How will applications of machine learning change in the next 10 years
What are the shortcomings of machine learning
What language do you think is best to write a machine language application in
How can machine learning differentiate between a recorded voice and a real one
In what ways does Pindrop’s audio machine learning differ from conventional forms of ML
How is the Atlanta tech scene different from Silicone Valley
A month or so ago I found a discussion on Machine Learning on Quora. Are you familiar with Quora? It is a cool app. You pose a question to Quora requesting an answer, Quora puts the question out in cyberspace and whoever wants to answer can do so. Interesting to spend so time on.
The above questions were answered by Professor Vijay Balsubramaniyan PH.D. at Georgia Tech University in Atlanta Georgia. The first question he addresses is:
How will applications of machine learning change in the next ten years
Answer requested by Ashish Ranjan, Gyanendra Kumar, and 94 others
His answer struck me because I had not heard that this was the plan or I just wasn’t paying attention. But it makes great sense. He said that the future of ML or any technology makes it more human. I just heard an ad for Google. They claim that their computer voice for answering machines is indistinguishable from a human voice. That will be interesting to check out.
Machine learning he says is getting close in specific areas such as image recognition and classification, speech recognition for self-driving cars. “For example, Googles’ word error rate for speech recognition has gone from 30% in 2012 to 5% in 2017. That’s the difference between understanding 13 words out of 20 (2 sentences out of 3) to 19 words out of 20.” The difficulty is the last mile (95% to 99%).
He indicated that researchers expect to make significant strides in the next 10 years. Now that is the comment of a researcher. He didn’t say they were expecting to solve the problem in 90 days, 365 days but in terms of years. And quite a long time also. An interesting goal that they have also “computers will make our everyday tasks easier at home, at work, everywhere we go.”
What are the shortcomings of machine learning
Answer requested by Gyanendra Kumar, Hasha Ramanagoudra, and 44 others
Machine learning has several shortcomings he admits. First ML is only as good as the quality of data used. The old “garbage in, garbage out.” As everything gets more voluminous and complex the challenges increasing can lead to false conclusions such as ‘seeing what you want to see.’
He states that “ML helps technology become more human but it is necessary to guard against it absorbing our deeply ingrained human biases.”
“The ML model that you are working with needs to be critically evaluated using traditional experimental methods. Its strengths and weaknesses have to be identified. All of this is more challenging than developing the model in the first place.”
A Short Aside
Vijay and two other PhDs founded a company called Pindrop Security. They serve the global marketplace by phone anti-fraud and authentication technology. They primarily work with Call Centers. Their applications provide audio analysis technology analyzes 147 different features of a phone call. In 2015 Pindrop screened more than 360 million calls and raised $122 million in funding. In 2017 they protected 410,826,795 phone calls, detected 401,926 fraud calls, generated $200,500,000 in savings for their clients. The company’s mission statement is: “Our Mission is to provide security, identity, and trust in every voice interactions.”
What language do you think is best to write a Machine Learning application in
Answer requested by Jamie Corkhill, Harsha Ramanagoudra and 79 others
According to IBM research, Python is the most popular language currently used for Machine Learning. It has flexibility, an abundance of strong ML packages like stikit-learn, and they can easily replace critical routines with C/C+ when necessary.”
He did suggest keeping an eye on Golang which is gaining in ML support and popularity.”
How can machine learning differentiate between a recorded voice and a real one, given that the quality of the recorded voice is fairly good
Answer requested by Pushkar Sharma, Hammad Arshad and 9 more.
“Even the most realistic recorded voice that sounds legitimate to the human ear retain some trace features that are different from the live voice of the genuine speaker. These features are often emphasized (example played back in higher volume) while analyzing the spectral characteristics of the signal.”
Thoughts on Adversarial Machine Learning
Answer requested by Amit Jadhav, Praveen Krishna and 14 more
“Adversarial machine learning is a particular class of online machine learning that is intended for computer security.”
While typical (offline) machine learning tools use fixed training data and assume that the unseen test data follows the same distribution as the training data. Adversarial machine learning tools are continuously adapting to the ever-changing distribution of data.
This is often the case in authentication systems where malicious impostors keep looking for new vulnerabilities to defeat them.
“Adversarial machine learning is very important at Pindrop. Fraudsters keep changing their attack techniques and are becoming smarter over time.”
“Our fraud prevention system is in a continuous evolution to keep catching new kinds of fraud activities over the voice channel.”
We have heard that refrain several times lately. Elon Musk has proclaimed it, Steven Hawking has warned us of the same.
So Trump portrays Mexico and China and global trade as the enemies. What is he talking about?
Back on January 26 of 2017, he declared: “It has been a one-sided deal from the beginning of NAFTA with massive numbers of jobs and companies lost”. Hmm
President Obama stated “The next wave of economic dislocations won’t come from overseas. It will come from the relentless pace of automation that makes a lot of good middle-class jobs obsolete.” He offered these words of caution during his farewell address.
Research supports Obama’s claim. Far more jobs are lost to robots and automation (better technology) than trade with China, Mexico or any other country.
America has lost jobs to trade, but robots are the big threat. Any job that is repetitive in nature and even more so if it is hazardous to worker’s health are in danger of being replaced by robots.
In Manufacturing, nearly 5 million jobs have been lost.
Real Numbers for Real Issues:
U.S. Trade with China killed 985,000 American manufacturing jobs between 1999 and 2011
per MIT professor David Autor
U.S. Trade with Mexico cost roughly 800,000 jobs between 1997 and 2013
per Robert Scott, Economic Policy Institute
That might sound high. But last year alone the US added more jobs than those losses combined. And remember Mexico imports 40% of its goods from the United States.
Additionally, two Ball State professors found that between 2000 and 2010 about 87% of the manufacturing job losses stemmed from factories becoming more efficient.
The main driver of more efficiency? Automation and Better Technology.
J. Bradford Jensen, an economics professor at Georgetown University stated “There has been a lot of technical change that has reduced the need for labor – some of it is automation, some of is design, more software, less hardware.
So why not crack down on robots?
“It’s harder to demonize what everyone sees as technical progress. It’s easier to demonize the foreigner,” Jenson added.
It’s hard to really get solid numbers when talking about automation because it also creates jobs. ATMs are a case in point. They perform jobs that bank tellers one did. But there isn’t much evidence that bank employment tanked as a result of ATMs. MIT professor Daron Acemoglu
One last point to consider. Mexico imports goods. 40% of those goods are American.
Editors note: I recommend reading a post I wrote New Year’s weekend. It is on my blog “dabblerducksbutt.com” The title is Capitalism Overreach.
It is a story of coal mining in West Virginia. As you know the miners of West Virginia did not get a chance to enjoy the fruits of the twentieth century. Hopefully, we will use this example to ensure that no family, no community is left behind in this Fourth Industrial Revolution.
If the job loss rate is even close to 47% the pain felt by the middle class and working families is going to be unimaginable. There won’t be other jobs to go. Nowhere to live.
I have found so much more material that I am going to digest and file another post shortly after this one.
I must discuss all the changes that have occurred in the space. Did space change? Not more than usual I don’t think. This blog why such a moronic title? It’s the end of the year and all writers thrown everything that didn’t get printed during the year into one big garbage dump at year end. Or maybe not? Hmm
The First Year End of the Deep Education Web.com Blog
One thing that struck me as a bit unusual that occurred this year is the new or potentially new findings of life on other worlds. More on that in a minute.
Introducing the Dark “Hole” in the Sun
This image of the sun is rendered in Ultra Violet by NASA’s Solar Dynamics Observatory. This particular dark hole appeared because the star has an always-on magnetic field so it can get kinks and bends which can then cause sunspots and solar flares. They can also open the corona of the sun, the plasma that surrounds all-stars. These holes allow solar winds to rush into space. This may be an ordinary occurrence but it sure is spectacular. On the other hand, they can cause disturbances to satellite and power grids. They also supercharge the planets auroras, the northern and southern lights. Last month the Northern Aurora Borealis was seen as far south as Nebraska.
As it moves to its minimum of the 11-year cycle in 2019 the holes will become longer lasting and longer lasting. These holes can last several sunny days which is about 27 earth days.
Thanks to LiveScience for the image and information.
Hubble is Going Away
Did you know it is being replaced? In the spring of 2019, the James Webb Space Telescope will lift off. It will do so much more than Hubble did. I don’t know how that is going to be possible. From day 1 when the images were less than stellar (pun intended), I have blown away. I wish I could spend every day, all day long going thru images or roses and space. They are both magically enthralling.
The James Webb Space Telescope, JWST for short, will support thousands of scientists around the world with its new technologies. It is a collaboration of NASA, ESA (the European Space Agency), and CSA (the Canadian Space Agency. It will be managed by the Goddard Space Flight Center in Maryland just as Hubble is. The industrial partner is Northrup Grumman. I was caught in a moment of introspection when this article said that the name JWST was arrived at in 2003. Imagine that this has been in the works for more than fourteen years.
Introducing the First Alien Moon
During the week of July 28, 2017, astronomers were teased by a discovery of great magnitude. They or actually the Kepler Space Telescope, found what may be the first exomoon. An exomoon is a name given to objects that revolve around exoplanets. Now isn’t that helpful? ‘Exo’ means that the objects from outside of our solar system.
This is a huge moon, named Kepler 1625b since it revolves around planet Kepler 1625. This pair is 4,000 light years from earth. A lightyear if I remember correctly from grade school (yes since was around back then!) is the time that light traveling in a vacuum to travel can travel in one Julian year, about 365.25 days. The actual computation is about 5.9 trillion miles!
The Wonder of Kepler
Kepler hunts for planets by looking for a telltale dip in a star’s brightness as another object passes in front of it. To find a moon is the same process but much more difficult. I looked for more current information but it is not yet available. The Hubble Space Telescope had been booked for examining and confirming the existence of this moon during the month of October that just passed.
This moon is BIG. Much bigger than Ganymede that revolves our Jupiter. The really big deal of this discovery (fingers crossed) is that it will be the first moon detected in orbit around an alien planet. This marks a new chapter in the astronomer’s study of the cosmos. I would have loved to hear Carl Sagan narrate this story. He had such a great way of transferring his excitement of these incomparable discovery’s that are so far away seem, not really intimate, but close to home, I guess. He maintained his awe in spite of the drab scientific jargon.
These quests are not just to find objects, these massively smart space telescopes look back into time when the universe was just beginning. Kepler has been a massively successful telescope. In June astronomers used data gathered by Kepler, to identify 219 alien candidates that may be habitable by scientific standards like earth. How do we earthlings get off thinking that we are superior beings? I am utterly humbled by these discoveries. I understand we are heading back to the moon.
I assume that the age-old arguments regarding what path to take still continues. Werhner von Braun, the German scientist turned American Citizen had his path squarely in mind. First a shuttle, then a space station and then the moon and then Mars. Obviously, we didn’t take that path. I guess I can understand how reaching the moon would have more PR power than building a shuttle. What amazes me, is that von Braun was so clear-minded about the future. He died at 65 years of age four years before the first shuttle flew. What a remarkable man.
The Cassini Space Telescope just complete its 13 years of examining Saturn and the neighborhood. It took Cassini 7 years to reach Saturn.
The other hand of wonder must be an assessment. Maybe it is just that time. Cassini flew from the earth in 1997 and ended this year. Maybe I am just gauging success by how many things are left flying by the time I fall to earth. Doesn’t make much sense does it.? But there has to be an answer in there somewhere…
The CEO of Boeing and Elan Musk are getting competitive. Denis Muilenberg is probably betting on the fact that Mr.Musk and his Space X rockets is always a bit overoptimistic.
What thoughts bend your brain waves? Are you an explorer or a scientific man. One item that seems to augur well for the scientific man is the photo that an astronaut took on his last day in Space, as he departed the Space Station.
Introducing The Last Space Piece for the Year 2017
It seems scientists, specifically astronomer’s can’t get enough of Kepler. The artist’s illustration of how Kepler might look today is courtesy of Reuters.
In June 2017 astronomers confirmed that Kepler has found 10 new Earth-size planets.That brings the total to 50 is what impressive? Wait there’s more: Kepler has already discovered 4,034 potential exoplanets of which 2,335 have been confirmed by other telescopes as actual planets. Now, which students are not going into astronomy or astrophysics, or evening someday composing a hit song like “Stardust”.
“And now the purple dusk of twilight time
Steals across the meadows of my heart
High up in the sky little stars climb
Always reminding me that we’re apart
You wander down the lane and far away
Leaving me a song that will not die
Love is now the stardust of yesterday
The music of the years gone by.
Sometimes I wonder, how I spend
The lonely nights
Dreaming of a song
Haunts my reverie
And I am once again with you.
When our love was new
And each kiss an inspiration
But that was long ago
And now my consolation is in the stardust of a song
Beside the garden wall, when stars are bright
You are in my arms
Tells his fairy tale
Of paradise, where roses grow
Though I dream in vain
In my heart it will remain
My stardust melody
The memory of love’s refrain.
1927 Hoagy Carmichael, Stardust Lyrics 1929 by Mitchell Parish
Hit song by Nat King Cole and by Natalie Cole, Willie Nelson and many more
“Courage is the enforcing virtue, the one that makes possible all the other virtues common to exceptional leaders: honesty, integrity, confidence, compassion, and humility”.
“We are taught to understand, correctly, that courage is not the absence of fear, but the capacity for action despite our fears.”
The above quotes were made by one of the most famous, most articulate and self-effacing men I have watched. He was a prisoner of war in North Vietnam’s Hanoi Hilton for more than five years of torture and mistreatment of the worst kind. He has been a United States Senator and is now one of our great Elder Statesmen. He will rank with all of the great ones of yesteryear and he may be the last one to come our way.
At the time of this great speech, to honor him with the award of the Liberty Medal, he is fighting terminal brain cancer. Senator McCain has fought the good fight. He has won all the battles that needed winning. He has already won the war against lesser men who spout inane stupidities and have no regard for the great country that we are. He has been a staunch supporter of the people of Arizona and of the United States of America. He will live long in our memories.
In his honor, I am going to feature images of the great state of Arizona.
Artificial Learning, Deep Learning, Machine Learning
“How they’re different and why are they all essential to the Internet of Things”
I had to go back and reread the post last time discussion of Artificial, Deep and Machine Learning. Not only are they fascinating topics to study, they may even be good topics for conversation.
Today we will look at the explanations by Calum McClelland. He is the Director of BD@Leverage. “Striving to change myself and the world for the better.”
I found his article in Medium. What an excellent source of writing. Beginners, long-lived writers, topics from A to Z.
Mr. McClellan starts his discussion by getting everybody on the same page. “We’re all familiar with the term “Artificial Intelligence.” After all, it’s been a popular focus in movies such as The Terminator, The Matrix, and Ex Machina. I like The Matrix series. How would a writer keep all the plot lines, characters, scenes, dialog all straight? No doubt by taking better notes than I!
“I’ll begin by giving a quick explanation of what AI, ML, and DL actually mean and how they’re different.” Mr. McClelland begins.
He continues “then, I’ll share how AI and the Internet of Things are inextricably intertwined, with several technological advances converging at once to set the foundation for an AI and IOT explosion.”
He certainly called that right. I read this article on February 2nd, 2017. Let’s try to anticipate what he predicted and what has been taking place in the same 8 months.
John McCarthy, in 1956, first coined the phrase AI. AI can perform tasks that are characteristic of human intelligence. Generally, it includes planning, understanding language, recognizing objects and sounds, learning and problem-solving.
“We can put AI in two categories, general and narrow. General AI would have all of the characteristics of human intelligence, including the capacities mentioned above. Narrow AI exhibits some facets of human intelligence, and can do that facet extremely well, but is lacking in other areas. A machine that’s great for recognizing images but nothing else would be an example of narrow AI.”
Machine learning is simply a way of achieving AI. Hmm, this discussion seems a bit looser than the one we looked last time, at least it seems easier to read.
Arthur Samuel coined the phrase Machine Intelligence in 1959. He defined it as,”the ability to learn without being explicitly programmed.” You can get to AI without using Machine Learning but oh it would take building millions of lines of codes with all the complex rules and decision-trees.
Instead of hard-coding software routines to execute a particular task, machine learning is a way of ‘training’ an algorithm so that it can learn how. “Training” involves dealing with massive amounts of data sets and then allowing the algorithm to sort itself out by adjusting and improving. Something like the Marine Corps teaches ‘Adjust and Execute’. At least it did when my three sons were in a few, well about 20, years ago. That really dates me and believe me I can feel every pulled muscle and strained ligaments from each misstep from during that time.
Machine learning has been instrumental in improving computer ‘vision’ (the ability of a machine to recognize an object in an image or video). Gather millions of pictures and have humans tag them. They would take a picture of a dog and of a cat. When the algorithm is instructed to build a model of a cat it can tell the difference. When it has performed this feat accurately thousands of times it has ‘learned’ what the difference between that cat and that dog.
Deep learning is one of the many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, and others.
Deep learning was inspired by the brain, its structure, and function. Also how the neurons were interconnected. Artificial Neural Networks ( ANNs) are algorithms that mimic the biological structures of the brain.
“In ANNs, there are “neurons” which have discrete layers and connections to other “neurons. Each layer picks out a specific feature to learn, such as curves/edges in image recognition.
It’s this layering that gives deep learning its name, otherwise stated as “depth created by using multiple layers as opposed to a single layer. The last time we learned that, just before going to press, IBM announced that they had made great strides in ‘speeding up’ these process which will save incredible amounts time to learn and get functioning.
Artificial Intelligence and IoT are much like the relationship between the human brain and body.
“Our bodies collect sensory input such as sight, sound, and touch. Our brains take that data and make sense of it, turning light into recognizable objects and sounds into understandable speech. Our brains then make decisions, sending signals back out to the body to command movements like picking up an object or speaking.”
This Internet of Things is like our body, sensors connected and raw data streaming in and forwarded to the ‘brain’. Artificial intelligence making sense of that data and deciding what actions to perform. The connected devices of IoT are on the receiving side, carrying out the actions or communicating with other devices.
Unleashing The Other’s Potential
His example of IoT and artificial intelligence are like two hands waving in the air. If we use only one hand only a small fraction of what is possible is accomplished. With both hands waving, both the value and the promise are multiplied.
Machine learning and deep learning have led to huge leaps in AI. Both of these require massive amounts of data and the data is being collected by billions of sensors. The more data the better the AI.
The more AI is improved the more IoT will be adopted. I think we have reached, and maybe gone a little past, ‘the tipping point’. Almost every day some new item, product, or process is being touted as the next best….hair dryer, semi truck, pizza maker. Just as IoT makes AI better, AI makes IoT more useful.
In industry, AI can be applied to predict when machines will need maintenance or analyze a manufacturing process to make gains in efficiency and generating large savings in dollars.
Medium, Artificial Intelligence, Machine Learning, and Deep Learning Calum McClelland September September 26, 2017
Regarding consumers, the push seems to be, make technology adapt to us rather the other way around. A big example is in speech recognition. Every week somebody says they do it better.
I just hope that one day, some machine can understand my speech. The older I get (and the more teeth that I lose, the less the machines can understand me).
Until then I will let productivity slide by me as I continue my old prehistoric ways.
This year particularly the role of speech is seen everywhere, or at least in all the new products that Amazon is pushing. A size and shape of Alexa for everybody. “Alexa what time is it?”. The time is, as the lights dim and the bells chime, bedtime. In the meantime, Alexa adjusts the thermostat, locks the doors and opens the refrigerator so I can get a snack on the way upstairs.
“CONVERGENT TECHNOLOGICAL ADVANCEMENTS HAVE MADE ALL OF THIS POSSIBLE”
More powerful computer chips and improved manufacturing techniques translate into cheaper, more powerful sensors.
Additional advancements are coming in the technology of batteries. Elon Musk was able to improve the battery power and life during the recent hurricanes. By sending out a code to all the Tesla’s that had been purchased whether or not they had purchased the battery upgrade. Understandably the code upgrade only lasted a few weeks. Of course, you can always go in a ‘buy’ an upgrade.
Wireless connectivity is another improvement. Smartphones and data transfer rates are allowing all these sensors to send data to the ‘cloud’. I can attest to the improvement. Rather than pay $100 per month for the high-speed internet of 60 megabytes, I now pay $20 for the use of a ‘Homebase’. A fancy name for a small box that reaches out and touches you at about 3.0 megs tops. Slower, sometimes more noticeable than others but the price is something that makes it a lot more affordable.
Mr. McClelland promises to write a new piece in ‘Medium’ each week discussing another IoT topic in nontechnical terms. People can also send him requests. If it is a short question you can tweet him at #askIoT.
Blow out – AI
I am just going to blow a few things out here rather than keep them to the end. One of the biggest rewards I have stumbled upon (one being the app ‘Stumbleupon’) are the online sites: Medium, Telecrunch, and Futurism. How Futurism manages to put out so many editions out that have so much content is way beyond me. I plan to put out a version every week and it always stretches to a month. Imagine if I did this for a living I would starve! What brought that to mind is an excellent ezine I have been reading. I am struggling to think of its name. It is Daily Kos, yes, but more than that (yes I am now aware that ‘Daily’ is a ‘Politico Magazine’ owned piece.) But I was reading this other piece and I hope someone will send me the answer because I don’t remember it.
“Futurism” what a fantastic ezine. Great graphics, excellent topics, presented in a punchy format. I just love it. So for this bullet round we will look at “Scientists Just Found Half of the Missing Matter in Our Universe; Google’s Internet -Beaming Balloons will soon be floating over Puerto Rico; Tesla’s Elon Musk will be donating his batteries in Puerto Rico.”Researchers Find “Executioner Protein” That Causes Cancer Cells to Self Destruct without hurting healthy cells”.
You know and even I know that we are missing half of all matter, in the Milky Way – in the spaces between actual objects. The matter is known to be there but we just can’t see it. Two teams of astronomers one team French and one team English determined that the missing matter can actually be found in the filaments of hot, diffuse gas linking galaxies. When leftover light from the Big Bang passes through a hot gas it can be captured. A map of this effect was produced by the Planck Satellite. Each group was able to find definitive evidence that the gas between galaxies was dense enough to form filaments.
Futurism Dan Galeon October 9th, 2017
PROJECT LOON TO THE RESCUE:
Google has obtained temporary licenses from the FCC (thru April 2018) to deploy 2 helium balloons for the purpose of beaming emergency LTE internet over the islands of Puerto Rico and the U.S. Virgin Islands. The balloons float at 65,000 feet and send 160 GB of data. They cover an area about the size of Sweden and the data is comparable to receive around 30 million WhatsApp messages or 2 million emails.
This is not the first time Google has deployed its Project Loon, helium LTE Coverage providers in the wake of a disaster. The balloons have worked in Peru, France, Brazil, New Zealand, Indonesia and Sri Lanka.
Futurism Karia Lant October 8th, 2017
EXECUTIONER PROTEIN CAUSES CANCER CELLS TO SELF -DESTRUCT WITHOUT HURTING HEALTHY CELLS
Albert Einstein College of Medicine scientists have induced cancer cells to commit suicide with a new compound that leaves healthy cells untouched.
These scientists deployed their novel approach against acute myeloid leukemia (AML)cells (this cancer kills more than 10,000 Americans and makes up about 1/3 of all new cases of leukemia each year). The new compound fights cancer by triggering apoptosis: a natural process the body uses to get rid of malfunctioning and unwanted cells. Some other existing cancer treatments induce apoptosis indirectly by damaging the DNA in cancer cells.
The ‘executioner’ protein is BAX. This process seems like a ‘eureka’ moment to me but let’s look deeper.
In 2008, Dr. Gavathiotis was part of a team that first described BAX’s activation site’s shape and structure. Since that time (almost 10 years) he has been searching for small molecules to activate BAX and produce sufficient activity to overpower the natural resistance cancer cells mount to apoptosis. Pronounced: ( a-pəp-ˈtō-ˌsēz,).
His team screened more than one million compounds and narrowed the field to 500, many of them synthesized by the team, and then evaluated them. The technical jargon follows but hopefully I distilled it close enough to be correct. I just have trouble imagining spending 10 years in the pursuit of something you think works but you have to prove it first. Ten years. How many dollars? How do you fight for dollars for projects like this?
Futurism Karia Lant October 9, 2017
Creating Hydrogen Fuel from Water
Hydrogen fuel has been difficult and cost-intensive to produce, along with being extremely toxic to the environment).
Enter the University of Central Florida (UCF).
Current political machinations aside fossil fuels are on the way out. UCF researcher and assistant professor Yang Yang has developed a breakthrough hybrid nanomaterial that uses the power of an existing green source, solar energy, to turn seawater into hydrogen fuel.
Another overnight miracle that was ten years in the making. Scientists have been working for years to split solar hydrogen.
The current state of hydrogen fuel is well known. It almost doubles the fuel economy of traditional gasoline and but is also considerably more expensive to process.
In addition, there is no infrastructure to distribute the fuel. The current process also uses natural gas which is nonrenewable. Hopefully, politicians will not muck up the likelihood that, due to Hurricane Irma, Florida will be able to use the plentiful seawater and federal funds to bolster the new economy with this new research. Imagine having to replace gas stations with gas stations. We need to be looking at replacing gas stations with hydrogen stations.
Mercedes Benz unveiled a production-ready SUV at the Frankfurt Auto Show in September 2017. Toyota and Honda are also moving fast in getting this new hydrogen fuel to market. Next year will be another fascinating one. Electric vehicles were just able to gain a foothold and already they are being replaced with cheaper fuel alternatives.
Futurism Chelsea Gold October 5th, 2017
FUTURISM – A LOOK FORWARD BACKWARDLY
Remember when the US built the first C5 Galaxy supercargo lifter? Remember US’s first man in space? Remember the first moon launch? Let’s reminisce for a moment, for just a moment though because China is handing us our lunch. The Chinese are building solid fuel rocket launchers. The Chinese have positioned freighters (as in ships) along the Equator. Why? To launch rockets! Cheaper, less fuel used, more smarter. They read everything we did and everything Russia did and are doing it bigger, faster, cheaper. Russian cosmonauts and American astronauts in the Space Station. Now Russia and China are swimming together. We don’t have the will or the resources or the smart enough politicians to move us forward. China is going to spring ahead while we fall back.The solid fuel rockets are being developed by The China Academy of Launch Vehicle Technology (CALVT). They have a military transport capable of carrying the Long March 11 rocket which weighs 120,000 pounds. ONE HUNDRED AND TWENTY THOUSAND POUNDS? How big is the airplane? The Y20 has a max payload of 132,000 lbs. The rocket is merely 120,000 pounds. But never fear, the CALVT is working on a bigger rocket.
Greater payloads, less fuel being used. They can increase the frequency of flights and thus improve the learning curve.
Futurism Kyree Leary October 4th, 2017
WHO IS SMARTER GOOGLE AI or A FIRST GRADER?
Google’s Artificial Intelligence is outperforming Apple’s Siri. (Say it ain’t so Joe). Google’s AI is rated as having an IQ of 47.28. A six-year-old child has an IQ averaging around 55.5. An average 18-year-old averages 97. China’s search engine Baidu had a score of 32.92, Microsoft’s Bing measured 31.98 and Siri scored 23.94 – less than half of Google’s AI. But looking backwardly, in 2014 Google’s DeepMind rated 26.5, Microsoft’s had a 13.5. This means that in two years both have increased significantly. So, are we going to fall on the sword of AI? That is the prediction by Elon Musk regarding AI. Still too early to tell. Applications are now developing imagination and a sense of surroundings.
In fact, all the biggest
, Google’s CEO Sundar Pichai, Microsoft’s CEO Satya Nadella have both shifted resources to speed up development. Because both know that Amazon came out with 6 new models of Alexa a few months ago and now they have to catch up. While smartphones are ever increasing in their intelligence, I would watch for an ever stronger force developing with the artificially intelligent secretary and soon the artificially intelligent baby. Won’t mother’s just love that. She will have to be what? SUPER MOM! No doubt.
We didn’t even talk about how the movies of tomorrow will watch you; how Google’s new in-ear earbuds can translate 40 languages instantly,
IBM achieves a breakthrough: Deep Learning on Steriods
Preparing for the Transition to Applied Artificial Intelligence
Jobs for Americans: A Lesson from Germany
Artificial Intelligence in Self-Driving Cars
IBM’S Watson at the US Open: Tennis for Robots?
“Stop Pretending You Know What Artifificial Intelligence Is and Read This:
China: Robots and Intelligence
Machine Learning Drives Trucking Job Loss
Machine Learning drives Self-Driving truck preparations and could cause “Big Time” Job Loss for Drivers.
Artificial Intelligence has put the self-driving technology into the fast lane. Machine Learning will prevent thousands if traffic accidents each year. It will also save millions of gallons of fuel each year. The savings from keeping self-driving trucks running at consistent speeds will be tremendous.
Commuters will save countless hours of driving each day. Some say that drive times that are now over 2 hours will be delighted.
It will cost approximately 15,000 Americans their jobs. This is an addition to the millions of jobs lost in the last decade. Autonomous vehicles are a tremendous opportunity but will cause a big-time workforce issue. Eliminating economic hardships that disrupt the least number of people is essential. The big question: how do we make sure we’re planning far enough ahead. These disruptions can also create job opportunities for people. This remains a pertinent question that requires an answer.
These $300 Yoga Pants by Machine Learning
Billie Whitehouse is famous for pushing boundaries. Her first product blending fashion and technology: NadiX yoga pants. The pants have five sensors sewn in to help the wearer improve form for 30 different yoga poses. Once in a pose, the sensors vibrate in specific ways to tell you how to adjust your hips, knees or ankles. For the downward dog pose, for instance, the pulses guide a person to ground the ankle and lift the knee. The sensors highlight those micro muscles that you didn’t even know existed.
The idea seemed impossible to execute. Put electronics into garments still so new and so difficult? This was an engineer’s nightmare. The pants have removable, rechargeable batteries that last up to 90 minutes. The battery connects via Bluetooth to a smartphone app. People then choose the level of yoga they’re going to be practicing. Myth turned reality don’t you think?
IBM Achieved a Deep Learning Breakthrough
IBM engineers have developed Artificial Intelligence software that is faster. This makes the entire machine learning process faster and easier. Complex deep learning models on a single server will not be an issue. IBM managed to scale up distributed deep learning. Instead of taking days for a deep learning network to process models, it could now take only hours or even less. Wait time with deep learning training from days or hours to minutes or seconds. This also enables improved accuracy. Some individuals think that these Artificial Intelligence models are an achievement. Others think they seem too good to be true.
Preparing for the Transition to Applied Artificial Intelligence
Machine Learning gains more footholds in applications every day. It has become a topic that many engineers want to master. Machine Learning solutions require more than training an arbitrary model on your data. It requires an understanding of the type of data you have. How and what biases your data contains. The statistical models need understanding. Is the model applicable to your particular dataset? The success of this model requires knowledge of the metrics to optimize your model’s output. Certain skills required before transitioning to Applied Artificial Intelligence include:
Statistics: understanding Machine Learning, requires solid knowledge of statistics fundamentals.
Concepts of Machine Learning Theory: is an understanding of the range of how different loss functions work. An understanding of why backpropagation is useful, and what a computational graph is.
Data wrangling is important for Applied Artificial Intelligence. The success of the model correlates with the quality and quantity of your data. The old saying: GARBAGE IN – GARBAGE OUT is true. Especially with the amounts of data and the speed of this software churns through it.
Debugging/Tuning models requires that a solid knowledge of the fundamentals is essential. The right architecture and parameters require solid theoretical fundamentals. Good infrastructure work is necessary to be able to test different configurations.
Software Engineering is in the mix. Applied Machine Learning will allow you to leverage Software Engineering skills. Sometimes this requires a little twist. Mastery of these concepts and skills is Artificial Intelligence.
Jobs for Americans: A Lesson from Germany
Germany is one of the world’s leading models of workforce development efforts. Apprenticeship models that combine on the job paid experience and classroom learning. This equips the students and sets them up to compete for jobs out of school. The apprenticeship programs are responsible for this. The unemployment rate for German youth is one of the lowest in any of the world’s advanced economies. Compare the rate of 6.5 percent as of January 2017. The estimate is 11.5 percent in the U.S. The U.S. has seen a sudden increase in its own apprenticeship programs. These programs are working to prepare students for careers in middle-skill jobs. German apprenticeship continues as a model for employment growth in the United States. Support in public and private sectors for apprenticeship efforts will contribute to economic growth in the U.S.
Artificial Intelligence in SELF-DRIVING CARS
Saturday night rideshare doesn’t sound like fun. An ad appears touting a new restaurant over on the other side of town- free ride!
Why pay when you can get it for free?
Self-driving cars to restaurants, bars, pizza joints. Owners will be happy to provide the rides!
It might even be an answer to the dropping sales because people don’t want to go outside especially in winter.
What is going to happen to the Infrastructure? Cabs and public transportation will no doubt feel the impact.
Costs will be so low that businesses will provide rides right to their door. Car dealerships – buy a car? Why?
Hod Lipson is the author of “Driverless, Intelligent Cars and the Road Ahead”. He is also an engineering professor at Columbia University. He predicts that innovation will bring an explosion of growth.
IBM’S WATSON brings Cognitive Highlights to Tech at the US Open
IBM launches Watson Media, a suite of solutions powered by Artificial Intelligence. Watson has the ability to analyze images, video, and language at the US Open.
Cognitive Highlights To recognize important match moments
Slam Tracker Keeps up with the scores, stats and other insights
IBM Cloud uses years of Slam Tracker Data’s MACHINE LEARNING to understand player’s styles.
Elizabeth O’Brien is IBM Program Director of Sports and Entertainment Partnerships. Watson is at the center of a massive data analysis during the tournament. The idea is to take Watson’s capabilities to improve the fan experience. A way for the tournament to earn revenue is also a plus.
She explained that “If you are sitting there, there are 17 courts of play going on. Every point on each of the 17 courts is a potential highlight. So, if you’re a broadcaster and you have a highlight, you’re looking at thousands of potential highlights. Watson can look at them ‘These are the potential highlights’. Watson is suggesting the potential solution that you are looking for!
It is debuting at the Open this year but Watson Media has been around for some time. Wimbledon and the Master’s golf tournament have been venues for Watson also.
Within the app is also a high-powered chatbot that IBM calls the ‘Cognitive Concierge’. The Artificial Intelligent chatbot uses natural language. It processes questions about food or drinks that someone might have during a match. Last year Watson answered 56,000 questions. This year on the pre-opening day it fielded 4,000 questions and on the first day answered 8,000. Questions are: where is a particular player is playing. Where to get tickets and what parts of the venue tickets give attendees access to are also questions.
Ms. O’brien said that IBM is watching the questions that are being asked and learning what people want to know. This is increasing the body of knowledge and the questions Watson can answer.
Watson generates revenue for the USTA. Watson is building engagement with tennis fans around the world via the USTA app.
Heineken brings highlights to Twitter. Mercedes-Benz and American Express are also sponsoring content through the Concierge.
London was the most popular city source for visitors with 39 percent. Montreal (31 percent), San Jose (26 percent) and Tokyo (4 percent) follow. The numbers by country: the US was the most popular followed by UK, Canada, Germany, Italy, and Australia.
The Open has 700,000 fans go thru the event over the course of two weeks. Lew Sherr, the USTA’s chief revenue officer said that compares to a “Knick’s season, a Jet’s season. It’s an NHL, NBA season packed in two weeks”. Watson’s universe is hundreds of millions of interactions with fans.
Roger Federer scores a point at Arthur Ashe Stadium and Watson recognizes that its a highlight and alerts the USTA. The USTA then blasts video out to fans via USTA’s social medium feeds. Executives from IBM and USTA say that Watson allows them to review highlights faster. The highlights then get to the fans faster. USTA fans have a ‘sense of what is happening point by point”.
IBM has been teaching Watson that, a fist to the face of Roger with a bent elbow, means a celebratory moment. It cross-references this data with the roars of the crowd. Add in statistical analysis and Watson determines that this is one of the best moments of the match. Watson auto generates highlights which simplify the work of the video production crew. It process and sets up the highlight-reel creation fo USTA. Noah Syken, who is IBM VP of Sports and Entertainment Partnerships. He says that so much action is being played that even the fastest video team has trouble keeping pace. There are 22 courts; 4 ‘show’ courts, 13 field courts and 5 practice courts. Watson is ‘watching’ the games in the same way that it ‘reads’ X-rays and MRIs scans for doctors. (http://businessinsider.com/ibms-watson-wants-to-read-medical-scans-2015-8).
This is the first year that USTA is able to create experiences that will drive fan engagement. Watson is generating a “Highlight of the Day” and posts it on USTA’s Facebook page. Video highlights, player bio pages will appear at the IBM Watson Experience on the US Open Plaza.
IBM has ambitions to for the technology to grow over time. It is a will a tool for broadcasters or a tool to help develop player skills during training. Slam Tracker is the official scoring app for the US Open. It provides real-time scores, statistics, and point-by-point analysis. It also looks data about player and ball position. In January USTA opened a 64 acre, $63 million training facility in Orlando. The goal is to help in developing future American grown tennis champions.
Contributor Author Marty Swant (www.adweek.com/contributor/swant/). He is a technology staff writer for Adweek. He specializes in digital marketing trends and social platforms. He also specializes in ad tech and virtual reality and artificial intelligence. Jen Booten is a senior writer at Sporttechie. She covers the many ways that technology is disrupting sports. (http://www.sporttechie.com/author/jen-booton/)Other sources for information are:
“Stop Pretending you know what ArtificiaI is and read this instead”
“You have probably heard the news: AI is going to take your job. Wait, No, It’s going to create a new job for you. AI is going to kill us all! Wait, AI is totally smarter than us at, like, all smart things. But that probably doesn’t matter? Neural Networks. Machine Learning. Deep Learning. OMG. HELP!”
What are we talking about? We may not be talking, arguing, thinking about the same things! Nah, that NEVER happens. Let’s check in with someone that KNOWS!
Harvard Professor Leslie Valiant to the rescue: “You have a right to be confused.”
The terms Artificial Intelligence and Machine Learning are being misused in the popular press. Trevor Darrell is a leading researcher at UC Berkley. He is a part of the DARPA-funded artificial intelligence research project of emerging technologies for use by the military.
You are right. Professor Valiant continues: “There is no precise distinction-they overlap.”
“Artificial intelligence,” he says, “is the general name for a field of study-the study of whatever answer to the question might be.” HUH? WHAT? I thought we were going to be deconfused?
OK. “Answer the question: “what are the requirements for artificial intelligence?”
“AI is more like a goal than a thing.” Technically speaking it isn’t an ‘it’ at all. Think of a big box. In the box, we put foggy AI and lots of ‘things’ like – machine learning, deep learning, neural networks. Now these ‘things’ have something to chew on, some edges surrounding them. They are a precise name for various scientific, mathematical and engineering methods. These are methods that people use the fields of AI.
The phrase “artificial intelligence” sounds straight and above board. This phrase that clouds the issue of precision in discussing science. Elon Musk, the guy from SpaceX who is landing first stage rockets back on a platform in the ocean and reusing them. The CEO of Tesla Ince; the co-chair of Open AI; the CEO of Neuralink. The founder co-founder and chairman of Solar City. The co-founder of Zip2; the founder of X.com which merged with Confinity and later took the name PayPal. Yes HIM. He’s the guy that calls AI “the demon”. Who claims that “AI”, not a nuclear bomb, not white separatists and KKK “is what we should fear most.” It falls somewhere between ‘smart as a puppy’ and some subset of a cockroaches’ brain. (Stephen Hawkings agrees with the premise – more on that later.)
“George Orwell proclaimed, “the slovenliness of our language makes it easier for us to have foolish thoughts.” Hmm, going to the scientists didn’t help much did it? Google CEO Sandi Pichai (he is smart, watched his TED talk the other day) and Elon Musk maker of ‘a self-driving car’ and space vehicles are famous businessmen (Elon just sold 145,000 self-driving semi-trailer trucks to UPS!). Elon makes machines capable of speech. He is cornering the market on ‘things to fear (his words) that are going to take our jobs away. Doesn’t help much, does it? Elon says that we have more to fear from AI than anything else.
We should avoid using ‘artificial’ and ‘intelligence’ together. We have to go back to the beginning of computer lingo and ask Alan Touring. Yes, the guy who defined what a computer is. He thought that defining’ intelligence’ was too hard. He favored describing it by “intelligence is as intelligence does.” Does that help?
Invent more ‘things’ made with machine learning, deep learning and, neural networks. Then we can point to one ‘thing’ and say ‘smartphone’. See what I’m saying? The ‘thing’ defines’ itself. No other words are necessary. Everyone knows what a smartphone is. Right? (A little aside here: Sundar Pichai of Google is really impressed with a neural network. That is what powers Google’s ‘Assistant’ on your smartphone. You can use the ‘Assistant’ even on an iPhone as long as you are using Google Chrome. Anyway, I wish you would have been able to use it to be your Christmas presents! Half the time. Half the money. Half the running around. Seriously. It knows sooo much.)
People in undeveloped countries use smartphones. Their use outpaces the use of other ‘intelligent’ things. In 2013 a median of 45% across 21 developing countries used the internet or owned a smartphone. In 2015 the number rose to 54% much of that in China, Brazil, and Malaysia.
By comparison, 8% of people in developed countries use the internet and smartphones. One of the biggest divides is between ‘Millenials’ 18-35 and those that are older. 76% of internet users in emerging countries use social networks. This compares with the US where more than 71% use smartphones! In Europe 65% across 6 European countries use smartphones. Ten years the iPhone didn’t exist!
PEW RESEARCH CENTER Source: Spring 2015 Global Attitudes survey Q71 & Q72
Author: John Pavlus, September 6, 2017. Titled So-So Semantics in Quartz (the guide to the new global economy for people excited by change. https://qz.com)
Editor: I can vouch for the absolute insanity in Quartz. A whole different way to communicate with someone/thing smarter than you – your smartphone. Not to be believed events occurring. Imagine editing your chromosomes – while they are still in your body! Check out Hugo too! Your very own AI bot to converse with. A great study buddy.
China: Robots and Intelligence
China is installing robots like crazy. Shipments of robots to the country rose 27% last year. At 90,000 it was more than any other nation. It is on track to account for one-third of the world’s total. The push for automation could depress wages for Chinese workers. It will exacerbate income inequality. It will hurt consumption. This shift will have worldwide ramifications economists warn. It will dent prospects for a more balanced global economy. American projected job loss 47%. EU 35 %. Pay attention folks!
Elon Musk, the Tesla Man automatically gave drivers of Tesla Model X and S vehicles ‘more power’. He gave away ‘free software-upgrades’ of car batteries to people struggling to survive the ‘summer of floods’. The same batteries that were lasting 60-kilowatt hours were now lasting 75-kilowatt hours. The increase in capacity was from 200 miles per charge to 242 miles per charge an increase of 17.3%. The upgrades were temporary. If you want to buy the upgrade, it is an ‘over the air’ installation of $2,000. You don’t even have to go to your dealer for the upgrade!
Artificial Intelligence recreated Super Mario Brothers by watching someone else play it. (Not confirmed at press time. ed.)
The wonders from Space! Since 1972, the Landsat series of satellites have provided high-resolution images of the earth’s surface. These images are used by business, government, scientists, and the military. This database provides the longest continuous record of the Earth’s continents as seen from space. The latest in the series is the Landsat Data Continuity Mission Spacecraft to be named Landsat 8 when it becomes operational.
The satellite is placed into a near-polar orbit, traveling north to south as it crosses the equator. At a speed of 4.7 miles per second (7.5 km/sec), each orbit takes nearly 99 minutes. Landsat completes just over 14 orbits per day. Landsat’s instruments cover the Earth’s surface from 81 degrees north to 81 degrees south every 16 days.
Image 1: Lake Eyre, South Australia
Image 2: Mississippi River with towns
Image 3: Phytoplankton, Gotland Island, Baltic Sea, Sweden
Image 4: Sandstorm how the sand particles appear from space
The timeline of Landsat Satellites.
Images from the current Landsat, Landsat 8
Date April 26/2018
Today I promised that I would repair an earlier post that somehow disappeared.
Not only did I reenter some of the lost material, I learned a how to use video. Yes, that’s right VIDEO!
If the rest of the world can learn to work with artificial intelligence and machine learning I can learn to add video to my blog posts.
In addition to that, I downgraded my plan to Personal and saved $251 a year (at least until I can find a way to monetize this fun that I’m having!).
So lean back and click the start switch. If you find any glitches please let me know. My bride and I are leaving our house of 43 years, where we raised our three sons and watched as their families grew. It is now the sunset of our lives, mine anyway. My legs and feet have been ravaged by diabetes and the 14 stairs to get up and down the stairs and those going into the basement (I haven’t been down there in what 3 years)?
It is time to turn the rose gardens and flower beds that I have built during the last 20 plus years over to a younger lad that can at least walk on the rough terrain of the grass. You didn’t know grass was that mean? Try neuropathy, the uneven ground makes itself known quickly.
It is a very sad end. I never contemplated leaving this house. And with 43 years of ‘stuff’! We only have 30 days to get it done!
The good news is that the good doctor gave me other need some cortisone and the bursae in both knees. I should be dancing in the streets by morning!
Please, lay back and I will shut up just as soon as I see that you comfortably ensconed in your favorite position.
High Energy Solar Flares affect the operation of orbiting satellites and can even pose a risk to astronauts on the International Space Station.
However, “CMEs Coronal Mass Ejections, huge eruptions that send clouds of solar plasma streaking through space at millions of miles per hour are the real danger. CMEs that hit earth can spawn intense geomagnetic storms,” and disrupt power grids, satellite navigations, and radio communications.
“In March 1989, a strong CME caused a blackout that left 6 million people in the Canadian province of Quebec without power for 9 hours!”
In 1859 a powerful slammed into Earth generating beautiful auroral displays as far south as the Caribbean. If a geomagnetic storm as strong as that one – known as a Carrington Event, were to hit today the damage could run as high as $600 billion to $2.6 trillon damage in the US alone!
The sun blasted out a coronal mass ejection (CME) along with a part of a solar filament, over a 3 hour period on Feb 24, 2015 Credit: Solar Dynamics Observatory NASA
“The U.S government is getting more serious about dealing with the dangers posed by powerful sun storms.”
On Thursday (October 29) the White House released two documents that lay out the new national plan for mitigating the negative effects of solar flares and other types of ‘space weather’.
The space weather can wreak havoc all over the technological earth wiping out communications centers, power grids, and even satellite navigation.
This new plan is called “National Space Weather Strategy”
I started watching this collection of Time Lapse Photography by the astronauts on the International Space Station. My wife brought me a full plate of her out of the world spaghetti and I couldn’t stop watching the panorama of space.
Well, the spaghetti is done but the film isn’t. But I still have at least one more post to repair.
We are moving from our traditional home of 43 years to a tiny teeny apartment. Two bedrooms so it isn’t like a studio but where do you put 43 of accumulation. I don’t even know where to start.
Thanks for stopping by.
I recommend subscribing to this time-lapse photography. Remember to ding the bell so that you will be notified when updates are posted.
This is the first blog post on this new website. This site is dedicated to those that have gone before; before with courage in the face of ridicule, before with insight no one else could see, before with the thirst to share their newfound knowledge to anyone that would listen.
“Education is all a matter of building bridges” Ralph Ellison ( know most widely for his novel “Invisible Man” 1952 Random House.
The world is exploding with changes in this year 2017. I remember reading an article a few years ago in 2010 maybe that we wouldn’t recognize computers by the year 2020 or even more so 2030 the whole environment will have changed. The journey that I began in February 2017 tiptoeing into a blog regarding an amazing article. It was written in the US Chamber of Commerce Foundation newsletter by Mark D’Alessio. He was quoted by Gus Lubin in Business Insider Magazine, http://www.businessinsider.com/jobs-that-are-disappearing-fastest-2016. Mr. Lubin lists the jobs that will be lost because of technological advancement.
The top ten are:
Bookkeeping, accounting, and auditing clerks
Cooks, fast food workers
Postal service mail carriers
Executive secretaries and executive administrative assistants
Farmworkers and laborers, crop, nursery, and greenhouse
Sewing machine operators
Postal service mail sorters, processors, and processing machine operators
Cutting, punching, and press machine setters, operators, and tenders, metal and plastic
Switchboard operators, including answering service
“One thing we know for sure is technologies will continue to impact the workplace. This, in reality, means that workers need skills that are in demand and are transferable to a range of occupations. Workers need to manage their risk in the marketplace and continuously skilling up to the needs of the 21st-century economy. ”
I read an article a week or so ago (which incidentally led to the development of this website) that 10 million jobs had been lost in the last 10 years! Every week now there are articles, commentaries, pundits that know the outcome of all this Artificial Intelligence. What has deep learning to do with self-driving cars? How can I feel, taste, touch Machine Learning? We are only beginning to see the ramifications of all of our technological advancement. But this is old news. The new news:
TOTAL SOLAR ECLIPSE COMING! AUGUST 21, 2017!!!
This an excerpt from Space.com
“Three months from today (May 21) a shadow of darkness will travel across the United States in the middle of the day. The portion of the country that falls under this shadow will experience a total solar eclipse, an incredible phenomenon that occurs when the moon completely covers the disk of the sun. Here are just a few of the things you’ll need to know as you count down to this rare experience:
On Aug 21, 2017, the total solar eclipse will be visible in a 70-mile-wide band stretching from Oregon to South Carolina. The region where the moon completely covers the sun – called the path of totality” – will pass through Idaho, Wyoming, Nebraska, Kansas, Missouri, Illinois, Kentucky, Tennessee, Georgia, North Carolina and South Carolina. Observers in the U.S. (including in Alaska and Hawaii) positioned outside of this band will be able to see a partial solar eclipse. The partial eclipse will also be visible from the rest of North America, Central America and part of South America.”
The reason I published so far in advance was so that you – YOU – would be able to run out and get one of these books: (from Amazon of course)
“Eclipse – Journey to the Dark Side” by Frank Close (I JUST HAVE to interject. This is the second time in my life that I have run into this title. It is a play by Howard Richardson and William Berney titled ‘Dark of the Moon’. It was produced on Broadway in 1945. It went on to much acclaim in college and high school drama productions – where I first ran into it; and an album by Pink Floyd “Dark Side of the Moon” Harvest Records March 1, 1973, Abbey Road Studios (well so what if it has four extra syllables!). From the 1945 Broadway Play “Ballad of Barbara Allen”
A witch boy from the mountain came, A – pinin’ to be human, Fer he had seen the fairest gal…A gal named Barbara Allen. Anyway, a 1953 revival added 3 more verses.
The reason that I published this blog so far in advance of the website being published, was so that you could run to your tablet and order 2 Kids books for the momentous occasion:
“Looking Up! The Science of Stargazing” (Simon Spotlight 2017) by Joe Rao and Illustrated by Mark Borgions
“Solar Science: Exploring Sunspots, Seasons, Eclipses and More” (NTSA Press, 2015) by Dennis Schafz and Andrew Fraknoi
and the kids can buy for you:
“Totality: The Great American Eclipses of 2017 and 2024” (Oxford Press, 2017) by Mark Littman and Fred Espenak
“See the Great American Eclipses” (Great American Eclipses LLC, 2016) by Michael Zeiler
“Your Guide to the 2017 Total Solar Eclipse” (Springer, 2016) by Michael Bakich
“An American Eclipse: A Nation’s Epic Race to Catch the Shadow of the Moon and Win the Glory of the World” (Liverlight 2017) by David Baron
“Sun Moon Earth: The History of Solar Eclipses from Omens to Doom to Einstein and Exoplanets” (Basic Books, 2016) by Tyler Nordgren
And how could I get by without a Facebook Post (printed below) AND a plug for Amazon! Hopefully, I will get this site published soon so that I can sell you these Fabulous Amazon books from that Fabulous Amazon library from my personal website as an Amazon Affiliate (see the disclosure below).
Two additional tidbits: I noticed somewhere a blurb about some comparison of the 1973 eclipse vs the one that is coming. It was regarding anti-matter and no it was as the New York Time reporter quipped “the antimatter cooked the burgers on the grill” or (something close to that).
“There’s something remarkable about a single snapshot of the Earth – an intact view of our planet in its entirety, hanging in space,” the astronaut Scott Kelly observed in an essay on Medium (www.medium.com). The challenge of getting far enough away to get the Earth into a single frame and the matter of lighting. “In order to view the Earth as a fully illuminated globe, a person (or camera) must be situated in front of it, with the sun directly at his or her back. Not surprisingly, it can difficult to arrange that shot while traveling approaching thousands of miles per hour”.
This website: Deep Education Web: Artificial Intelligence, Deep Learning, Machine Learning, Neurol Networks, Tensor et al. will be coming to a neighborhood near you – hopefully by the end of June 2017.
Always an enticing vision causing man to look beyond, beyond the ground, beyond the sky into the New Horizons that have kept calling since the beginning of time.
As a young man with friends, we would set off in September (the nights were getting cold and so kept the mosquitoes at bay), sitting by a warm fire after a long day of paddling in the Boundary Waters, sipping a muscle warming brandy and water staring at the stars. Oh so brilliant, no city lights to dim their glory, to be transported to the land of imagination. What if? I wonder when? Who would have thought? How often?