Canada

World’s first available independent translation earpiece, powered by AI to be in the hands of consumers by July

On 06/13/2017, in Artificial Intelligence / Machine Learning / Deep Learning, Asia, Australia, Canada, cognitive computing, collaboration, communications, corporate / business world, Daniel S. Christian, digital audio, education technology, emerging technologies, Europe, global / globalization, human-computer interaction (HCI), IBM, ideas, innovation, intelligent systems, intelligent tutoring, Languages and translation, learning from the living [class] room, Mobile technologies, MOOCs -- Massive Open Online Courses, Natural Language Processing (NLP), online learning, online tutoring, platforms, Technologies for your home, tools, UK, United States, user experience, UX, vendors, videoconferencing, voice recognition / voice enabled interfaces, web-based collaboration, workplace, by Daniel Christian

Australian start-up taps IBM Watson to launch language translation earpiece — from prnewswire.com
World’s first available independent translation earpiece, powered by AI to be in the hands of consumers by July

Excerpts:

SYDNEY, June 12, 2017 /PRNewswire/ — Lingmo International, an Australian technology start-up, has today launched Translate One2One, an earpiece powered by IBM Watson that can efficiently translate spoken conversations within seconds, being the first of its kind to hit global markets next month.
…
Unveiled at last week’s United Nations Artificial Intelligence (AI) for Good Summit in Geneva, Switzerland, the Translate One2One earpiece supports translations across English, Japanese, French, Italian, Spanish, Brazilian Portuguese, German and Chinese. Available to purchase today for delivery in July, the earpiece carries a price tag of $179 USD, and is the first independent translation device that doesn’t rely on Bluetooth or Wi-Fi connectivity.

Lingmo International, an Australian technology start-up, has today launched Translate One2One, an earpiece powered by IBM Watson that can efficiently translate spoken conversations within seconds.

From DSC:
How much longer before this sort of technology gets integrated into videoconferencing and transcription tools that are used in online-based courses — enabling global learning at a scale never seen before? (Or perhaps NLP-based tools are already being integrated into global MOOCs and the like…not sure.) It would surely allow for us to learn from each other in a variety of societies throughout the globe.

New Google Earth has exciting features for teachers [Chang]

On 04/25/2017, in 24x7x365 access, 3D, A/V -- audio/visual, Asia, attention, Australia, Canada, digital learning, education technology, engagement / engaging students, Europe, Geography / Geology, Google, higher education, India, innovation, interface design, K-12 related, learning, Michigan, online media, student-related, teachers, UK, United States, user experience, UX, vendors, virtual field trips, youth, by Daniel Christian

New Google Earth has exciting features for teachers — from thejournal.com by Richard Chang

Excerpt:

Google has recently released a brand new version of Google Earth for both Chrome and Android. This new version has come with a slew of nifty features teachers can use for educational purposes with students in class. Following is a quick overview of the most fascinating features…

The 82 Hottest EdTech Tools of 2017 According to Education Experts [Cassella; tutora.co.uk]

On 04/06/2017, in 21st century, 3D, adjunct faculty, analytics, animation, Artificial Intelligence / Machine Learning / Deep Learning, assessment, augmented reality, Australia, blogs / blogging, bots, business side of he, Canada, change, chemistry, cloud-based computing / apps / other cloud-related, collaboration, colleges, communications, community colleges, computer science, creativity, Daniel S. Christian, digital audio, digital citizenship, digital learning, digital photography, digital video, e-books, e-publishing related items (EPUB and more), education technology, educational games / serious games, emerging technologies, engagement / engaging students, Europe, gifted students, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), India, innovation, interactivity, internet, K-12 related, Languages and translation, learning, learning ecosystem, literacy, maker movement, mathematics, Media/film, memory, Mobile learning, multimedia, online learning, participation, pedagogy, platforms, play, productivity / tips and tricks, programming, robotics, science, story, storytelling, student teaching/teacher education, student-related, teachers, Technologies for your home, tools, UK, United States, universities, vendors, virtual field trips, virtual reality / worlds / learning, writing, youth, by Daniel Christian

The 82 Hottest EdTech Tools of 2017 According to Education Experts — from tutora.co.uk by Giorgio Cassella

Excerpt:

If you work in education, you’ll know there’s a HUGE array of applications, services, products and tools created to serve a multitude of functions in education.

Tools for teaching and learning, parent-teacher communication apps, lesson planning software, home-tutoring websites, revision blogs, SEN education information, professional development qualifications and more.

There are so many companies creating new products for education, though, that it can be difficult to keep up – especially with the massive volumes of planning and marking teachers have to do, never mind finding the time to actually teach!

So how do you know which ones are the best?

Well, as a team of people passionate about education and learning, we decided to do a bit of research to help you out.

We’ve asked some of the best and brightest in education for their opinions on the hottest EdTech of 2017. These guys are the real deal – experts in education, teaching and new tech from all over the world from England to India, to New York and San Francisco.

They’ve given us a list of 82 amazing, tried and tested tools…

From DSC:
The ones that I mentioned that Giorgio included in his excellent article were:

AdmitHub – Free, Expert College Admissions Advice
Labster – Empowering the Next Generation of Scientists to Change the World
Unimersiv – Virtual Reality Educational Experiences
Lifeliqe – Interactive 3D Models to Augment Classroom Learning

“The Enterprise Gets Smart” + AI principles from the 2017 Asilomar Conference

On 03/24/2017, in 21st century, algorithms, Amazon, analytics, Artificial Intelligence / Machine Learning / Deep Learning, Asia, bots, business, Canada, career development, change, changing business models, cognitive computing, communications, corporate / business world, corporate universities / corporate training, data mining, emerging technologies, ethics, Europe, Facebook, future, game-changing environment, global / globalization, Google, human-computer interaction (HCI), IBM, ideas, India, innovation, intelligent systems, leadership, legislatures / government / legal, liberal arts, morals/values, reinvent, research, robotics, science, society, surviving, UK, United States, vendors, vision, by Daniel Christian

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)

The woman who thinks time has rendered Western education obsolete — from unlimited.world with thanks to Maree Conway for her tweet on this

Excerpt (emphasis DSC):

For years, Finland has loitered in the upper echelons of global literacy and numeracy tables, leading politicians from other Western nations to see its education system as a model of inspiration. Why, then, is the Finnish government submitting it to a radical overhaul?

Dr. Marjo Kyllonen is the Education Manager for Helsinki. Having devised the blueprint for the future of Finland’s school system, she is playing a pivotal role in driving these changes through. She is doing so because she sees the structure and aims of current education systems in the West as increasingly irrelevant and obsolete, relics of an Industrial Age that we started to leave behind a long time ago. She argues that we need to rethink our entire relationship to education to equip future generations with the tools they need to face the challenges to come –challenges such as climate collapse, automated workforces, urbanisation and social division. The key to her blueprint is an emphasis on collaborative, holistic, “phenomenon” teaching – a routine that is less beholden to traditional subject-based learning and instead teaches pupils to work together to deal with problems they will face in their everyday lives, including those they encounter online and in the digital world.

Other:

If schools were invented today, what would they be like?
Instead of studying different subjects in isolation, learning should be anchored to real-life phenomena, things that kids see around them, so they see the connection between what they’re learning and real life. The traditional way of teaching isolated subjects with a teacher as the sole oracle of knowledge is widening the gap between the lives kids are living today and what they do at school.
So we have to think, what skills will people need in 60 years? Life is not split into subjects, so why is learning? What is more crucial for future society is cross-disciplinary thinking; all the experts say that the big problems of tomorrow won’t be solved if you only have one approach.

From DSC:
Whether one agrees with Marjo or not, her assertions are very thought provoking. I really enjoyed reading this piece.

From DSC:
Can you imagine this as a virtual reality or a mixed reality-based app!?! Very cool.

This resource is incredible on multiple levels:

For their interface/interaction design
For their insights and ideas
For their creativity
For their graphics
…and more!

From DSC:
Given the exponential pace of technological change that many societies throughout the globe are now on, we need some tools to help us pulse-check what’s going on in the relevant landscapes that we are trying to scan.

Below, I would like to suggest 2 methods/tools to do this. I have used both methods for years, and I have found them to be immensely helpful in pulse-checking the landscapes. Perhaps these tools will be helpful to you — or to your students or employees — as well. I vote for these 2 tools to be a part of all of our learning ecosystems. (And besides, they also encourage micro-learning while helping us spot emerging trends.)

Google Alerts

Feedly.com

VR First: Democratizing VR/AR Innovation

On 02/03/2017, in 21st century, A/V -- audio/visual, architecture, Asia, attention, augmented reality, Canada, change, colleges, communications, communities of practice, community colleges, computer science, consortiums, convergence, creativity, education, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, Europe, experimentation, future, future of higher education, game-changing environment, global / globalization, health, higher education, history, human-computer interaction (HCI), ideas, immersion, India, innovation, interaction design, interactivity, Media/film, Mixed reality, network based learning, online learning, platforms, play, psychology, social learning / networks, social media, tools, UK, United States, universities, usability, user experience, Using teams, UX, vendors, virtual reality / worlds / learning, wearables, by Daniel Christian

Some excerpts of this infographic:

The Periodic Table of AI — from ai.xprize.org by Kris Hammond

Excerpts:

This is an invitation to collaborate. In particular, it is an invitation to collaborate in framing how we look at and develop machine intelligence. Even more specifically, it is an invitation to collaborate in the construction of a Periodic Table of AI.

Let’s be honest. Thinking about Artificial Intelligence has proven to be difficult for us. We argue constantly about what is and is not AI. We certainly cannot agree on how to test for it. We have difficultly deciding what technologies should be included within it. And we struggle with how to evaluate it.

Even so, we are looking at a future in which intelligent technologies are becoming commonplace.
…
With that in mind, we propose an approach to viewing machine intelligence from the perspective of its functional components. Rather than argue about the technologies behind them, the focus should be on the functional elements that make up intelligence. By stepping away from how these elements are implemented, we can talk about what they are and their roles within larger systems.

Also see this article, which contains the graphic below:

From DSC:
These graphics are helpful to me, as they increase my understanding of some of the complexities involved within the realm of artificial intelligence.

Also relevant/see:

From DSC:
Hmmm…this is interesting! I ran into a company based out of Canada called Sightline Innovation — and they offer Machine Learning as a Service!

Here’s an excerpt from their site:

MLaaS: AI for everyone
Sightline’s Machine Learning as a Service (MLaaS) is the AI solution for Enterprise. With MLaaS, you provide the data and the desired outcome, and Sightline provides the Machine Learning capacity. By analyzing data sets, MLaaS generates strategic insights that allow companies to optimize their business processes and maximize efficiency. Discover new approaches to time management, teamwork and collaboration, client service and business forecasting.

Mine troves of inert customer data to reveal sales pipeline bottlenecks, build more in-depth personas and discover opportunities for upsales.
MLaaS empowers Enterprise to capitalize on opportunities that were previously undiscovered. MLaaS.net is the only system that brings together a full spectrum of AI algorithms including:

Convolutional Neural Networks
Deep Nets
Restricted Boltzman Machines
Probabilistic Graphical Models; and
Bayesian Networks

I wonder if Machine Learning as a Service (MLaaS) is the way that many businesses in the future will tap into the power of AI-based solutions – especially smaller and mid-size companies who can’t afford to build an internal team focused on AI…?

Learning Ecosystems

World’s first available independent translation earpiece, powered by AI to be in the hands of consumers by July

“The Enterprise Gets Smart” + AI principles from the 2017 Asilomar Conference

Research Issues

Ethics and Values

Longer-term Issues

Very well done! Can you imagine this as a VR or MR-based app?! Also, check out these ideas about what our lives — & world — might be like in the future!

The Periodic Table of AI [Hammond]

Very interesting — Machine Learning as a Service!

Categories

Tags

Looking for something?

Visit our friends!

Archives