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Neil Movold

Neil Movold's Public Library

10 minutes ago

"The slides provide a quick overview of how the Cognitive Computing Era might impact the future of Education. The slides provide summary information, a list of trends to watch and links to additional resources "

  • The slides provide a quick overview of how the Cognitive Computing Era might impact the future of Education. The slides provide summary information, a list of trends to watch and links to additional resources

  • A ‘multi-tenant’ approach means we use different themes, organisational frameworks and reporting to give each organisation their own ‘branding’ and organisation-specific information as users access the site. Specific data reports are administered centrally by a Ko Awatea site administrator, ensuring accurate records can be kept on each separate organisation.
  • The success of the LEARN platform is down to the collaborative, open approach pioneered by Ko Awatea, CMDHB and Catalyst. The LEARN platform is helping New Zealand’s participating DHBs save around 300 hours of e-learning development time by being able to share resources, and sharing a single instance of Totara LMS is estimated to save up to $270,000 a year across all the organisations. Each DHB still maintains its own visual identity on the platform with multiple brands, and smaller DHBs benefit from the support of larger DHBs while being able to contribute back to the wider network by pooling their own resources.

  • Students who can do harder things with harder tests at an earlier age" and L.I.F.T (Learning Ideas From Text).

  • Cognitive computing combines artificial intelligence and machine-learning algorithms, in an approach which attempts to reproduce the behaviour of the human brain. An example is provided by the IBM company's Watson machine
    • It is quite simple actually: cognitive computing extends analytics levels to new kind of data, using new technologies.  Let us look at each of these.

        
         
      • Data.  In a nutshell, cognitive computing is especially useful when data is a large corpus of free text documents.  Think of Wikipedia, which was the data used for Jeopardy Watson.  Think of the scientific literature used  in Watson for Oncology.  In these use cases, cognitive computing is used to analyze millions of free text documents to support a wide range of activities.
      •  
      • New technology.  Dealing primarily with unstructured data and free text, cognitive computing drags on technologies like natural language processing and machine learning.  It can be seen as the current generation of artificial intelligence machines.  In particular, you don't program a system like Watson, you educate it.  Rather than coding into the system, you merely provide a large set of training examples.  For instance, Jeopardy Watson has been trained with a large number of Jeopardy questions and their corresponding answers.
      •  
      • Analyics Journey.  Watson offerings range from descriptive use cases such as data exploration to prescriptive use case like recommending a cancer treatment via diagnostic and predictive use cases like finding relations between concepts and ideas buried in literature.
  • Cognitive computing rather extend the analytics journey to areas that were unreachable with more classical analytics techniques like business intelligence, statistics, and operations research.  Moreover, classical analytics and cognitive computing are not mutually exclusive.  For instance Watson Analytics leverages cognitive computing to offer the benefit of traditional analytics techniques without their complexity.

  • However, human decision-making is subject to numerous cognitive biases that can easily distort judgement. For example, iconoclastic author Tom Peters highlights 159 cognitive biases that impact management decision-making (Peters, Tom. “159 Cognitive Biases Between You and Good Judgment (Good Luck!).” 29 May 2014). Emotions such as anxiety, fear or anger could easily cloud a person’s judgement. Human thinking is prone to the use of cognitive heuristics, a shortcut that may lead to biases and faulty decisions.
  • Given a computer is devoid of emotion and the hubris of human ego, it would seem logical that machine learning is not impacted by cognitive bias.
about 5 hours ago

"Cognitive computing has gained prominence as a major disrupter by enabling computers to interact with people in human-like ways. These systems understand and communicate in natural language, and leverage artificial intelligence to present new insights that far surpass those gleaned by human intelligence alone.

At the forefront of this technology, and cited by the 2016 Tech Trends report as the single most important innovator to watch, is IBM Watson.

With cognitive systems like Watson, we are now able to unlock the value in data that was previously inaccessible because it existed in an unstructured format or was dispersed in any number of separate silos. Cognitive systems think more like humans, at immense scale, which redefines what is possible to discover and to do. Over time, these new technologies will serve to transform jobs, businesses, customer experiences and entire industries."

  • Cognitive computing has gained prominence as a major disrupter by enabling computers to interact with people in human-like ways. These systems understand and communicate in natural language, and leverage artificial intelligence to present new insights that far surpass those gleaned by human intelligence alone.

     

    At the forefront of this technology, and cited by the 2016 Tech Trends report as the single most important innovator to watch, is IBM Watson.

     

    With cognitive systems like Watson, we are now able to unlock the value in data that was previously inaccessible because it existed in an unstructured format or was dispersed in any number of separate silos. Cognitive systems think more like humans, at immense scale, which redefines what is possible to discover and to do. Over time, these new technologies will serve to transform jobs, businesses, customer experiences and entire industries.

  • Cognitive computing, however, does not operate in a vacuum. The key to its success is two other trends on the Future Today Institute’s 2016 watch list: data and deep learning.
  • Harnessing Data Better With Cognitive Computing

     

    One of the reasons data made the list is because it is a key driver of many other technologies, including cognitive computing. Major industries, governments and individuals increasingly rely on data from an ever-expanding number of sources to help them do everything from fixing machines to making smarter purchases.

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about 5 hours ago

"Bootstrapping is an attractive way to launch and run a startup for many founders, primarily because it gives more freedom to the founders than getting investors to invest in the company. However, bootstrapping is also a very risky move, as doing so means you may not have lasting funds to cover operational costs.

Too many promising startups have failed because the founders neglected to make informed decisions with their limited funds or utilize their available resources to their full potential. That is why we here at the Founder Institute created an exhaustive guide that shows you how to make the most of what you have for your bootstrapped startup."

  • I try and focus the government on being evidence-based and outcomes focused and I will talk to anybody who wants to push that agenda along,” he says. “It does not matter whether they are left, right or green.
  • Leaving a full-time government role over a year ago has allowed him to work on this goal with more organisations. He works with central government agencies, including the Inland Revenue Department, Ministry of Education, Treasury, MSD and New Zealand Productivity Commission. He is currently on the board of Te Pūnaha Matatini, the Centre of Research Excellence (CoRE) dedicated to the study of how to transform complex data into knowledge.
  • that one thing is try to ‘add heat’ to remove complacency within government and the state sector.

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  • The overwhelming majority of the human population suffer from varying degrees of confirmation bias. We pick and choose data that match our predominant world view or set of beliefs, and often discount the rest. In these situations, it’s not the data that is faulty, or even that providing open data for people to use is a bad thing - rather I’m simply stressing that we need to be continually questioning our motivations behind using the data that we’re using, the pictures that it paints, and the subsequent action steps taken.
     
Aug 29, 16

"The lecture was given in a Cognitive and Analytics workshop at Indian Institute of Management. Topics covered was -
1) Understanding Natural Language Processing, Classification, Watson & its modules
2) Industry applications of Cognitive Computing
3) Understanding Cognitive Architecture
4) Understanding the disciplines / tools being used in Cognitive Science"

  • The lecture was given in a Cognitive and Analytics workshop at Indian Institute of Management. Topics covered was -  
    1) Understanding Natural Language Processing, Classification, Watson & its modules 
    2) Industry applications of Cognitive Computing  
    3) Understanding Cognitive Architecture 
    4) Understanding the disciplines / tools being used in Cognitive Science
Aug 26, 16

"Cognitive computing will usher in a new wave of change, giving organisations the power to gain insights and make decisions from vast amounts of data. Over the next 12 to 18 months these new systems will begin to replace the programmable computers we have known since the 1940s. Instead they will use natural language recognition and machine learning to discover new insights from vast amounts of unstructured data, at a speed never before possible."

  • Cognitive computing will usher in a new wave of change, giving organisations the power to gain insights and make decisions from vast amounts of data. Over the next 12 to 18 months these new systems will begin to replace the programmable computers we have known since the 1940s. Instead they will use natural language recognition and machine learning to discover new insights from vast amounts of unstructured data, at a speed never before possible.
  • “In education we will have personalised education. At some time in the future, you will have a system that follows you for life and knows what you know and what you need to know and the gaps in your knowledge. It knows how you learn and how to help you understand and get up to speed on any new topic you need to know; you will have the sort of one-to-one education that we can only hope to have today.”
  • Walsh says IBM’s use of the term “augmenting” is a sensible move since artificial intelligence bristles with emotional baggage. “That will be how we protect people’s jobs and give a good outcome for people, and not just have wealth concentrated in the hands of the owners of the robots,” he says.

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Aug 26, 16

"Who we are: academic and industrial researchers, practitioners, software developers, end users, and students.

What we do:

Promote and support the growth and application of AI principles and techniques throughout computing
Sponsor or co-sponsor high-quality, AI-related conferences
Organize the Career Network and Conference (SIGAI CNC) for early-stage researchers in AI
Sponsor recognized AI awards
Support important journals in the field
Provide scholarships to student members to attend conferences
Promote AI education and publications through various forums and the ACM digital library"

Aug 26, 16

"UX innovator discusses what forward-thinking schools are doing now, and what AI in education will look like in the near future."

Aug 25, 16

"By sifting through recent articles, guides, top ten lists, and infographics written by experts around the web, we've distilled the Top 3 pieces of advice that entrepreneurs need to know on a key topic. "

  • By sifting through recent articles, guides, top ten lists, and infographics written by experts around the web, we've distilled the Top 3 pieces of advice that entrepreneurs need to know on a key topic. 
Aug 25, 16

"It's summertime, but that doesn't mean we don't feel stressed. In fact, some of us might feel even more winded having to carry the extra workload of people who are out on two-week vacations to the south of France. An entrepreneur I know said he'd just gone through the most stressful period of the year trying to raise money while every investor seemed to be out of town. "I’ll never do that again," he said.

Whatever is causing you stress, you don't need to let it ruin your day or your life. Here are five ways successful people deal with everyday aggravations:"

  • Whatever is causing you stress, you don't need to let it ruin your day or your life. Here are five ways successful people deal with everyday aggravations:

     

    1. Do the hard stuff first.

  • Self service has become one the most lucrative marketing campaigns of the last few years in the realms of business intelligence (BI) and analytics, second only to Big Data. Every vendor in the BI and analytics space makes this claim, with perhaps no exception. Self-service data sensemaking, however, is an example of false advertising that’s producing a great deal of harm. How many bad decisions are being made based on specious analytical findings by unskilled people in organizations that accept the self-service myth? More bad decisions than good, I fear.
  • Some software vendors frame their products as self service out of ignorance: they don’t understand data sensemaking and therefore don’t understand that self service doesn’t apply.
  • The few software vendors that understand data sensemaking frame their products as self service because the deceit produces sales, resulting in revenues.

7 more annotations...

  • Self service has become one the most lucrative marketing campaigns of the last few years in the realms of business intelligence (BI) and analytics, second only to Big Data. Every vendor in the BI and analytics space makes this claim, with perhaps no exception. Self-service data sensemaking, however, is an example of false advertising that’s producing a great deal of harm. How many bad decisions are being made based on specious analytical findings by unskilled people in organizations that accept the self-service myth? More bad decisions than good, I fear.

  • Cognitive computing has the potential to reshape how work gets done, how businesses grow, and how markets and industries evolve by delivering automated, evidence-based responses that drive better outcomes. Learn how Deloitte is focused on using cognitive computing as a positive disruptor.
  • says Mike Rhodin, SVP, IBM Watson Group. Deloitte currently serves IBM as a client in 45 countries.
Aug 22, 16

"e theory of disruptive innovation, introduced in these pages in 1995, has proved to be a powerful way of thinking about innovation-driven growth. Many leaders of small, entrepreneurial companies praise it as their guiding star; so do many executives at large, well-established organizations, including Intel, Southern New Hampshire University, and Salesforce.com.

Unfortunately, disruption theory is in danger of becoming a victim of its own success. Despite broad dissemination, the theory’s core concepts have been widely misunderstood and its basic tenets frequently misapplied. Furthermore, essential refinements in the theory over the past 20 years appear to have been overshadowed by the popularity of the initial formulation. As a result, the theory is sometimes criticized for shortcomings that have already been addressed.

There’s another troubling concern: In our experience, too many people who speak of “disruption” have not read a serious book or article on the subject. Too frequently, they use the term loosely to invoke the concept of innovation in support of whatever it is they wish to do. Many researchers, writers, and consultants use “disruptive innovation” to describe any situation in which an industry is shaken up and previously successful incumbents stumble. But that’s much too broad a usage.

The problem with conflating a disruptive innovation with any breakthrough that changes an industry’s competitive patterns is that different types of innovation require different strategic approaches. To put it another way, the lessons we’ve learned about succeeding as a disruptive innovator (or defending against a disruptive challenger) will not apply to every company in a shifting market. If we get sloppy with our labels or fail to integrate insights from subsequent research and experience into the original theory, then managers may end up using the wrong tools for their context, reducing their chances of success. Over time, the theory’s usefulness will be undermined."

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