59 impressive things artificial intelligence can do today — from businessinsider.com by Ed Newton-Rex

Excerpt:

But what can AI do today? How close are we to that all-powerful machine intelligence? I wanted to know, but couldn’t find a list of AI’s achievements to date. So I decided to write one. What follows is an attempt at that list. It’s not comprehensive, but it contains links to some of the most impressive feats of machine intelligence around. Here’s what AI can do…

 

 

 


Recorded Saturday, February 25th, 2017 and published on Mar 16, 2017


Description:

Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, or could it present a threat to the very basis of human civilization? The future of artificial intelligence is up for debate, and the Origins Project is bringing together a distinguished panel of experts, intellectuals and public figures to discuss who’s in control. Eric Horvitz, Jaan Tallinn, Kathleen Fisher and Subbarao Kambhampati join Origins Project director Lawrence Krauss.

 

 

 

 

Description:
Elon Musk, Stuart Russell, Ray Kurzweil, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, and Jaan Tallinn discuss with Max Tegmark (moderator) what likely outcomes might be if we succeed in building human-level AGI, and also what we would like to happen. The Beneficial AI 2017 Conference: In our sequel to the 2015 Puerto Rico AI conference, we brought together an amazing group of AI researchers from academia and industry, and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI. We hosted a two-day workshop for our grant recipients and followed that with a 2.5-day conference, in which people from various AI-related fields hashed out opportunities and challenges related to the future of AI and steps we can take to ensure that the technology is beneficial.

 

 


(Below emphasis via DSC)

IBM and Ricoh have partnered for a cognitive-enabled interactive whiteboard which uses IBM’s Watson intelligence and voice technologies to support voice commands, taking notes and actions and even translating into other languages.

 

The Intelligent Workplace Solution leverages IBM Watson and Ricoh’s interactive whiteboards to allow to access features via using voice. It makes sure that Watson doesn’t just listen, but is an active meeting participant, using real-time analytics to help guide discussions.

Features of the new cognitive-enabled whiteboard solution include:

  • Global voice control of meetings: Once a meeting begins, any employee, whether in-person or located remotely in another country, can easily control what’s on the screen, including advancing slides, all through simple voice commands using Watson’s Natural Language API.
  • Translation of the meeting into another language: The Intelligent Workplace Solution can translate speakers’ words into several other languages and display them on screen or in transcript.
  • Easy-to-join meetings: With the swipe of a badge the Intelligent Workplace Solution can log attendance and track key agenda items to ensure all key topics are discussed.
  • Ability to capture side discussions: During a meeting, team members can also hold side conversations that are displayed on the same whiteboard.

 


From DSC:

Holy smokes!

If you combine the technologies that Ricoh and IBM are using with their new cognitive-enabled interactive whiteboard with what Bluescape is doing — by providing 160 acres of digital workspace that’s used to foster collaboration (and to do so whether you are working remoting or working with others in the same physical space) — and you have one incredibly powerful platform! 

#NLP  |  #AI  |  #CognitiveComputing  | #SmartClassrooms
#LearningSpaces  |#Collaboration |  #Meetings 

 

 


 

 

 


 

AI Market to Grow 47.5% Over Next Four Years — from campustechnology.com by Richard Chang

Excerpt:

The artificial intelligence (AI) market in the United States education sector is expected to grow at a compound annual growth rate of 47.5 percent during the period 2017-2021, according to a new report by market research firm Research and Markets.

 

 

Amazon deepens university ties in artificial intelligence race — from by Jeffrey Dastin

Excerpt:

Amazon.com Inc has launched a new program to help students build capabilities into its voice-controlled assistant Alexa, the company told Reuters, the latest move by a technology firm to nurture ideas and talent in artificial intelligence research.

Amazon, Alphabet Inc’s Google and others are locked in a race to develop and monetize artificial intelligence. Unlike some rivals, Amazon has made it easy for third-party developers to create skills for Alexa so it can get better faster – a tactic it now is extending to the classroom.

 

 

The WebMD skill for Amazon’s Alexa can answer all your medical questions — from digitaltrends.com by Kyle Wiggers
WebMD is bringing its wealth of medical knowledge to a new form factor: Amazon’s Alexa voice assistant.

Excerpt:

Alexa, Amazon’s brilliant voice-activated smart assistant, is a capable little companion. It can order a pizza, summon a car, dictate a text message, and flick on your downstairs living room’s smart bulb. But what it couldn’t do until today was tell you whether that throbbing lump on your forearm was something that required medical attention. Fortunately, that changed on Tuesday with the introduction of a WebMD skill that puts the service’s medical knowledge at your fingertips.

 

 

 

The Blockchain Revolution and Higher Education — from er.educause.edu by Don Tapscott and Alex Tapscott
The blockchain provides a rich, secure, and transparent platform on which to create a global network for higher learning. This Internet of value can help to reinvent higher education in a way the Internet of information alone could not.

Excerpt:

What will be the most important technology to change higher education? In our view, it’s not big data, the social web, MOOCs, virtual reality, or even artificial intelligence. We see these as components of something new, all enabled and transformed by an emerging technology called the blockchain.

OK, it’s not the most sonorous word ever, sounding more like a college football strategy than a transformative technology. Yet, sonorous or not, the blockchain represents nothing less than the second generation of the Internet, and it holds the potential to disrupt money, business, government, and yes, higher education.

The opportunities for innovators in higher education fall into four categories:

  • Identity and Student Records: How we identify students; protect their privacy; measure, record, and credential their accomplishments; and keep these records secure
  • New Pedagogy: How we customize teaching to each student and create new models of learning
  • Costs (Student Debt): How we value and fund education and reward students for the quality of their work
  • The Meta-University: How we design entirely new models of higher education so that former MIT President Chuck Vest’s dream can become a reality1

The blockchain may help us change the relationships among colleges and universities and, in turn, their relationship to society.

Let us explain.

 

What if there was an Internet of value — a global, distributed, highly secure platform, ledger, or database where we could store and exchange things of value and where we could trust each other without powerful intermediaries? That is the blockchain.

 

 

From DSC:
The quote…

In 2006, MIT President Emeritus Vest offered a tantalizing vision of what he called the meta-university. In the open-access movement, he saw “a transcendent, accessible, empowering, dynamic, communally constructed framework of open materials and platforms on which much of higher education worldwide can be constructed or enhanced.”

…made me wonder if this is where a vision that I’m tracking called Learning from the Living [Class] Room is heading. Also, along these lines, futurist Thomas Frey believes

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider. (source)

Blockchain could be a key piece of this vision.

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

The Enterprise Gets Smart
Companies are starting to leverage artificial intelligence and machine learning technologies to bolster customer experience, improve security and optimize operations.

Excerpt:

Assembling the right talent is another critical component of an AI initiative. While existing enterprise software platforms that add AI capabilities will make the technology accessible to mainstream business users, there will be a need to ramp up expertise in areas like data science, analytics and even nontraditional IT competencies, says Guarini.

“As we start to see the land grab for talent, there are some real gaps in emerging roles, and those that haven’t been as critical in the past,” Guarini  says, citing the need for people with expertise in disciplines like philosophy and linguistics, for example. “CIOs need to get in front of what they need in terms of capabilities and, in some cases, identify potential partners.”

 

 

 

Asilomar AI Principles

These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here.

 

Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.

Research Issues

 

1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

  • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
  • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
  • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
  • What set of values should AI be aligned with, and what legal and ethical status should it have?

3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Ethics and Values

 

6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

9) Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.

10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

12) Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data.

13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

14) Shared Benefit: AI technologies should benefit and empower as many people as possible.

15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

17) Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided.

Longer-term Issues

 

19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities.

20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.

21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

22) Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.

23) Common Good: Superintelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization.

 

 

 

Excerpts:
Creating human-level AI: Will it happen, and if so, when and how? What key remaining obstacles can be identified? How can we make future AI systems more robust than today’s, so that they do what we want without crashing, malfunctioning or getting hacked?

  • Talks:
    • Demis Hassabis (DeepMind)
    • Ray Kurzweil (Google) (video)
    • Yann LeCun (Facebook/NYU) (pdf) (video)
  • Panel with Anca Dragan (Berkeley), Demis Hassabis (DeepMind), Guru Banavar (IBM), Oren Etzioni (Allen Institute), Tom Gruber (Apple), Jürgen Schmidhuber (Swiss AI Lab), Yann LeCun (Facebook/NYU), Yoshua Bengio (Montreal) (video)
  • Superintelligence: Science or fiction? If human level general AI is developed, then what are likely outcomes? What can we do now to maximize the probability of a positive outcome? (video)
    • Talks:
      • Shane Legg (DeepMind)
      • Nick Bostrom (Oxford) (pdf) (video)
      • Jaan Tallinn (CSER/FLI) (pdf) (video)
    • Panel with Bart Selman (Cornell), David Chalmers (NYU), Elon Musk (Tesla, SpaceX), Jaan Tallinn (CSER/FLI), Nick Bostrom (FHI), Ray Kurzweil (Google), Stuart Russell (Berkeley), Sam Harris, Demis Hassabis (DeepMind): If we succeed in building human-level AGI, then what are likely outcomes? What would we like to happen?
    • Panel with Dario Amodei (OpenAI), Nate Soares (MIRI), Shane Legg (DeepMind), Richard Mallah (FLI), Stefano Ermon (Stanford), Viktoriya Krakovna (DeepMind/FLI): Technical research agenda: What can we do now to maximize the chances of a good outcome? (video)
  • Law, policy & ethics: How can we update legal systems, international treaties and algorithms to be more fair, ethical and efficient and to keep pace with AI?
    • Talks:
      • Matt Scherer (pdf) (video)
      • Heather Roff-Perkins (Oxford)
    • Panel with Martin Rees (CSER/Cambridge), Heather Roff-Perkins, Jason Matheny (IARPA), Steve Goose (HRW), Irakli Beridze (UNICRI), Rao Kambhampati (AAAI, ASU), Anthony Romero (ACLU): Policy & Governance (video)
    • Panel with Kate Crawford (Microsoft/MIT), Matt Scherer, Ryan Calo (U. Washington), Kent Walker (Google), Sam Altman (OpenAI): AI & Law (video)
    • Panel with Kay Firth-Butterfield (IEEE, Austin-AI), Wendell Wallach (Yale), Francesca Rossi (IBM/Padova), Huw Price (Cambridge, CFI), Margaret Boden (Sussex): AI & Ethics (video)

 

 

 
 

SXSW Announces Winners for 2017 Accelerator Pitch Event — from prnewswire.com
Pitch competition showcased global startups featuring cutting-edge innovation in 10 technology categories

Excerpt:

The winners of the 2017 SXSW Accelerator Pitch Event are:

 

 

 

 

 

From DSC:
In the future, will Microsoft — via data supplied by LinkedIn and Lynda.com — use artificial intelligence, big data, and blockchain-related technologies to match employers with employees/freelancers?  If so, how would this impact higher education? Badging? Credentialing?

It’s something to put on our radars.

 

 

 

 

 

Excerpt:

A sneak peak on Recruitment in AI era
With global talent war at its peak, organisations are now looking at harnessing Artificial Intelligence (AI) capabilities, to use search optimisation tools, data analytics, and talent mapping to reach out to the right talent for crucial job roles. Technology has been revolutionising the way recruitment works with the entire process being now automated with ATS and other talent management softwares. This saves time and costs involved with recruiting for HR managers, whilst allowing them to do away with third-party service providers for talent sourcing such as employment bureaus and traditional recruitment agencies. With modern talent acquisition technology empowered by AI, the time taken for recruitment is halved and search narrowed to reach out to only the best talent that matches job requirements. There is no need for human intervention and manual personality matching to choose the best candidates for suitable job roles.

Talent mapping, with the help of big data, is definitely the next step in recruitment technology. With talent mapping, recruiters can determine their candidate needs well in advance and develop a strategic plan for hiring long-term. This includes filling any skill gaps, bolstering the team for sudden changes in the workplace, or just simply having suitable talent in mind for the future. All of these, when prepared ahead of time, can save companies the trouble and time in future. Recruiters who are able to understand how AI works, harness the technology to save on time and costs will be rewarded with improved quality of hires, enhanced efficiency, more productive workforce and less turnover.

 

From DSC:
At the recent
Next Generation Learning Spaces Conference, in my introductory piece for our panel discussion, I relayed several ideas/areas that should be on our institutions’ radars. That is, at least someone at each of our institutions of higher education should be aware of these things and be pulse-checking them as time goes by.

 

 

 

 

 

 

 

 

 

 

 

One of these ideas/areas involved the use of blockchain technologies:

 

 

If #blockchain technologies are successful within the financial/banking world, then it’s highly likely that other use cases will be developed as well (i.e., the trust in blockchain-enabled applications will be there already).

Along those lines, if that occurs, then colleges and universities are likely to become only 1 of the feeds into someone’s cloud-based, lifelong learning profile. I’ve listed several more sources of credentials below:

 

 

Given the trend towards more competency-based education (CBE) and the increased experimentation with badges, blockchain could increasingly move onto the scene.

In fact, I could see a day when an individual learner will be able to establish who can and can’t access their learner profile, and who can and can’t feed information and updates into it.

Artificial intelligence and big data also come to mind here…and I put Microsoft on my radar a while back in this regard; as Microsoft (via LinkedIn and Lynda.com) could easily create online-based marketplaces matching employers with employees/freelancers.

 

 

 


Along these lines, see:


 

  • The Mainstreaming of Alternative Credentials in Postsecondary Education — from by Deborah Keyek-Franssen
    Excerpt:

    • The Context of Alternative Credentials
      The past few years have seen a proliferation of new learning credentials ranging from badges and bootcamp certifications to micro-degrees and MOOC certificates. Although alternative credentials have been part of the fabric of postsecondary education and professional development for decades—think prior learning assessments like Advanced Placement or International Baccalaureate exams, or industry certifications—postsecondary institutions are increasingly unbundling their degrees and validating smaller chunks of skills and learning to provide workplace value to traditional and non-traditional students alike.
      Many are experimenting with alternative credentials to counter the typical binary nature of a degree. Certifications of learning or skills are conferred after the completion of a course or a few short courses in a related field. Students do not have to wait until all requirements for a degree are met before receiving a certificate of learning, but instead can receive one after a much shorter period of study. “Stackable” credentials are combined to be the equivalent of an undergraduate or graduate certificate (a micro-degree), or even a degree.
    • The National Discussion of Alternative Credentials
      Discussions of alternative credentials are often responses to a persistent and growing critique of traditional higher educational institutions’ ability to meet workforce needs, especially because the cost to students for a four-year degree has grown dramatically over the past several decades. The increasing attention paid to alternative credentials brings to the fore questions such as what constitutes a postsecondary education, what role universities in particular should play vis-à-vis workforce development, and how we can assess learning and mastery.

 

 


Addendums added on 3/4/17, that show that this topic isn’t just for higher education, but could involve K-12 as well:


 

 

 

 

 

HarvardX rolls out new adaptive learning feature in online course — from edscoop.com by Corinne Lestch
Students in MOOC adaptive learning experiment scored nearly 20 percent better than students using more traditional learning approaches.

Excerpt:

Online courses at Harvard University are adapting on the fly to students’ needs.

Officials at the Cambridge, Massachusetts, institution announced a new adaptive learning technology that was recently rolled out in a HarvardX online course. The feature offers tailored course material that directly correlates with student performance while the student is taking the class, as well as tailored assessment algorithms.

HarvardX is an independent university initiative that was launched in parallel with edX, the online learning platform that was created by Harvard and Massachusetts Institute of Technology. Both HarvardX and edX run massive open online courses. The new feature has never before been used in a HarvardX course, and has only been deployed in a small number of edX courses, according to officials.

 

 

From DSC:
Given the growth of AI, this is certainly radar worthy — something that’s definitely worth pulse-checking to see where opportunities exist to leverage these types of technologies.  What we now know of as adaptive learning will likely take an enormous step forward in the next decade.

IBM’s assertion rings in my mind:

 

 

I’m cautiously hopeful that these types of technologies can extend beyond K-12 and help us deal with the current need to be lifelong learners, and the need to constantly reinvent ourselves — while providing us with more choice, more control over our learning. I’m hopeful that learners will be able to pursue their passions, and enlist the help of other learners and/or the (human) subject matter experts as needed.

I don’t see these types of technologies replacing any teachers, professors, or trainers. That said, these types of technologies should be able to help do some of the heavy teaching and learning lifting in order to help someone learn about a new topic.

Again, this is one piece of the Learning from the Living [Class] Room that we see developing.

 

 

 

 

No hype, just fact: What artificial intelligence is – in simple business terms — from zdnet.com by Michael Krigsman
AI has become one of the great, meaningless buzzwords of our time. In this video, the Chief Data Scientist of Dun and Bradstreet explains AI in clear business terms.

Excerpt:

How do terms like machine learning, AI, and cognitive computing relate to one another?
They’re not synonymous. So, cognitive computing is very different than machine learning, and I will call both of them a type of AI. Just to try and describe those three. So, I would say artificial intelligence is all of that stuff I just described. It’s a collection of things designed to either mimic behavior, mimic thinking, behave intelligently, behave rationally, behave empathetically. Those are the systems and processes that are in the collection of soup that we call artificial intelligence.

Cognitive computing is primarily an IBM term. It’s a phenomenal approach to curating massive amounts of information that can be ingested into what’s called the cognitive stack. And then to be able to create connections among all of the ingested material, so that the user can discover a particular problem, or a particular question can be explored that hasn’t been anticipated.

Machine learning is almost the opposite of that. Where you have a goal function, you have something very specific that you try and define in the data. And, the machine learning will look at lots of disparate data, and try to create proximity to this goal function ? basically try to find what you told it to look for. Typically, you do that by either training the system, or by watching it behave, and turning knobs and buttons, so there’s unsupervised, supervised learning. And that’s very, very different than cognitive computing.

 

 

 

 

 

 

IBM to Train 25 Million Africans for Free to Build Workforce — from by Loni Prinsloo
* Tech giant seeking to bring, keep digital jobs in Africa
* Africa to have world’s largest workforce by 2040, IBM projects

Excerpt:

International Business Machines Corp. is ramping up its digital-skills training program to accommodate as many as 25 million Africans in the next five years, looking toward building a future workforce on the continent. The U.S. tech giant plans to make an initial investment of 945 million rand ($70 million) to roll out the training initiative in South Africa…

 

Also see:

IBM Unveils IT Learning Platform for African Youth — from investopedia.com by Tim Brugger

Excerpt (emphasis DSC):

Responding to concerns that artificial intelligence (A.I.) in the workplace will lead to companies laying off employees and shrinking their work forces, IBM (NYSE: IBM) CEO Ginni Rometty said in an interview with CNBC last month that A.I. wouldn’t replace humans, but rather open the door to “new collar” employment opportunities.

IBM describes new collar jobs as “careers that do not always require a four-year college degree but rather sought-after skills in cybersecurity, data science, artificial intelligence, cloud, and much more.”

In keeping with IBM’s promise to devote time and resources to preparing tomorrow’s new collar workers for those careers, it has announced a new “Digital-Nation Africa” initiative. IBM has committed $70 million to its cloud-based learning platform that will provide free skills development to as many as 25 million young people in Africa over the next five years.

The platform will include online learning opportunities for everything from basic IT skills to advanced training in social engagement, digital privacy, and cyber protection. IBM added that its A.I. computing wonder Watson will be used to analyze data from the online platform, adapt it, and help direct students to appropriate courses, as well as refine the curriculum to better suit specific needs.

 

 

From DSC:
That last part, about Watson being used to personalize learning and direct students to appropropriate courses, is one of the elements that I see in the Learning from the Living [Class]Room vision that I’ve been pulse-checking for the last several years. AI/cognitive computing will most assuredly be a part of our learning ecosystems in the future.  Amazon is currently building their own platform that adds 100 skills each day — and has 1000 people working on creating skills for Alexa.  This type of thing isn’t going away any time soon. Rather, I’d say that we haven’t seen anything yet!

 

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

And Amazon has doubled down to develop Alexa’s “skills,” which are discrete voice-based applications that allow the system to carry out specific tasks (like ordering pizza for example). At launch, Alexa had just 20 skills, which has reportedly jumped to 5,200 today with the company adding about 100 skills per day.

In fact, Bezos has said, “We’ve been working behind the scenes for the last four years, we have more than 1,000 people working on Alexa and the Echo ecosystem … It’s just the tip of the iceberg. Just last week, it launched a new website to help brands and developers create more skills for Alexa.

Source

 

 

Also see:

 

“We are trying to make education more personalised and cognitive through this partnership by creating a technology-driven personalised learning and tutoring,” Lula Mohanty, Vice President, Services at IBM, told ET. IBM will also use its cognitive technology platform, IBM Watson, as part of the partnership.

“We will use the IBM Watson data cloud as part of the deal, and access Watson education insight services, Watson library, student information insights — these are big data sets that have been created through collaboration and inputs with many universities. On top of this, we apply big data analytics,” Mohanty added.

Source

 

 


 

Also see:

  • Most People in Education are Just Looking for Faster Horses, But the Automobile is Coming — from etale.org by Bernard Bull
    Excerpt:
    Most people in education are looking for faster horses. It is too challenging, troubling, or beyond people’s sense of what is possible to really imagine a completely different way in which education happens in the world. That doesn’t mean, however, that the educational equivalent of the automobile is not on its way. I am confident that it is very much on its way. It might even arrive earlier than even the futurists expect. Consider the following prediction.

 


 

 

 
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