’s hard to remember directions you’ve heard but not seen.

 

 

Google has announced its first smart speaker with a screen — from businessinsider.com by Brandt Ranj

  • Google has announced the Google Hub, its first smart home speaker with a screen. It’s available for pre-order at Best Buy, Target, and Walmart for $149. The Hub will be released on October 22.
  • The Hub has a 7″ touchscreen and sits on a base with a built-in speaker and microphones, which you can use to play music, watch videos, get directions, and control smart home accessories with your voice.
  • Its biggest advantage is its ability to hook into Google’s first-party services, like YouTube and Google Maps, which none of its competitors can use.
  • If you’re an Android or Chromecast user, trust Google more than Amazon, or want a smaller smart home speaker with a screen, the Google Hub is now your best bet.

 

 

Google is shutting down Google+ for consumers following security lapse — from theverge.com by Ashley Carman

Excerpt:

Google is going to shut down the consumer version of Google+ over the next 10 months, the company writes in a blog post today. The decision follows the revelation of a previously undisclosed security flaw that exposed users’ profile data that was remedied in March 2018.

 

 

Google shutters Google+ after users’ personal data exposed — from cbsnews.com

 

 

Google+ is shutting down, and the site’s few loyal users are mourning – from cnbc.com by Jillian D’Onfro

  • Even though Google had diverted resources away from Google+, there’s a small loyal base of users devastated to see it go away.
  • One fan said the company is using its recently revealed security breach as an excuse to shutter the site.
  • Google said it will be closing Google+ in the coming months.

 

 

 

This is how the Future Today Institute researches, models & maps the future & develops strategies

 

This is how the Future Today Institute researches, models & maps the future & develops strategies

 

Also see what the Institute for the Future does in this regard

Foresight Tools
IFTF has pioneered tools and methods for building foresight ever since its founding days. Co-founder Olaf Helmer was the inventor of the Delphi Method, and early projects developed cross-impact analysis and scenario tools. Today, IFTF is methodologically agnostic, with a brimming toolkit that includes the following favorites…

 

 

From DSC:
How might higher education use this foresight workflow? How might we better develop a future-oriented mindset?

From my perspective, I think that we need to be pulse-checking a variety of landscapes, looking for those early signals. We need to be thinking about what should be on our radars. Then we need to develop some potential scenarios and strategies to deal with those potential scenarios if they occur. Graphically speaking, here’s an excerpted slide from my introductory piece for a NGLS 2017 panel that we did.

 

 

 

This resource regarding their foresight workflow was mentioned in  a recent e-newsletter from the FTI where they mentioned this important item as well:

  • Climate change: a megatrend that impacts us all
    Excerpt:
    Earlier this week, the United Nations’ scientific panel on climate change issued a dire report [PDF]. To say the report is concerning would be a dramatic understatement. Models built by the scientists show that at our current rate, the atmosphere will warm as much as 1.5 degrees Celsius, leading to a dystopian future of food shortages, wildfires, extreme winters, a mass die-off of coral reefs and more –– as soon as 2040. That’s just 20 years away from now.

 

But China also decided to ban the import of foreign plastic waste –– which includes trash from around the U.S. and Europe. The U.S. alone could wind up with an extra 37 million metric tons of plastic waste, and we don’t have a plan for what to do with it all.

 

Immediate Futures Scenarios: Year 2019

  • Optimistic: Climate change is depoliticized. Leaders in the U.S., Brazil and elsewhere decide to be the heroes, and invest resources into developing solutions to our climate problem. We understand that fixing our futures isn’t only about foregoing plastic straws, but about systemic change. Not all solutions require regulation. Businesses and everyday people are incentivized to shift behavior. Smart people spend the next two decades collaborating on plausible solutions.
  • Pragmatic: Climate change continues to be debated, while extreme weather events cause damage to our power grid, wreak havoc on travel, cause school cancellations, and devastate our farms. The U.S. fails to work on realistic scenarios and strategies to combat the growing problem of climate change. More countries elect far-right leaders, who shun global environmental accords and agreements. By 2029, it’s clear that we’ve waited too long, and that we’re running out of time to adapt.
  • Catastrophic: A chorus of voices calling climate change a hoax grows ever louder in some of the world’s largest economies, whose leaders choose immediate political gain over longer-term consequences. China builds an environmental coalition of 100 countries within the decade, developing both green infrastructure while accumulating debt service. Beijing sets global standards emissions––and it locks the U.S out of trading with coalition members. Trash piles up in the U.S., which didn’t plan ahead for waste management. By 2040, our population centers have moved inland and further north, our farms are decimated, our lives are miserable.

Watchlist: United Nations’ Intergovernmental Panel on Climate Change; European Geosciences Union; National Oceanic and Atmospheric Administration (NOAA); NASA; Department of Energy; Department of Homeland Security; House Armed Services Sub-committee on Emerging Threats and Capabilities; Environmental Justice Foundation; Columbia University’s Earth Institute; University of North Carolina at Wilmington; Potsdam Institute for Climate Impact Research; National Center for Atmospheric Research.

 

Jarvish’s smart motorcycle helmets will offer Alexa and Siri support and an AR display

 

Jarvish’s smart motorcycle helmets will offer Alexa and Siri support and an AR display — from the verge.com by Chaim Gartenberg

Excerpt:

The Jarvish X is the more basic of the two models. It offers integrated microphones and speakers for Siri, Google Assistant, and Alexa support so wearers have access things like directions, weather updates, and control music through voice control. There’s also a 2K, front-facing camera built into the helmet so you can record your ride. It’s set to cost $799 when it hits Kickstarter in January.

 

 

 

10 jobs that are safe in an AI world — from linkedin.com by Kai-Fu Lee

Excerpts:

Teaching
AI will be a great tool for teachers and educational institutions, as it will help educators figure out how to personalize curriculum based on each student’s competence, progress, aptitude, and temperament. However, teaching will still need to be oriented around helping students figure out their interests, teaching students to learn independently, and providing one-on-one mentorship. These are tasks that can only be done by a human teacher. As such, there will still be a great need for human educators in the future.

Criminal defense law
Top lawyers will have nothing to worry about when it comes to job displacement. reasoning across domains, winning the trust of clients, applying years of experience in the courtroom, and having the ability to persuade a jury are all examples of the cognitive complexities, strategies, and modes of human interaction that are beyond the capabilities of AI. However, a lot of paralegal and preparatory work like document review, analysis, creating contracts, handling small cases, packing cases, and coming up with recommendations can be done much better and more efficiently with AI. The costs of law make it worthwhile for AI companies to go after AI paralegals and AI junior lawyers, but not top lawyers.

 

From DSC:
In terms of teaching, I agree that while #AI will help personalize learning, there will still be a great need for human teachers, professors, and trainers. I also agree w/ my boss (and with some of the author’s viewpoints here, but not all) that many kinds of legal work will still need the human touch & thought processes. I diverge from his thinking in terms of scope — the need for human lawyers will go far beyond just lawyers involved in crim law.

 

Also see:

15 business applications for artificial intelligence and machine learning — from forbes.com

Excerpt:

Fifteen members of Forbes Technology Council discuss some of the latest applications they’ve found for AI/ML at their companies. Here’s what they had to say…

 

 

 

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