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.

 

 

 

AI Now Law and Policy Reading List — from medium.com by the AI Now Institute

Excerpt:

Data-driven technologies are widely used in society to make decisions that affect many critical aspects of our lives, from health, education, employment, and criminal justice to economic, social and political norms. Their varied applications, uses, and consequences raise a number of unique and complex legal and policy concerns. As a result, it can be hard to figure out not only how these systems work but what to do about them.

As a starting point, AI Now offers this Law and Policy Reading List tailored for those interested in learning about key concepts, debates, and leading analysis on law and policy issues related to artificial intelligence and other emerging data-driven technologies.

 

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.

 

 
 

Smart Machines & Human Expertise: Challenges for Higher Education — from er.educause.edu by Diana Oblinger

Excerpts:

What does this mean for higher education? One answer is that AI, robotics, and analytics become disciplines in themselves. They are emerging as majors, minors, areas of emphasis, certificate programs, and courses in many colleges and universities. But smart machines will catalyze even bigger changes in higher education. Consider the implications in three areas: data; the new division of labor; and ethics.

 

Colleges and universities are challenged to move beyond the use of technology to deliver education. Higher education leaders must consider how AI, big data, analytics, robotics, and wide-scale collaboration might change the substance of education.

 

Higher education leaders should ask questions such as the following:

  • What place does data have in our courses?
  • Do students have the appropriate mix of mathematics, statistics, and coding to understand how data is manipulated and how algorithms work?
  • Should students be required to become “data literate” (i.e., able to effectively use and critically evaluate data and its sources)?

Higher education leaders should ask questions such as the following:

  • How might problem-solving and discovery change with AI?
  • How do we optimize the division of labor and best allocate tasks between humans and machines?
  • What role do collaborative platforms and collective intelligence have in how we develop and deploy expertise?


Higher education leaders should ask questions such as the following:

  • Even though something is possible, does that mean it is morally responsible?
  • How do we achieve a balance between technological possibilities and policies that enable—or stifle—their use?
  • An algorithm may represent a “trade secret,” but it might also reinforce dangerous assumptions or result in unconscious bias. What kind of transparency should we strive for in the use of algorithms?

 

 

 

25 skills LinkedIn says are most likely to get you hired in 2018 — and the online courses to get them — from businessinsider.com by Mara Leighton

Excerpt:

With the introduction of far-reaching and robust technology, the job market has experienced its own exponential growth, adaptation, and semi-metamorphosis. So much so that it can be difficult to guess what skills employer’s are looking for and what makes your résumé — and not another — stand out to recruiters.

Thankfully, LinkedIn created a 2018 “roadmap”— a list of hard and soft skills that companies need the most.

LinkedIn used data from their 500+ million members to identify the skills companies are currently working the hardest to fill. They grouped the skills members add to their profiles into several dozen categories (for example, “Android” and “iOS” into the “Mobile Development” category). Then, the company looked at all of the hiring and recruiting activity that happened on LinkedIn between January 1 and September 1 (billions of data points) and extrapolated the skill categories that belonged to members who were “more likely to start a new role within a company and receive interest from companies.”

LinkedIn then coupled those specific skills with related jobs and their average US salaries — all of which you can find below, alongside courses you can take (for free or for much less than the cost of a degree) to support claims of aptitude and stay ahead of the curve.

The online-learning options we included — LinkedIn Learning, Udemy, Coursera, and edX— are among the most popular and inexpensive.

 

 

Also see:

 

 

 

Six tech giants sign health data interoperability pledge — from medicaldevice-network.com by GlobalData Healthcare

Excerpt:

Google, Amazon, and IBM joined forces with Microsoft, Salesforce, and Oracle to pledge to speed up the progress of health data standards and interoperability.

This big new alliance’s pledge will have a very positive impact on healthcare as it will become easier to share medical data among hospitals. Both physicians and patients will have easier access to information, which will lead to faster diagnosis and treatment.

The companies claim that this project will lead to better outcomes, higher patient satisfaction, and lower costs—a so-called “Triple Aim.”

 

From DSC:
No doubt that security will have to be very tight around these efforts.

 

 

State of AI — from stateof.ai

Excerpt:

In this report, we set out to capture a snapshot of the exponential progress in AI with a focus on developments in the past 12 months. Consider this report as a compilation of the most interesting things we’ve seen that seeks to trigger informed conversation about the state of AI and its implication for the future.

We consider the following key dimensions in our report:

  • Research: Technology breakthroughs and their capabilities.
  • Talent: Supply, demand and concentration of talent working in the field.
  • Industry: Large platforms, financings and areas of application for AI-driven innovation today and tomorrow.
  • Politics: Public opinion of AI, economic implications and the emerging geopolitics of AI.

 

definitions of terms involved in AI

definitions of terms involved in AI

 

hard to say how AI is impacting jobs yet -- but here are 2 perspectives

 

 

There’s nothing artificial about how AI is changing the workplace — from forbes.com by Eric Yuan

Excerpt:

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

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

 

 

 

AI can now ‘listen’ to machines to tell if they’re breaking down — from by Rebecca Campbell

Excerpt:

Sound is everywhere, even when you can’t hear it.

It is this noiseless sound, though, that says a lot about how machines function.

Helsinki-based Noiseless Acoustics and Amsterdam-based OneWatt are relying on artificial intelligence (AI) to better understand the sound patterns of troubled machines. Through AI they are enabling faster and easier problem detection.

 

Making sound visible even when it can’t be heard. With the aid of non-invasive sensors, machine learning algorithms, and predictive maintenance solutions, failing components can be recognized at an early stage before they become a major issue.

 

 

 

Chinese university uses facial recognition for campus entry — from cr80news.com by Andrew Hudson

Excerpt:

A number of higher education institutions in China have deployed biometric solutions for access and payments in recent months, and adding to the list is Peking University. The university has now installed facial recognition readers at perimeter access gates to control access to its Beijing campus.

As reported by the South China Morning Post, anyone attempting to enter through the southwestern gate of the university will no longer have to provide a student ID card. Starting this month, students will present their faces to a camera as part of a trial run of the system ahead of full-scale deployment.

From DSC:
I’m not sure I like this one at all — and the direction that this is going in. 

 

 

 

Will We Use Big Data to Solve Big Problems? Why Emerging Technology is at a Crossroads — from blog.hubspot.com by Justin Lee

Excerpt:

How can we get smarter about machine learning?
As I said earlier, we’ve reached an important crossroads. Will we use new technologies to improve life for everyone, or to fuel the agendas of powerful people and organizations?

I certainly hope it’s the former. Few of us will run for president or lead a social media empire, but we can all help to move the needle.

Consume information with a critical eye.
Most people won’t stop using Facebook, Google, or social media platforms, so proceed with a healthy dose of skepticism. Remember that the internet can never be objective. Ask questions and come to your own conclusions.

Get your headlines from professional journalists.
Seek credible outlets for news about local, national and world events. I rely on the New York Times and the Wall Street Journal. You can pick your own sources, but don’t trust that the “article” your Aunt Marge just posted on Facebook is legit.

 

 

 

 

 

 

Below are some excerpted slides from her presentation…

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Also see:

  • 20 important takeaways for learning world from Mary Meeker’s brilliant tech trends – from donaldclarkplanb.blogspot.com by Donald Clark
    Excerpt:
    Mary Meeker’s slide deck has a reputation of being the Delphic Oracle of tech. But, at 294 slides it’s a lot to take in. Don’t worry, I’ve been through them all. It has tons on economic stuff that is of marginal interest to education and training but there’s plenty to to get our teeth into. We’re not immune to tech trends, indeed we tend to follow in lock-step, just a bit later than everyone else. Among the data are lots of fascinating insights that point the way forward in terms of what we’re likely to be doing over the next decade. So here’s a really quick, top-end summary for folk in the learning game.

 

“Educational content usage online is ramping fast” with over 1 billion daily educational videos watched. There is evidence that use of the Internet for informal and formal learning is taking off.

 

 

 

 

 

 

10 Big Takeaways From Mary Meeker’s Widely-Read Internet Report — from fortune.com by  Leena Rao

 

 

 

 

 

 

Google’s robot assistant now makes eerily lifelike phone calls for you — from theguardian.com by Olivia Solon
Google Duplex contacts hair salon and restaurant in demo, adding ‘er’ and ‘mmm-hmm’ so listeners think it’s human

Excerpt:

Google’s virtual assistant can now make phone calls on your behalf to schedule appointments, make reservations in restaurants and get holiday hours.

The robotic assistant uses a very natural speech pattern that includes hesitations and affirmations such as “er” and “mmm-hmm” so that it is extremely difficult to distinguish from an actual human phone call.

The unsettling feature, which will be available to the public later this year, is enabled by a technology called Google Duplex, which can carry out “real world” tasks on the phone, without the other person realising they are talking to a machine. The assistant refers to the person’s calendar to find a suitable time slot and then notifies the user when an appointment is scheduled.

 

 

Google employees quit over the company’s military AI project — from thenextweb.com by Tristan Greene

Excerpt:

About a dozen Google employees reportedly left the company over its insistence on developing AI for the US military through a program called Project Maven. Meanwhile 4,000 others signed a petition demanding the company stop.

It looks like there’s some internal confusion over whether the company’s “Don’t Be Evil” motto covers making machine learning systems to aid warfare.

 

 

 

The link between big tech and defense work — from wired.com by Nitasha Tiku

Except:

FOR MONTHS, A growing faction of Google employees has tried to force the company to drop out of a controversial military program called Project Maven. More than 4,000 employees, including dozens of senior engineers, have signed a petition asking Google to cancel the contract. Last week, Gizmodo reported that a dozen employees resigned over the project. “There are a bunch more waiting for job offers (like me) before we do so,” one engineer says. On Friday, employees communicating through an internal mailing list discussed refusing to interview job candidates in order to slow the project’s progress.

Other tech giants have recently secured high-profile contracts to build technology for defense, military, and intelligence agencies. In March, Amazon expanded its newly launched “Secret Region” cloud services supporting top-secret work for the Department of Defense. The same week that news broke of the Google resignations, Bloomberg reported that Microsoft locked down a deal with intelligence agencies. But there’s little sign of the same kind of rebellion among Amazon and Microsoft workers.

 

 

Amazon urged not to sell facial recognition tool to police — from wpxi.com by Gene Johnson

Excerpt:

Facebook SEATTLE (AP) – The American Civil Liberties Union and other privacy advocates are asking Amazon to stop marketing a powerful facial recognition tool to police, saying law enforcement agencies could use the technology to “easily build a system to automate the identification and tracking of anyone.”

The tool, called Rekognition, is already being used by at least one agency – the Washington County Sheriff’s Office in Oregon – to check photographs of unidentified suspects against a database of mug shots from the county jail, which is a common use of such technology around the country.

 

 

From DSC:
Google’s C-Suite — as well as the C-Suites at Microsoft, Amazon, and other companies — needs to be very careful these days, as they could end up losing the support/patronage of a lot of people — including more of their own employees. It’s not an easy task to know how best to build and use technologies in order to make the world a better place…to create a dream vs. a nightmare for our future. But just because we can build something, doesn’t mean we should.

 

 

The Complete Guide to Conversational Commerce | Everything you need to know. — from chatbotsmagazine.com by Matt Schlicht

Excerpt:

What is conversational commerce? Why is it such a big opportunity? How does it work? What does the future look like? How can I get started? These are the questions I’m going to answer for you right now.

The guide covers:

  • An introduction to conversational commerce.
  • Why conversational commerce is such a big opportunity.
  • Complete breakdown of how conversational commerce works.
  • Extensive examples of conversational commerce using chatbots and voicebots.
  • How artificial intelligence impacts conversational commerce.
  • What the future of conversational commerce will look like.

 

Definition: Conversational commerce is an automated technology, powered by rules and sometimes artificial intelligence, that enables online shoppers and brands to interact with one another via chat and voice interfaces.

 

 

 

Notes from the AI frontier: Applications and value of deep learning — from mckinsey.com by Michael Chui, James Manyika, Mehdi Miremadi, Nicolaus Henke, Rita Chung, Pieter Nel, and Sankalp Malhotra

Excerpt:

Artificial intelligence (AI) stands out as a transformational technology of our digital age—and its practical application throughout the economy is growing apace. For this briefing, Notes from the AI frontier: Insights from hundreds of use cases (PDF–446KB), we mapped both traditional analytics and newer “deep learning” techniques and the problems they can solve to more than 400 specific use cases in companies and organizations. Drawing on McKinsey Global Institute research and the applied experience with AI of McKinsey Analytics, we assess both the practical applications and the economic potential of advanced AI techniques across industries and business functions. Our findings highlight the substantial potential of applying deep learning techniques to use cases across the economy, but we also see some continuing limitations and obstacles—along with future opportunities as the technologies continue their advance. Ultimately, the value of AI is not to be found in the models themselves, but in companies’ abilities to harness them.

It is important to highlight that, even as we see economic potential in the use of AI techniques, the use of data must always take into account concerns including data security, privacy, and potential issues of bias.

  1. Mapping AI techniques to problem types
  2. Insights from use cases
  3. Sizing the potential value of AI
  4. The road to impact and value

 

 

 

AI for Good — from re-work.co by Ali Shah, Head of Emerging Technology and Strategic Direction – BBC

 

 

 

Algorithms are making the same mistakes assessing credit scores that humans did a century ago — from qz.com by Rachel O’Dwyer

 

 

 

 

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!

© 2018 | Daniel Christian