Skip to main content

Neil Movold

Neil Movold's Public Library

    • In our experience, most people think good listening comes down to doing three things:

      • Not talking when others are speaking
      • Letting others know you’re listening through facial expressions and verbal sounds (“Mmm-hmm”)
      • Being able to repeat what others have said, practically word-for-word

  • Allianz Risk Transfer AG (ART) and Nephila Capital Limited (Nephila)   announce that they have successfully piloted the use of blockchain smart   contract technology for transacting a natural catastrophe swap.
  • significantly accelerated and   simplified by blockchain-based contracts
  • Blockchain-based smart contract technology has the potential to   facilitate and accelerate the contract management process of such cat   swaps and bonds. Each validated contract on the open shared   infrastructure contains data and self-executable codes inherent to that   contract. When a triggering event occurs which meets the agreed   conditions, the blockchain smart contract picks up the predefined data   sources of all participants, and then automatically activates and   determines payouts to or from contract parties.

3 more annotations...

  • Cognitive Solutions saw revenue grow by 3.5% as cloud revenue flew higher by 54% during the quarter.
  • IBM is an enormous business, even after years of declines and replacing all of that revenue in any manner is going to be very challenging.
  • As I mentioned, IBM's "strategy" for a very long time has been to just buy back as much stock as possible to juice EPS instead of actually creating a sustainable business model.

1 more annotation...

  • “We believe technology will drive the future of insurance,” said Laura Taylor, managing principal at Nephila. “We have invested a great deal accordingly and are pleased to extend our long-standing strategic partnership with ART (Allianz Risk Transfer) to use of the blockchain.”
  • Michael Eitelwein, the head of disruptive technology at Allianz Group.

  • Below are 35 proven psychological phenomena that affect you and your students every day:
  • Cognitive psychologists use the term metacognition to describe our ability to assess our own skills, knowledge, or learning.

  • But lost in this clinical sequence are the Habits of Mind that (often predictably) lead to success or failure in the mastery of given standards. In fact, it is not in the standards or assessments, but rather these personal habits where success or failure -- in academic terms -- actually begin.
  • The habits themselves aren't new at all, and significant work has already been done in the areas of these "thinking habits." However, in a 21st century learning environment -- one often inundated with information, stimulation and connectivity -- there may be a newfound context for their application.
  • Applying Past Knowledge to New Situations

  • We need emotion to make decisions, if we lacked feeling (as certain brain-damaged patients do), we would become incapable of making a decent decision.
  • "Nature appears to have built the apparatus of rationality not just on top of the apparatus of biological regulation, but also from it and with it,"
  • Emotion and feeling act as the bridge between rational and nonrational processes. And effective decision-making, as he sees it, would not be possible in the absence of emotional input to provide both motivation and meaning.

8 more annotations...

  • Research shows that decision-making is inextricably tied to emotion.
  • This means that decision-making is actually tied to mood regulation. Indeed, anxiety and depression are often categorized as feelings of immobility, being stuck, and an inability to make decisions.

  • “It’s the Uber for X” has given way to “It’s X plus AI” as the default business model for startups.

  • As of 2016, a rough rule of thumb is that a supervised deep learning algorithm will generally achieve acceptable performance with around 5,000 labeled examples per category, and will match or exceed human performance when trained with a dataset containing at least 10 million labeled examples."
  • I will now go back to designing a computer control system for a complex chemical plant. It is hard work. Computers are very good at paying attention and reacting quickly, but very poor at noticing things that they have not been taught to notice. They are bad at understanding context or asking questions. That's why we still have operators. The operators sit around more than they used to, have to think more abstractly than they used to, supervise more production than they used to, and tend towards overweight more than they used to. I am comfortable with our automated future.

  • The current boom is based on an old idea, with a modern twist: so-called artificial neural networks (ANNs), modelled on the architecture of the human brain.
  • A simple ANN has an input layer of neurons where data can be fed into the network, an output layer where results come out, and a few hidden layers in the middle where information is processed.
  • But things have changed in the past few years, for three reasons. First, new training techniques made training deep networks feasible. Second, the rise of the internet has made billions of documents, images and videos available for training purposes.

3 more annotations...

Jul 18, 16

The terms “machine learning” and “artificial intelligence” are often used interchangeably, as they both have a similar meaning. Artificial intelligence is intelligence exhibited by machines or computers. Machine learning is a subtext of artificial intelligence, describing the study in which the AI is created.

  • Professor Shaun Hendy is the Director of Te Pūnaha Matatini, a New Zealand Centre of Research Excellence hosted by the University of Auckland. Te Pūnaha Matatini is a national research network that uses methods from complex systems to solve problems for business and to develop better economic and environmental policies.

  • At the same time as many scientists are becoming less accessible, we’re facing environmental and societal problems that science can help solve.

  • Te Pūnaha Matatini is training a new type of scientist for the benefit of New Zealand; we offer research projects that develop scientific skills that are relevant to our economy, society, and environment.
  • We’re working to build the kind of New Zealand of which we can all be proud – showcasing excellent and relevant transdisciplinary research in New Zealand, and promoting the role of science and research to New Zealand communities.
  • We’re working together with New Zealand industry, government, and communities to enable New Zealanders to grow up and thrive in an increasingly complex and interconnected world.

1 more annotation...

  • This is a new CoRE, established in 2015. It aims to develop methods and tools for transforming complex data into knowledge for better decision-making. Research themes include complex data analytics, complex economic and social systems, and complexity and the biosphere.
Jul 15, 16

"The term Artificial Intelligence was originally coined by John McCarthy in 1955, defining it as “the science and engineering of making intelligent machines”. Now more than a half a century old, the field of AI and machine learning is finally achieving some of its oldest goals by being used successfully in areas such as data mining, industrial robotics, logistics, speech recognition, banking software, medical diagnosis and search engines.

Tech giants have all been investing heavily in AI and Machine Learning. In 2010 Facebook introduced facial recognition technology, and in 2013 Mark Zuckerberg dedicated a lab to AI research. In 2014 Google bought artificial intelligence startup DeepMind for $400 million (£263 million), making it one of the largest tech acquisitions to date. Microsoft have also been investing heavily in AI with their project Oxford, which uses an emotion detection service that can assign an emotion to a person depending on their facial expression. This kind of facial recognition allows photos to be edited depending on the feelings expressed in them.

IBM have also been making large strides in AI and Machine learning with their Watson computer which famously won the US quiz show Jeopardy in 2011, outperforming his human counterparts. IBM and have now teamed up with Nvidia incorporating Nvidia’s Tesla K80 GPUs, making Watson 1.7 faster at responding to inquiries. IBM are also developing a teaching assistant app that will plan lessons based on approved material.

Apple has bought artificial intelligence startup Emotient and while it’s not completely clear what Apple’s plans are, reports suggest that the acquisition will centre on facial recognition technology and customers reaction to ads. Apple have also acquired UK-based AI company Vocal IQ with reports suggesting that they are aiming to develop Siri further and use Vocal IQ’s speech AI software.

From Q1 to Q3 2015 we saw $47.2 billion invested in AI and Machine Learning, and with roughly 900 companies working in the AI field tackling problems in business intelligence, finance and security, the centuries’ long quest to develop machines and software with human-like intelligence inches closer to reality."

  • Take a break after you've absorbed new information, then exercise in a few hours to improve your ability to recall what you learned.

  • It's an illusion of consciousness, since, in reality, what we are aware of at any given moment is a fraction of what is really going on and which we are aware of in other, albeit, unrecognizable ways.

    Consciousness is a filter that has been created to screen out the bigger part of reality it has been conditioned to ignore. We perceive what it has been taught and what it allows to come through our senses.

  • Big Data tackles this problem from the other direction. The data are poorly defined, much of it may be inaccurate and much of it may in fact be missing.
     Big Data has to have enough volume so that the amount of bad data or missing data becomes statistically insignificant.
  • The abundance of available data means also that the trend was shifting from Business Intelligence (inherently  descriptive statistics ) where data is used to measure things, detect trends, etc.. to the use of  inductive statistics to infer laws from large sets of data  to reveal patterns, relationships and dependencies, or to perform predictions of outcomes and behaviours.
  • Data Science is all about extracting knowledge from data, either structured or unstructured, and incorporates many diverse skills such as mathematics, statistics, artificial intelligence, computer programming, visualisation, image analysis, and much more.

6 more annotations...

1 - 20 of 3111 Next › Last »
20 items/page

Highlighter, Sticky notes, Tagging, Groups and Network: integrated suite dramatically boosting research productivity. Learn more »

Join Diigo