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In Brief:
New developments from Princeton University and the University of Texas-Austin have revealed odd behavior in electrons that could lay the foundation for a new generation of faster microchips, according to a study published in Science.
Anyone who does not have QC as part of their 5+Yr Roadmap for IT are truly exposing their company as well as shareholders and customers. China, Russia, Cartels, DarkNet, etc. will use the technology to extort victims, destroy companies, economies, and complete countries where folks have not planned, budget, skilled up, and prep for full replacement of their infrastructure and Net access. Not to mention companies who have this infrastructure will provide better services/ CCE to svc. consumers.
In a recent article, we highlighted a smart beta ETF called the “Sprott BUZZ Social Media Insights ETF” that uses artificial intelligence (AI) to select and weight stocks. If we stop and think about that for a moment, that’s a pretty cool use of AI that seems well ahead of its time. Now we’re not saying that you should go out and buy this smart beta ETF right away. It uses social media data. We know that on social media, everyone’s an expert and many of the opinions that are stated are just that, opinions. However some of the signals may be legitimate. Someone who just bought Apple is likely to go on telling everyone how bullish they are on Apple shares. Bullish behavior is often accompanied by bullish rhetoric. And maybe that’s exactly the point, but the extent to which we’re actually using artificial intelligence here is not that meaningful. Simple scripting tools go out and scrape all this public data and then we use natural language processing (NLP) algorithms to determine if the data artifacts have a positive or negative sentiment. That’s not that intelligent, is it? This made us start to think about what it would take to create a truly “intelligent” smart beta ETF.
What is Smart Beta?
We have talked before about how people that work in finance love to obfuscate the simplicity of what they do with obscure acronyms and terminology. Complex nomenclature is suited for sophisticated scientific domains like synthetic biology or quantum computing but such language is hardly merited for use in the world of finance. We told you before what beta is. Smart beta is just another way of saying “rules based investing” which has in fact been around for centuries, but of course we act like it’s new and start publishing all kinds of research papers on it. In fact, a poll offered up by S&P Capital IQ shows that even 1 out of 4 finance professionals recognizes the term “smart beta” to be little more than a marketing gimmick:
To all those who said it couldn’t happen for another 10+ years; this article is definitely for you.
Robert Wolkow, University of Alberta physics professor and the Principal Research Officer at Canada’s National Institute for Nanotechnology, has developed a technique to switch a single-atom channel.
What does it all mean? With applications for practical systems like silicon semi-conductor electronics, it means smaller, more efficient, more energy-conserving computers, as just one example of the technology revolution that is unfolding right before our very eyes (if you can squint that hard).
Machine learning will drop the cost of making predictions, but raise the value of human judgement.
To really understand the impact of artificial intelligence in the modern world, it’s best to think beyond the mega-research projects like those that helped Google recognize cats in photos.
According to professor Ajay Agrawal of the University of Toronto, humanity should be pondering how the ability of cutting edge A.I. techniques like deep learning —which has boosted the ability for computers to recognize patterns in enormous loads of data—could reshape the global economy.
“If we were to draw energy from a typical AA battery based on this design, it would last for a billion years.” — Sungsik Lee, PhD, in the journal Science.
The transistors can be produced at low temperatures and can be printed on almost any material, such as glass, plastic, polyester fabrics, and paper.
Similar to a computer in sleep mode, the new transistor harnesses a tiny “leakage” of electrical current, known as “near-off-state current.” This leak at the point of contact between the metal and semiconducting components of a transistor, the “Schottky barrier,” is normally an undesirable characteristic of all transistors.
There have been significant advances in developing new prostheses with a simple sense of touch, but researchers are looking to go further. Scientists and engineers are working on a way to provide prosthetic users and those suffering from spinal cord injuries with the ability to both feel and control their limbs or robotic replacements by means of directly stimulating the cortex of the brain.
For decades, a major goal of neuroscientists has been to develop new technologies to create more advanced prostheses or ways to help people who have suffered spinal cord injuries to regain the use of their limbs. Part of this has involved creating a means of sending brain signals to disconnected nerves in damaged limbs or to robotic prostheses, so they can be moved by thought, so control is simple and natural.
However, all this had only limited application because as well as being able to tell a robotic or natural limb to move, a sense of touch was also required, so the patient would know if something has been grasped properly or if the hand or arm is in the right position. Without this feedback, it’s very difficult to control an artificial limb properly even with constant concentration or computer assistance.
Tough times lay ahead for human workers. With the advent of automation comes a much smaller job market and an ever-shrinking work force. Jobs traditionally held by humans are now being taken over by robots and computer software. Now, another job sector is being threatened by automation: the public sector.
A study conducted by Oxford University and Deloitte, a business advisory firm, found that 850,000 public sector jobs in the UK are at risk of being lost by 2030 due to automation. The report also mentions how more than 1.3 million administrative jobs in the public sector have a 77% probability of being automated. These jobs include highly repetitive jobs like clerical work and transportation work.
–This report comes as good news to fiscal policy makers who wish to cut costs. It shows the government can save up to £12 billion in public sector wages by 2030.
