Education 2.0 & 3.0

"Music streaming company Spotify is a prime example of an AI Native business. In this post, you'll learn what that means and why it should matter to you ..."

Research report: The impact of AI, machine learning, automation and robotics on the information profession

The purpose of this independent research is to help our professional community to understand how AI, machine learning, process automation and robotics are either already impacting the daily work of healthcare information professionals or likely to do so in the near future.

In it author Dr Andrew Cox from Sheffield University, calls for a joined-up and coherent response from information professionals, enabling us to maximise the benefits of AI, machine learning, automation and robotics for information users while mitigating the emerging risks.

The full research report, published by CILIP with the support of Health Education England, sets out a detailed and methodical analysis of the challenges and opportunities presented by this new generation of technologies.

Report at: https://drive.google.com/file/d/19gWoLV_rSP1qKS9Z8KOoorRAQuHmFN4u/view 

Engineers from the University of Cambridge have developed a vegetable-picking robot that can autonomously identify and harvest iceberg lettuce, one of the more manually demanding crops for human pickers. Vegebot was trained using a machine-learning algorithm that helped it distinguish healthy lettuces ready for harvest, in a variety of different weather conditions.

"This morning I want to talk to you about machine learning. In particular, I want to talk with you about machine learning in the context of education and how it could be introduced in the classroom."

A small, family-owned grocery store in the heart of a downtown district has been providing goods to their community for over ten years. Customers come and go, and products fly off the shelves in waves. For the last two years, the store has seen a decline in sales and wonders if they will be able to weather the latest storm of dropping sales and over-bloated inventory. The owner relies on his intuition, but lately has noticed that his business is running inefficiently.

Google really wants you to learn how to develop AI. It's offering the same course it gives to company engineers free to everyone now.

Those who understand learning and work with young people know that in an uncertain world of rapid change we urgently need to be helping learners to take risks, to work in teams, to develop a greater understanding of the way systems and societies work, and to become more creative. Fundamentally, these things have been washed out of the system in favour of a ‘learn fact, repeat fact’ model.

To get the best out of this technology in the future, educators need to turn the current systems upside down.

In previous technology developments in education – such as multimedia, whiteboards or the internet – initially, most worried that they would upset the world they were used to and feared for their jobs. Only a few imagined how these technologies could change the world and make things better. In reality, new technologies are typically highjacked to inappropriately maintain the status quo and end up powering the exam sausage factory.

Moving forward into 2017, it is not the tech itself that needs to change. In most aspects of our lives, technology has made significant changes (for good and bad), but in education, particularly schools, there is still stubborn resistance.

Learn more / En savoir plus / Mehr erfahren:

https://gustmees.wordpress.com/2015/04/13/dos-and-donts-adapting-to-21st-century-education/

https://gustmees.wordpress.com/2015/07/19/learning-path-for-professional-21st-century-learning-by-ict-practice/

https://gustmees.wordpress.com/2015/12/27/what-are-the-best-ways-of-teaching-and-learning-ideas-and-reflections/

By Ron Drabkin - Machine learning will be steadily adopted in a variety of educational technology tools. How will that affect you?

A short video from the University of Oxford explains the concept of machine learning.

Por Carlos Bravo Reyes Desde hace años es conocido el empleo de la inteligencia artificial, en numerosos procesos para mejorar la vida d

Machine learning helps teachers or instructors to have a thorough understanding of a student's performance.

Machine learning is all around us. We all use machine learning systems every day - such as spam filters, recommendation engines, language translation services, chatbots and digital assistants, search engines, and fraud detection systems.

It will soon be normal for machine learning systems to drive our cars, and help doctors to diagnose and treat our illnesses.

It's important that kids are aware of how our world works. The best way to understand the capabilities and implications is to be able to build with this technology for themselves.

This blog is by Risto Siilasmaa, Chairman of the Board of Directors of Nokia Corporation Twitter: @rsiilasmaa I was fascinated by artificial intelligence during the end of the 80's and spent numerous hours working on Natural Language Processing challenges using a weird and wonderful programming…

Microsoft says AI and machine learning driven by open source and the cloud

Artificial intelligence and machine learning are rapidly gaining importance, and Mark Russinovich, Microsoft Azure chief technology officer, believes it's because of open-source software and the cloud.

Yes, Microsoft just announced that the next major edition of Windows 10 will support artificial intelligence (AI) and machine learning (ML). But, marketing hype aside, Microsoft knows darn well that the real heavy lifting for AI and ML happens on the cloud with open-source software. That was the message Mark Russinovich, Microsoft's Azure CTO, brought to The Linux Foundation's Open Source Leadership Summit (OSLS) in Sonoma, CA.

Russinovich opened by saying:

AI technologies and techniques are experiencing a renaissance. Open-source technologies and communities have fostered the growth of self-taught machine learning developers with libraries and frameworks. The computing power of the cloud has made the processing of large data sets cost effective and commonplace. As more research continues to be done and shared throughout the communities we will continue to see more intelligent apps driving even greater adoption of open-source technologies across all processing platforms.

Specifically, he mentioned two examples where Microsoft is using the cloud and open source to help provide solutions with customers. The first is with Rolls-Royce aircraft engines which use ML to track their wear and tear. This data is then used with AI to proactively maintain the engines.

Learn more / En savoir plus / Mehr erfahren:

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=AI

https://www.scoop.it/t/21st-century-innovative-technologies-and-developments/?&tag=AI

https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=machine+learning

Deep-learning researchers have found that certain neurons in the brain have shape and electrical properties that appear to be well-suited for “deep learning” — the kind of machine-intelligence used in beating humans at Go and Chess.

Canadian Institute For Advanced Research (CIFAR) Fellow Blake Richards and his colleagues — Jordan Guerguiev at the University of Toronto, Scarborough, and Timothy Lillicrap at Google DeepMind — developed an algorithm that simulates how a deep-learning network could work in our brains. It represents a biologically realistic way by which real brains could do deep learning.

The finding is detailed in a study published December 5th in the open-access journal eLife. (The paper is highly technical; Adam Shai of Stanford University and Matthew E. Larkum of Humboldt University, Germany wrote a more accessible paper summarizing the ideas, published in the same eLife issue.)

El Machine Learning se convierte en el nuevo camino de la Inteligencia Artificial para optimizar resultados.

Researchers have known that “artificial neurons” could carry out logical functions—i.e., learn the way humans do—since 1943. The term “artificial intelligence” has been around since its introduction at a science conference at Dartmouth University in 1956. But only in the past several years have we started seeing theory put into practice the way those researchers imagined. We now have machines that can translate languages, compose music, write novels, and operate vehicles.

El próximo día 3 de marzo intervengo en el Congreso ExpoeLearning 2017. Y este año, al contrario que en las ocasiones anteriores,  en los que siempre he hablado sobre aprendizaje colaborativo, innovación en la formación y comunidades de práctica, lo haré sobre inteligencia artificial y machine learning. En general todo el Congreso tendrá este año…