"Slamma Jamma"

Salad section of Amazon Go image recode
The future of retail grocery. Amazon Go Salad Section IMAGE RECODE
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The Future of Retail Amazon Go Image Recode
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The Future of Retail Amazon Go Image Recode
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The Future of Retail Amazon Go Image Recode
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The Future of Retail Amazon Go Image Recode
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The Future of Retail Amazon Go Image Recode

Date January 17, 2018

Good Morning

As predicted, this year is gonna to a full court press from one end to the other. I thought the title of a basketball movie would be appropriate. The whistle just blew, so let’s get  our “Slamma Jamma”

diaggram of full court press Google Images
Diagram of a Full Court Press.

 Ball Inbound

Well, it’s a new morning. I am in a hospital room waiting for breakfast to be delivered. This hospital stay has really wreaked havoc with my blog posts. I have mounds of research for this blog – but it’s at home. In addition, I have written a blog on others subjects but in my blog “minecrjm.blogspot.com“.

Before I continue I must raise the alarm on a few items. Normally I would post them at ‘ minecrjm.blogspot.com but I don’t anticipate posting there for a few days.

1) Jeff Sessions wants to keep out immigrants that are illiterate. I sure wish that rule applied to his forefathers

2) Trump is 6’ 3″ tall. Except that he is not. His previous health records list him at 6’2”. If that is true his weight at this physical would list him as obese. True to form: lie rather than fix

3) His henchmen are doctoring federal reports that list terrorist activities. They are changing ‘homegrown activities to make them appear as if they were from foreign countries they want to keep people out. Almost all terrorist actives in the US have been from homegrown terrorists.

4) Another sign this country is tilting to fear of Trump’s white supremacist henchmen: Psychologists called off a public discussion on the “The Dangerous Case of Donald Trump”: Reason? The henchmen were making dangerous threats.

5) Not only did two United States Senators lie about the racist vulgar words from Trump, but the newly minted Secretary of Homeland Security joined the chorus during her confirmation hearing. How do we trust these liars? How do other counties? Each other? This is all going to crumble into a pile of smashed breadcrumbs. Croutons anyone?

Money Transfers = Russia

6) Future News: Watch for it! Mueller has found many suspicious money transfers between Russia banks and US entries. Example: former Russian Ambassador to the US was paid $120,000 10 days before the election; a $150,000 transfer was thwarted by bank employees 5 days after the election. KEEP FOLLOWING THE MONEY!

Carry On

It is morning and I am in my room at Ecumen, a rehab facility. In order to go home, I have to be able to climb 12 stairs. I have 12 stairs at home. I have to prove that I can perform the necessary tasks at home. However, after 5 days in a hospital bed, my muscles really have lost a great deal of strength. I agreed with the hospital therapist that I should spend a few days at a rehab center before attempting a full-blown home challenge.

Deep Education Web

Back to my post.

I am going to experiment with shorter posts using ‘bullet’ headlines. There is just so much going on and can’t give each topic the time it deserves but I want to make sure you have the most information possible.

New format?

Elon Musk had a fabulous 2017. His Tesla 3 production is still suffering but Space X proved the concept that reusable rockets do work. He also had a slammin’ opening to his driverless semi. UPS ordered 145 of them the day after his show. He also built a huge battery in Australia.

Another Prediction Coming True!

China is surpassing the US. It is ahead of us in trust among nations the US fell from first place in the first year of Trump. Surprised? Germany is now #1.

China has the most advanced quantum technology. It perfected the ability to encrypt and send useful signals over far greater distances than thought possible.

The current use of strings of numbers to transmit bank accounts info, secret databases etc. are brittle and easy to crack by skilled hackers.

Jian-Wei Pan a researcher at the University of Science and Technology of China States ” Historically, every advance in cryptography has been defeated by advances in cracking technology. Quantum key distribution ends this battle.”

Quantum keys, used for opening encrypted files, are encoded in the physical state of quantum particles. This means that they are protected not only by the limits of computers but the laws of physics.”

While we can encrypt transmissions between normal computers they cannot be copied or stolen. A rule of quantum mechanics states that an object can only be viewed once.  Autonomous Destruction!

Another prediction come true!

Asia under Trump: How the US is losing the region to China

Headline CNN  dated January 27, 2018

 

A Rare Event – see the blog for January 31, 2018

Super blue blood moon Google Images text overly MS Publisher
January 31, 2018. A rare event! Three moons! Blue Moon Blood Moon Lunar Eclipse

Just finished a post on the Super Blue Blood Moon on this blog. It is Sunday, January 28, 2018. I am finishing my stay in rehab on Wednesday, February 2 and returning to a crazy life.

Back to the Future

Now I can start back at the top. Catch me if you can😄 How many hundreds of thousands of people will come to Amazon Go over the next generation?

After a year’s delay, Amazon opened its convenience store to the public. WOW!

Clean. Dynamic. CONVENIENT. That is how I describe this brick and mortar venture from the world’s premier e-tailer. Scan your Amazon card on your way into the store. Specially designed cameras using artificial intelligence will charge the card (credit or debit) that you have on file with Amazon, as you pick up each item.

Congestion gone! People are doing the work of creating salads etc that you will take home. A deli on steroids. Machines will be doing the heavy lifting and thinking.

Now imagine this concept as your grocery store. You will have to wait for a while. Amazon will use this concept store to reconfigure the stores of Whole Foods Coop that Jeff Bezos purchased last year for $13 Billion. I imagine he has been chomping at the bit to get this going. I don’t know what the daily interest on $13 billion is but I will bet I couldn’t pay it. I expect these concepts to roll out to Whole Foods as fast as he can get them.

Next, they will come to a neighborhood near you. Imagine the money that this operation will save him! No cashiers. Soon robots doing most of the stocking! After all, that is what Amazon is famous for. His warehouses i,e, ‘fulfillment centers’ are staffed with robots that pick the orders.  Save labor costs.

Indeed, SAVE LABOR COSTS! As these stores roll out to his corporation and shortly to his competition what are all the cashiers going to do? Maybe they can be utilized in- store to make salads and whatever signature items are designed to be sold but how many single mother’s, widows, physically challenged people are going to be left out of a paycheck?

How many of the labor force that keeps the grocery store’s running are going to be left behind by the Fourth Industrial Revolution just like the coal miners of West Virginia?

to be continued

Thanks for stopping by.

Craig

 

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Supermoon Day January 31, 2018

Super blue blood moon Google Images text overly MS Publisher
January 31, 2018. A rare event! Three moons! Blue Moon Blood Moon Lunar Eclipse

In the early morning hours of January 31, 2018, you can witness a TRIFECTA of MOTHER NATURE! A Triple moon event. A BlueMoon. A Blood Moon and A Lunar Eclipse! All in one glorious spectacle – depending on the weather AND whether you can wake up!

Who, What, Where, When, Why, WOW!

The WOW applies if you took the same journalism class or curriculum that I did.

Wake up, especially if you live on the west coast.  Those living on the east coast will

The phases of the super Blue Blood Moon from The Guardian Staff
Phases of the Super Blue Blood Moon The Guardian
Coming to a neighborhood near you Google Images
Coming to a neighborhood near you
full phaes of Super Blue Blood Moon Google Images
Full Phases of Super Blue Blood Moon. Google Images

be gipped of the finale since dawn will ruin the show.

Lunar Eclipse from NASA with viewing times nasa image
NASA IMAGE Lunar Eclipse with times of moonset

Gordon Johnston program executive and lunar blogger at NASA Headquarters in Washington DC said if you live in the eastern part of the United States to “Set your alarm early look outside about 5.51 AM. The best time will be about 6.45 AM making sure to have a clear line of sight and look in the west-northwest direction, opposite from where the Asunción will rise”.

In the Central time zone action begins at  4.51 AM with the reddish shadow will appear at 6.15 AM CST,  The eclipse will be hard to see because the Sun is rising. The moon will set at 7.00 AM. Your best viewing will be a high place will a clear line of sight looking West.

The show will begin in the Rocky Mountain time zone at 4.48 MST. The peak of the blood moon eclipse is at 6.30 AM MST.

California and Western Canada will see the show start to finish. Have your seat in your spot by 3.48 PST. The eclipses will begin at 4.51 AM PST.

You can read Gordon Johnston’s blog at Moon.NASA,gov

The P’s and Q’s

1. The moon will be 14% brighter because it will be at its perigee when it is closest to the earth.

2. A  blue moon is so called when it is the second full moon in a month. This one is being stolen from February. No full moon this month. Sorry.

3. A blood moon refers to the color the moon takes on when it enters a total lunar eclipse. The moon moves entirely within the earth’s shadow. The sun, moon, and earth must be in alignment for this to occur.

Review: supermoon – the moon is at its closest to the earth; blue moon – two full moons in one month; blood moon – reddish color when the moon is in earth’s shadow; lunar eclipse – the moon is entirely within the shadow of the earth.

Test Question: When was the last time this triple whammy occurred?

Blood moon slipping behind some clouds Google Images
Blood moon slipping behind some clouds.

 

One hundred and fifty years ago!

On January 1st we had the Wolf Moon

On January 31st we will have a Super Blue Blood Moon

On March 1st we will a full Worm Moon

On March 31st we will have a full Pink Blue Moon

On April 29th we  will have a full Flower Moon

On May 29th we will have a full Strawberry Moon

On June 28 is a full Buck Moon

On July 27th is a full Sturgeon Moon

On August 26th is a full Corn Moon

On September 24th is a full Harvest Moon

On October 24 is a full Hunter’s Moon

On November 23 is a full Beaver Moon

On December 22 is a full Cold Moon

Enjoy these Spectacles of Space!

Craig

150 years ago, January 1918 from Scientific American

Auto Dreams

“It’s more or less true—no one really knows anything about the future. So here goes, for a try. The automobile of the future will be weather-tight. Probably it will be all glass—sides, front, rear, and roof. If a malleable glass is ever made, the frame may be dispensed with, but nobody has discovered malleable glass, to date! In the future, the car with the steering wheel will be as obsolete as the car with the hand pump for gas or oil is today! Driving will be done from a small control board, which can be held in the lap. It will be connected to the mechanism by a flexible electric cable. A small finger lever, not a wheel, will guide the car.”

 

Machine Learning – A Visit with Vijay

Dated January 2, 2018

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

FEAR ROBOTS

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.”Pindrop logo

“Our fraud prevention system is in a continuous evolution to keep catching new kinds of fraud activities over the voice channel.”

machine learning robot staring at code Google Images CCL
MACHINE LEARNING ROBOT STARING AT CODE GOOGLE IMAGES CCL

FEAR ROBOTS

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.

Ten million jobs have been lost to technology in the last decade 

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.

Ford Mustang Production line The Atlantic Reuters/Rebecca Cook
Ford Mustang production line. Count how many humans working on the line. The Atlantic, Reuter/Rebecca Cook

I have found so much more material that I am going to digest and file another post shortly after this one.

Thanks for Stopping By!

Craig