21st Century Learning and Teaching

Machine learning can drive tangible business value for a wide range of industries — but only if it is actually put to use. Despite the many machine learning discoveries being made by academics, new research papers showing what is possible, and an increasing amount of data available, companies are struggling to deploy machine learning to solve real business problems. In short, the gap for most companies isn’t that machine learning doesn’t work, but that they struggle to actually use it.

How can companies close this execution gap? In a recent project we illustrated the principles of how to do it. We used machine learning to augment the power of seasoned professionals — in this case, project managers — by allowing them to make data-driven business decisions well in advance. And in doing so, we demonstrated that getting value from machine learning is less about cutting-edge models, and more about making deployment easier.

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

Everyday, there are 4 million blog posts, 100,000 news articles and 500,000 hours of video published on the Internet. A wealth of information and knowledge. A wealth of information and knowledge that is lost for most companies, at least for the most part.

Lost?

Step 1: content curation
Not entirely. Thanks to content curation technology, the Web can now be filtered. With content curation tools and platforms such as Scoop.it (among others of course), we can use more or less sophisticated ways to filter this huge amount of content that is published daily to zoom in on what matters to us. Good content curation technology is essential. It saves people a huge amount of time looking for content to share for marketing purposes or information that helps their organization make better decisions. And perhaps as importantly, without these filters, we would just be able to search – not discover. We would still find answers to what we don’t know but we wouldn’t know what we don’t know.

But until recently, all the solutions we’ve offered to deal with information overload – ours included – have revolved around the same basic idea: more – or more sophisticated – filters.

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Regulating the internet giants

The world’s most valuable resource is no longer oil, but data

The data economy demands a new approach to antitrust rules

A NEW commodity spawns a lucrative, fast-growing industry, prompting antitrust regulators to step in to restrain those who control its flow. A century ago, the resource in question was oil. Now similar concerns are being raised by the giants that deal in data, the oil of the digital era. These titans—Alphabet (Google’s parent company), Amazon, Apple, Facebook and Microsoft—look unstoppable. They are the five most valuable listed firms in the world. Their profits are surging: they collectively racked up over $25bn in net profit in the first quarter of 2017. Amazon captures half of all dollars spent online in America. Google and Facebook accounted for almost all the revenue growth in digital advertising in America last year.

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http://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data...

For some people, artificial intelligence still makes them feel a little…uneasy. It’s often depicted as sinister-looking robots who will take over our lives and our jobs, or even replace humanity. 

The reality is, we are already in an age in which AI is infused into our everyday lives in ways that augment rather than replace people. Digital assistants such as Cortana can find you the closest restaurant, dictate a text to your friend, manage your email inbox and even help you create more beautiful PowerPoint presentations.  Whether you realise it or not, AI is an integral part of all these interactions. And while it’s not something you can often see or touch, I bet you’re already experiencing the benefits of AI every day.

So, how does AI technology actually work? AI is a machine’s ability to recognise images and words, learn and reason in ways that are similar to people. Data is the fuel for AI, and our world is awash with data as our daily interactions are increasingly digital. AI uses sophisticated algorithms to sort through piles of data, spot patterns and make predictions – tasks that would be repetitive and time-consuming, if not practically impossible, for people to do manually. AI can do this work on our behalf and give us back more of life’s most precious commodity - time.

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FIGURE 1 J'ai montré dans un post précédent, l'importance contemporaine de la curation collaborative de données.  Les compétences dans ce domaine sont au coeur de la nouvelle litéracie algorithmique.

La figure 1 présente ces compétences de manière systématique et, ce faisant, elle met en ordre les savoir-faire intellectuels et pratiques tout comme les « savoir-être » éthiques…

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

Big Data is powerful on its own. So is artificial intelligence. What happens when the two are merged?

Big data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the coming decade. As big data initiatives mature, organizations are now combining the agility of big data processes with the scale of artificial intelligence (AI) capabilities to accelerate the delivery of business value.

Big Data and AI at MetLife

Pete Johnson is one of the most experienced executives working in the field of big data and AI within industry today. Having worked in the field of artificial intelligence for a generation dating back to his academic career at Yale University, Johnson now leads big data and AI initiatives as a fellow at MetLife. Johnson previously held positions as senior vice president for Strategic Technology with Mellon Bank and served as the executive vice president and chief technology officer of Cognitive Systems Inc. (CSI), an early artificial intelligence company specializing in natural language processing, expert systems, case-based reasoning, and data mining. CSI was founded by several members of the Yale University faculty in 1981, when Johnson completed his MS in computer science.

Johnson, whom I’ve known for over a decade, is a regular participant in a series of executive thought-leadership breakfasts that I host for senior industry executives to share perspectives on topics in big data, AI, and machine learning among their peers. Participants in the most recent executive breakfasts have included chief data officers, chief analytics officers, chief digital officers, chief technology officers, and heads of big data for firms including AIG, American Express, Blackrock, Charles Schwab, CitiGroup, General Electric (GE), MetLife, TD Ameritrade, VISA, and Wells Fargo, among others.

As a long-suffering expert in the field of artificial intelligence, Johnson observes three critical ways in which big data is now empowering AI:

1. Big data technology — We have the ability now to process huge quantities of data that previously required extremely expensive hardware and software, or “commodity parallelism.”
2. Availability of large data sets — ICR, transcription, voice and image files, weather data, and logistics data are now available in ways that were never possible in the past; even old “paper sourced” data is coming online.
3. Machine learning at scale — “Scaled up” algorithms such as recurrent neural networks and deep learning are powering the breakthrough of AI.

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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

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

The concept of Big Data is a relatively new one. It denotes the availability of vast volumes and sources of data, which were not available before. By itself, Big Data is powerful, and when combined with Artificial Intelligence and machine learning, the opportunities presented by this combination are just endless.  As big data moves to the maturity phase, firms are now looking for ways to combine the scale of AI and the agility of Big Data processes to bring about an acceleration on the delivery of the much-needed business value.

The Power of Combining AI and Big Data
Most businesses are data-driven. As a result, firms with the right type and quantity of data has the upper hand over rivals. Convergence between AI and big data is promising. Firms can now access large volumes of broken down and categorized data by their usefulness. Traditional computer processors cannot process big data. Big data can best be processed by a GPU database, which has the flexibility needed to handle a significant amount of data of different types.

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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=Big+Data...