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?
A lot of new things in the email today, and a few from recent revelations.
Robots can’t jump like Fleas. Why?
“A New Mathematical Model may help explain why we can’t create (yet) a robot that jumps like a flea” From Neurosciencenews.com April 28, 2018 Source: Duke University
An ant in “a zero-to-60 matchup, the fastest dragster would have little chance”. The ant can reach speeds of more than 140 mph in less than a millisecond to nab its prey.
A hydra is a soft-bodied aquatic creature. It defends itself using the capsules that are located on its tentacles that act like pressurized balloons.
“When trigger they fire a barrage of microscopic spears that briefly accelerate 100 times faster than a bullet.”
Can this new model help scientists create robots that mimic the jaw-dropping characteristics found in nature?
Scientists can look to insects and aquatic life to copy how creatures strike, jump, chomp, and punch.
These creatures or organisms don’t do these things using muscles but rather “spring loaded parts they can cock and release like an archer’s bow”, said Sheila Patek, associate professor of biology at Duke University.
This mini robot was inspired by the anatomy and jumping mechanism of a flea.
“The model allows researchers to test different settings of spring, latch, and motor or muscle parameters to determine the speed, acceleration, and other aspects of performance.
Let’s Tangle with some Atoms
Today on singularityhub.com “Scientists Discover How to Harness the Power of Quantum Spookiness by Entangling Clouds of Atoms.” Robert Young April 27, 2018
Einstein quipped that entanglement’s “spooky at a distance” – one particle in an “entangled pair” affects its twin instantaneously – no matter how far away.
Famously bizarre, these are real effects “that have been seen in laboratories over and over.”
Three European research groups have just managed to entangle not just a pair of these particles, but separate clouds of thousands of atoms- that they can harness.
My today’s lesson in quantum mechanics: “When particles are entangled they share properties in a way that make them dependent on each other, even when they are separated by long distances.
Experiments have shown these properties“exceptionally useful”. A particle in one location can spin and its pair will then spin also (teleportation).
They can also help store a huge amount of information in a given volume (super dense coding).
Another advantage of entanglement is that computers can be linked in different parts of the globe.
In addition to helping to make quantum computing (quantum internet) possible, secure communications (see my post at this link regarding Quantum Computing).
Any attempt to interfere (hack) into a quantum system immediately disrupts the entanglement making it obvious that a message has been tampered with.
They have crafted a system using a satellite to transmit data. If a computer nerd tried to hack into the transmission the transmission is immediately destroyed. Quantum theory states that with Quantum Key Distribution (QKD) a quantum photon cannot be copied perfectly and will leave a trace if disturbed. I have read that if such a ‘hack’ occurs the transmission will be destroyed (although the original document will not be disturbed).
Quantum mechanics is frontier that has been studied and researched since Max Planck and Albert Einstein began the theories that came to make up quantum mechanics, quantum physics, and many other observations to explain what Classical Physics cannot.
Quantum mechanics has led to the race to build the first commercially viable quantum computer (see my post at deepeducationweb.com). IBM has built one that can operate for 90 microseconds due to the extreme heat that it generates.
The operating temperature for the quantum computer has to be as it is in deep space.
So far we have touched on entangling atoms for data storage, how a pair can react the same way without constraints on distance of separation, quantum secure communications.
Canadian researchers at the University of Waterloo are designing systems to replace the Arctic radar system that exists today.
They are designing the system to use “quantum illumination” using entangled photons.
Have we seen these events before? Maybe in Star Trek? Gene Roddenberry is becoming more astute every day.
of tiny and IMMENSE
At its IBM Think 2018 conference, IBM unveiled inventions and technologies such as AI, Blockchain, and Quantum Computing.
It smallest computer is 1mm x 1mm which is smaller than a grain of fancy salt and costs less than ten cents to manufacture. This information is courtesy of “The Verge”, March 19, 2018, in an article by Paul Miller @futurepaul
As published on singularityhub.com “A Data Storage Revolution? DNA Can Store New Limitless Data in Almost Zero Space” by Peter H. Diamandis, MD April 26, 2018.
Our voracious appetite for “MORE” is creating a problem of immense proportions.
Immense problems breed IMMENSE COSTS and IMMENSE PROFITS! Last year, $20 billion was spent on new data centers in the US ALONE!
Where to store all of this stuff?
On January 31, 2018, in a report out of Redmond WA, Satya Nadella, CEO of Microsoft stated: “this quarter’s results (Dec 2017) speak to the differentiated value we are delivering to customers across our productivity solutions and as the hybrid cloud provider of choice.”
Yesterday Amazon reported quarterly profits triple of what analysts predicted. Sales reached $51 billion “which is a 43% increase over last year’s first quarter results.” Net Income for the quarter was $1.6 BILLION. These massive increases are attributed to retail business and cloud computing services.
Five days ago Alphabet announced profits increased 84% with a quarterly profit of $9.4 billion.
In this post on The Guardian, the huge increase is attributed to the “clicks and views” of Google ads on its search engine, YouTube etc.
By the end of the decade, projections for 2020 are the addition of 5 BILLION new minds to join the web.
“Memory grade silicon is rarely found pure in nature and researchers predict it will run out by 2040!”
DNA though can theoretically store 215 million gigabytes of data in a single gram of DNA!
I am sorry but this is another of those super technical lessons that would just get mangled under my explanation so I direct you to this link to study at your leisure.
I am safe in predicting that even with its potential for profit and the knowledge it will solve the data storage problem this process will take time.
Moore’s Law, the observation by the co-founder of Fairchild Semiconductor and INTEL, Gordon Moore.
He postulated that the use of integrated circuits doubles about every two years and that chip performance (David House an executive at Intel) would double every 18 months.
While this prediction has proven accurate for decades the upper limits of the law (an observation not actually a law) are rapidly approaching. Most recently, in 2015 Mr. Moore stated, “I see Moore’s law dying in the next decade or so.” This is the reason for the aggressive push for quantum computers.
So the push is on: quantum computing and computers, increase in storage processes to enable the growth of computing, and increases in security, driven by quantum mechanics.
Soon to arrive on the scene is the storage space required by the exponential growth of computing users and computing devices – DNA, dexyribonucleic acid.
opened his annual letter “Founders’ Letter” published on Friday, April 27, 2018, by quoting Charles Dicken’s A Tale of Two Cities “It was the best of times, it was the worst of times.”
As one of the co-founders of Google in 1998, Mr. Brin remarked how computing power has exploded. At the time things like AI, neural networks were “just a forgotten footnote in computer science”.
While in awe of the monthly leaps in developing computer applications he adds “such powerful tools also bring with them new questions and responsibilities.”
While Google has harnessed computers to translate photographic images, translate 100 languages and power navigation systems in automobiles, diagnose disease and discover new planetary systems it strives to be socially conscious and aware of its responsibilities as a corporate citizen.
Google’s development of applications with the US Military has angered many of its employees who have openly protested this segment of its business and demand the withdrawal of Google’s support for these applications even though they are not offensive in nature.
While heralding the “new spring of artificial intelligence” as the most significant developments he cautions of the “technological renaissance” and the danger artificial intelligence can cause if it is not used with the most humble precautions.
I wrote the original post (Below) and posted it on April 1st. I later found an article dated March 28, 2018, on the site “Tech Insider”.
While this tidbit is only a very small slice of the future it speaks to the partisan divide in this country (I am working on a post regarding that topic for dabblerduckbutts.com).
It also speaks to the information that I found that I portray as a ‘war’ that has only just begun (below). Back in the day of VHS and Betamax, of CDs and DVDs when, after the initial battles for supremacy, different vendors were able to come together and eventually do what was right for the consumer.
That appears to be not the case today and going for into the realm of ‘new’ technology. As things stand now, Apple, Google, Amazon each have their own services for TV and video. Apple’s won’t work with Google’s devices, Amazon’s won’t work with Apple’s or Google’s (except that Amazon Prime will now work with Apple TV (as of December 2017).
Each tech giant knows that whoever captures the most initial customers will no doubt keep them going into the future. If you owned Apple TV and speakers why would you buy additional speakers from Google when they won’t work with the ones that you currently own?
The future does look bleak indeed if there will not be any interoperability of devices. Hopefully, there will be more Rokus. It will play any product from any of the vendors. The result? It has a more market share than any of the others!
Will the others learn from this?
This is the second part of a post on how business is responding to the new technology of machine learning, where the new technology will lead, and which business will be the big winner of this next transformation.
In part one we looked at the profound changes coming among them that 47% of jobs will be lost. We looked at how machine learning is going to be the staple of business until Quantum Computers are online.
We looked at a Harvard Business School study “The Digital Business Divide – Analyzing the operating impact of digital transformation” that compared margins, earnings before taxes, and profits for businesses that have adopted digital technologies, the digital leaders to the digital laggards that already may be shut out of the biggest rewards.
We examined David Pring-Mills interviews with Dr. Kai-Fu-Lee a Taiwanese venture capitalist and Mr. Erik Cambria. Both men seemed to have a dark view of companies and vendors that claim to be purveyors of Artificial Intelligence.
I hijacked part of a booklet by PricewaterhouseCoopers which is a thorough examination of the types of artificial intelligence: assisted, augmented, and autonomous. I highly recommend this booklet “Bot.me: A revolutionary partnership – How AI is pushing man and machine closer together. Consumer Intelligence Series.”
I closed with a short piece regarding The New York Times. The Times editors have relaunched “At War” in March 2018. It is a blog written by Vets for Vets. In addition to having more credibility since the posts are written by combat veterans, the blog also launched the journalism careers of several of its contributors.
The Next Great Thing
So what does the future hold? New opportunities will abound. With 47% of jobs lost in the US alone (35% in the UK and 50% in Japan), technological tinkerers will come up with something right? Universal Basic Income will give some relief but the game and pressure to come up with the NGT (Next Great Thing) will be played by thousands if not millions.
Surely, The Singularity will be the incubator for the NGT. Surely, Quantum Computing will lend itself to the discovery of the NGT. Remember these games are already controlled by the Big Six, plus IBM and MedTech companies.
I sure can paint a bleak future for those people just itching to be the next Bill Gates, Paul Allen, Larry Page, Jeff Besos. But I never was good at predicting when a really new and unique device would appear that I just had to have it let alone predict who would have thought up the device.
I will leave the NGT up to the future to decide. The future can be fickle though. Remember when email was a thing of the past? Google is now promoting AMP email as web pages so that all of the fancy footwork that websites can do email will be able to do also. Ah well. We will have to wait for history to tell the tale.
Grab Hold of the Future
Are you casting about to gain knowledge and skills of the future? Are you tired of searching through volumes of literature to find ‘the one’? That one kernel that propels you into your future?
You may want to check out Enterprise.nxt by Hewlett Packard Enterprises. The list of topics includes: “Artificial Intelligence makes flash storage predictive”; Expert Guide to Running Hybrid IT”; The Ethics of AI: Tool, Partner or Master?”; “What Senior Tech Execs wish they learned earlier in their careers”; “5 Surefire cloud security certifications to boost your career”.
Bringing them Together – last post and this one
Artificial Intelligence and Machine Learning will revolutionize business and marketing more than television, the internet, and mobile have done.
Companies will need a lot of data to use machine learning to streamline its processes, unlock user insights and engage users in new ways. Consumers provide the data to drive these categories. Massive amounts of data are generated because consumers are using multiple devices, across multiple platforms.
85% of executives believe that AI will allow their companies to obtain or sustain competitive advantage. (The Boston Consulting Group “Is your Business Ready for Artificial Intelligence?” September 2017)
In fact, a study indicates that one-third of the time spent in the workplace involves collecting and processing data. (McKinsey & Company, “Where Machines Could Replace Humans-and Where They Can’t (Yet)” July 2016)
Machine learning can analyze millions of data points, and with the software can make smart decisions optimized for an individual business. This will free time so managers can focus on strategic tasks.
A business can determine its objectives, define and quality its audience and then let the software and the data from machine learning figure out how and where to engage the prospects.
A business used to define a core demographics as men aged 35 to 54.
Machine learning will take into account what you want to accomplish with that demographic such as a sale of a product.
But you have to do your homework. You can’t be a laggard so you will have already parsed your metrics such as who are the people that are your most valuable customers. Once you know those characteristics you can have the software look for millions of signals to find people who match the same profiles you have identified.
An example is Trivago.
The online travel company wanted to drive transactions from high-quality users that already used it app. Using Google-powered Univeral App campaigns, machine learning focused on optimizing the use of the app for these specific customers.
The company saw a 20% increase in high-quality user purchases. Machine learning can also determine the most effective ways to engage your high-value users. Think of being able to match the right user, to the right message, to the right creative and at the right time.
Google’s own experience of the right combination of the right message of the right creative at the right time at the right audience resulted in a 50% higher lifetime value for people using YouTube.
The capabilities of machine learning will be critical to personalizing user experiences and thus improve responses.
The caveats will be: First the company will need millions of data points (more on that later). Then it will need the right metrics on what it wants to accomplish (no sloppy thinking allowed). Then it will need to continuously optimize the customer journey (no one-off shots will work).
It is easy to say. I used to tell waitresses and managers that I worked with that all they had to do was show up and do their job. No longer. Machine learning will enable managers to quantify what is driving each buying decision.
Who is Going to Divide Up the Spoils
(Peter Burrows Laptop Magazine March 2018 MIT Review March 22, 2018)
The First Skirmishes
For the past three years, a battle has been raging. This battle is just the first volley of the first skirmish of a war to end all wars.
It is probable that the winner of this war will amass riches beyond the wildest imagination and will reign as king for decades to come.
This war is being fought for control of the future. Machine learning is the key. Each warrior is adept at producing algorithms to capture the results of machine learning.
But machine learning begins at the beginning. Whoever has the most data has the best chance of winning. Machine learning chomps thru data like the original PacMan games.
This skirmish has pitted Amazon, Google, and Microsoft at the edge of technology. Like standing on the edge of a starship looking over the expanse of blackness who is going to capture the plums.
Recent skirmishes have involved facial recognition and language translation. Each company is getting good enough in each category but the first plum is still to come. Who can turn the knowledge learned in creating these awesome skills into creating the AI based platforms that will be used to power the new generation?
“Machine learning is where the relational database was in the early 1990’s: everyone knew it would be useful for essentially every company, but very few companies had the ability to take advantage of it”. This quote is from Swami Sivasubramanian, the head of Amazon’s AI division.
Amazon, Google, Microsoft and let’s not forget Tencent, Alibaba and Baidu (we must assume they are playing this war game mustn’t we?), have massive computing resources and armies of talent required to build an AI utility. They all must win this war. To not win is to lose.
“Ultimately, the cloud is how most companies are going to make use of AI-and how technology suppliers are going to make money off of it”, says Nick McQuire and analyst with CSS Insight.
“AI could double the size of the $260 billion cloud market in the coming years”, adds Rajen Sheth, senior director of product management in Google’s Cloud AI unit.
Data is KING KEY
The first part of the key to everything is data. The nature of machine learning is that the more data a system has, the better the decisions it will make.
The second part of the key is that customers are more likely to get locked into an initial vendor and stay put. What company would be foolish enough to spend bundles of money on data and the developments that arise from machine learning only to ditch it in favor of another? Start over? Not very likely I think.
I think the lessons of the rise of computers were well learned. Who gets there first wins! Internet browser, office programs, enterprise software. These companies have been on a battlefield similar to this one before.
Arun Sundararajan studies digital technologies and how they affect the economy at NYU’s Stern School of Business. He states that “the prize will be to become the operating system of the next era of tech”.
Puneet Shivam, president of Avendus Capital US, an investment bank says: “The leaders of the AI Cloud will become the most powerful companies in history”.
Enterprise software companies such as Oracle, Salesforce, and SAP are already embedding machine learning into their apps. Think then of the thousands of AI wannabes that are in hot pursuit! Pitched warfare is on the horizon.
We see that Amazon, Google, and Microsoft (don’t forget Alibaba, Tencent, and Baidu) all offer services in facial recognition, in turning speech into text and vice versa for building the natural-language processing that allows Alexa, Siri, Cortana, and other digital assistants to understand your queries.
I receive online job requests from companies such as APPEN Global and WhatUsersDo. These companies hire independent contractors to perform basic interpersonal communication tasks.
These tasks can be recording voice dialog such as instructions a person would use to direct Siri to do some task. Another task is conversing with another person by reading scripts that would be used to write software for the personal assistants. Each task requires a specified number of submissions which, I assume, is to assure that enough data points are obtained to ensure accurate algorithms can be written.
How did Microsoft build its empire? Build the platform and build the apps to run on the platform. Apple did it with iOS and mobile apps in its era.
Each company runs the same plays to make machine learning accessible to total AI novices. Amazon unveiled SageMaker which could be used to build machine-learning apps to be not much more complicated than building a website.
A few weeks later Google introduced CloudAutoML. A company can feed its own unique collection of data into CloudAutoML and this tool will generate a machine-learning mode capable of improving the business.
Google states that more than 13,000 companies have asked to try CloudAutoML.
How many organizations in the world could benefit from machine learning? Maybe the real question is how many can hire the people with the necessary background and skills to make it work?
Jeff Dean, head of Google Brain says that “to get even 10 million companies to use machine learning, we have to make this stuff much easier to use”.
Microsoft has been doing breakthrough work on AI such as computer vision and natural-language processing for two decades. It has massive amounts of data for use by its Azure cloud including content from Bing, LinkedIn, Skype and the billion people that use Microsoft Office.
Sounds awesome. Google is the R&D guru of AI. It led the way to computers that can beat humans at their own games. It led the way to self-driving cars. It has its own line of chips to run its machine-learning infrastructure.
Thanks to Google Search it probably has access to more data than any other company. According to Alexander Wang, the 20-year-old founder of AI startup Scale, they are in the best position to monetize data and they have the best machine-learning researchers in the world”.
But Amazon is no slouch. A few years ago it burst onto the scene by demonstrating that almost half of its business was from AWS (Amazon Web Service). Watch for more from Mr. Bezos.
Microsoft’s commitment to offering deep and focused training before people left the military service led to a training apprenticeship and training program for military personnel at Joint Base Lewis-McChord which is located just 30 minutes south of Microsoft’s corporate headquarters in Redmond, Washington.
The idea was to train these people in skills that were in short supply in the technology industry.
Technical training would be augmented with mentoring from people already in the private sector. The bold name for the pilot program? The Microsoft Software & Systems Academy!
The first class had only 22 service members. It soon became apparent that this training filled a need to help service people transition to civilian careers.
Frank Shaw raised his hand and volunteered to create a new Military Affairs team at Microsoft and be responsible for the future of the program.
On March 21st, 2018 the 14th MSSa location at Camp Lejeune North Carolina began. Each of the almost 1,000 graduates of the course has a story to tell. But the real storyline of Frank’s story is that this program has 280 hiring partners with more coming online all the time. These partners create opportunities for veterans in the technology industry.
To become a hiring partner or get involved, visit military.microsoft.com/mssa
Combat team carry a team member on a stretcher.
Thanks for stopping by.
In the first part of this post, I promoted the last Blue Moon of 2018. I am going to update how that looked at various parts around the world. Paschal Blue Moon March 31, 2018
These three images of the Blue Moon, March 31, 2018, also known as the Paschal Moon.The images are from Space.com. I must apologize I lost my notes on the photographers. I know that the moon above the Navesink Twin Lights lighthouse in Highlands, New Jersey. Astrophotographer Steve Scanlon captured this image.
The image in the second row is of the Blue Moon in 2015 captured by Chris Jankowki of Erie Pennsylvania.
The one on the second row right is a jet flying thru the face of the Blue Moon March 31, 2018.
I will continue to scour my notes to find the photographers of the two images so that they get the credit they deserve. So far my Google searches have led nowhere and Space.com is not displaying the page that I hijacked these images from. Embarrassing and again, I apologize for not naming the photographers.
The next Blue Moon appears in October 2020. This year we were treated to a rare phenomenon two Blue Moons in a calendar year. The last time it occurred was in 1999. The next occurrence will be in 2037!
So that you have enough images to tide you over until then a last, impressive image captured by Frank Langben of San Jose CA.
This post ran over 4,000 words so I thought I should break it up. The second part will be posted shortly after the first.
In this post:
> Veterans Interest (at the end)
> Email of the future
> Digital Transformation of Business
> What Do You Mean by AI
Remember the rumors of the last year or so “Email is Dead”? Not so fast! Google has announced AMP for Gmail. Accelerated Mobile Pages will be available through the Gmail Developer Preview. Theoretically, “this new spec will be a powerful way for developers to create more engaging, interactive, and actionable email experiences.” (Google sell sheet). Vijith Assar in Select/All lands with both feet on the announcement. He says it is not needed and if effect, will slow Gmail down. He is not impressed on several fronts. I will leave to all of you to sort out. I am sticking with plain old Gmail that I have used since the dawn of time.
Does it Pay for Business to Spend on the New Technology?
Tim Berners-Lee said (recognize the name? He is the inventor of the World Wide Web) “The future is so much bigger than the past.”
The economies of the world are undergoing deep, deep transformation. Digital technology is changing everything from strategies to processes to marketing. The changes are profound and everlasting. Nothing will be the same. Indeed 47% of jobs in the US will be lost. In the UK the loss will be around 35%. The projection for Japan is up to 50% by 2035.
A point to remember is that jobs will be created. A factor not discussed my in the US is that 48% of people in the US think Universal Basic Income is a good idea!
Finland has put a pilot project into action and Canada and France are working out the details
But that is off-topic for this post. However, as regular readers are aware I strongly encourage people to get more education. What concerns me is the 70% of workers realize that jobs will be affected just not their jobs. Why? Only 30% of people are improving their education to prepare themselves for the coming onslaught.
In my last post on The Singularity and Quantum Computing, I said changes are going to be astronomical especially when quantum computing begins to be used.
Machine Learning will lead the way
In this post, we will examine how machine learning will lead the way until the day comes when quantum computers are available.
A co-founder of Intel, Gordon Moore forecast in 1995 that computing power would double every ten years and cost would decrease at the rate and pace.
We have come to the end of that road. The big question of this post concerns what has occurred in those companies that have aggressively transformed themselves using technology and those that are not so aggressive.
A paper by Marco Iansiti and Karim Lakhani of the Harvard Business School explores what more than a decade of research shows regarding the movers and those that are still thinking about moving to new technologies.
Their empirical observations show what a major opportunity awaits those companies investing in digitizing their business models.
The division of movers and not movers becomes a look at the ‘digital leaders’ and the ‘digital laggards’. Companies, specifically Google, Amazon, and Microsoft are using their expertise in cloud computing and machine learning to develop applications for their platforms so any business can use applications on their platforms to take advantage of the newest tech and transform themselves from laggards to leaders.
Again I got ahead of myself. Drs. Iansiti and Lakhani and associates at the Harvard Business School found the difference in average gross margin for 25% of companies that came to be labeled leaders and laggards.
The three-year-average gross margin for digital laggards was 37% and for digital leaders was 55%! Need I continue?
OK. The three-year-average earnings before taxes were 11% for the laggards and 16% for the leaders. Finally, to really whet your whistle the three-year-average of Net Income was 7% compared to 11%!
Their studies also showed that the digital advantage was not simply in spending more money, “the best-performing companies stated they have technology budgets ON PAR with the digital laggards. So there is more going on than what shows in the first batch of numbers. The same 25% of laggards spent 3.2% of their revenue on IT while the leaders spent 3.5%.
In digital companies, digital leaders approached the digital opportunity with a different mindset. Perhaps the way these companies executed in their operations would have given them a similar advantage even if they hadn’t seized the digital opportunity? I don’t know. But it would not appear to be so.
The main difference which may speak to my question is the digital leaders have consistent up-to-date metrics for decision making and can make the best use of the data they collect.
Managers make decisions. What is changing, dramatically, is the best managers are taking advantage of the new technologies to plan and execute faster and more efficiently.
Many, many years ago I was given the task of installing, training and supporting computerized cash registers in the restaurants I supervised. The question asked by upper management, “Is it worth it?” My answer was the computers would make the good managers better and that the not as good managers would waste the opportunity. Forty years later the same question is being asked.
Another issue is the new products that are coming to market. The new products themselves are taking advantage of the new technologies in ways the laggards will never be able to capture.
I recently read an article that said the newest equipment entering field service today have built-in sensors to report on the performance of the device, any health issue that may be occurring, and what/when preventative maintenance tasks need to be performed. Manager’s time can now be spent planning and executing strategies rather than tracking what machine is due for its next checkup. That sounds more profitable.
Data now being collected aids not only the user of the device but the manufacturer as well.
How to better meet customer’s needs, last longer, run more efficiently to save even more resources. All these are happening NOW!
Companies that are laggards are probably going to be laggards forever, at least until they succumb to the early death of laggards. Not getting with the ‘program’ soon enough.
I remember a project. It seemed like it took years to finish. I had to develop a Bill of Materials for a company I worked for. That was progressive back then but now that company is still mired in old inventory and old sales methods. The progressive attempt at achieving real cost knowledge and cost savings (profits) which would have accrued.
I see that happening so often as I visit businesses that I have supported for years. I do not know what is keeping them from modernizing but surely their days of existence are numbered and death is approaching ever faster.
These companies have great people working for them. I wonder if the employees know the disservice the owners and managers are doing to their careers.
Example of Digital Transformation and a Swift Kick
An example of digital transformation is that Amazon’s website changes every three seconds!
If you are a business owner or if you know one that can benefit from a swift kick to get motivated, please read this Harvard Business Study.
You will be richly rewarded if you heed the opportunities it presents. It is well researched, well written and presents solid opportunities for getting on with the digital lifestyle.
The Same Old Communication Problem – Apples to Oranges
Does AI mean the Same as AI?
“In 2017, artificial intelligence attracted $12 billion of Venture Capital investment. We are only beginning to discover the usefulness of AI applications.” by David Pring-Mill 3/15/2018
David Pring-Mill quotes Dr. Kai-Fu Lee, a Taiwanese venture capitalist and the founding president of Google China “it’s tempting for every entrepreneur to package his company as an AI company, and it’s tempting for every VC to say “I’m an AI investor”.
But Dr. Lee concludes that 2018 will be the year where many of the fakers will be exposed.
David Pring-Mill found an expert in the field of natural language processing, Erik Cambria, who said: “Nobody is doing AI today and everybody is saying that they do AI because it’s a cool and sexy buzzword.”
Mr. Cambria said that much of ‘AI’ is just emulation of human intelligence. “And there is nothing today that is even barely as intelligent as the most stupid human being on Earth!” “No one is doing AI yet, for the simple fact that we don’t know how the human brain works.”
Mr. Cambria continues “Companies are just looking at tricks to create a behavior that looks like intelligence but that is not real intelligence, it’s just a mirror of intelligence.”
I think respectable companies look at scientific integrity regarding the issue of accurate definitions and it is not a matter to be taken lightly. I am afraid though that hype is currently the currency of choice regarding Artificial Intelligence.
The lions of this Fourth Industrial Revolution: Mark Zuckerberg, Elon Musk, Bill Gates, Vernon Vinge, Ray Kurzweil, Ben Goertzel, Paul Allen, Hartmut Neven, Larry Page disagree among themselves as to what constitutes AI; where will AI lead us; will AI be benevolent or malicious?
So many people of hyper vision, of massive intelligence, of uncommon bravery to speak their minds openly to generate the questions and answers that are essential to the proper growth of AI is exciting to see.
Richard Feynman, during a commencement address at Cal Tech in 1974, said: “The first Principle (of AI) is that you must not fool yourself-and you are the easiest person to fool”. Later he added, “You should not fool the layman when you are talking as a scientist. Scientists should bend over backward to show how they could be wrong.”
I recommend the booklet I listed below. It is an extremely thorough look at the world using the lens of Artificial Intelligence. So many graphs, so many groups of topics just so many of everything in an easy to read and understand format.
I hijacked the following text from the PwC (PricewaterhouseCoopers) booklet
“AI, shorthand for artificial intelligence, defines technologies emerging today that can understand, learn, and then act based on the information. Forms of AI in use today include digital assistants, chatbots, and machine learning.
Today, AI works in three ways:
Assisted intelligence, widely available today, improves what people and organziations are already doing. A simple example, prevalent in cars today, is the GPS navigation program that offers direction to drivers and adjusts to road conditions.
Augmented intelligence, emerging today, enables people and organizations to do things they couldn’t otherwise do. For example, the combination of programs that organize cars ride-sharing services enables businesses that could otherwise not exist.
Autonomous intelligence, being developed for the future, establishes machines that act on their own. An example of this will be self-driving vehicles when they come into widespread use.
With a market projected to reach $70 billion by 2020, AI is poised to have a transformative effect on consumer, enterprise, and government markets and around the world.
There are certainly obstacles to overcome, but consumers believe AI has the potential to assist in medical breakthroughs, democratize costly services, elevate poor customer service, and even free up an overburdened workforce.
“Some tech optimists believe AI could create a world where human abilities are amplified as machines help mankind process, analyze, and evaluate the abundance of data that is created in today’s world, allowing humans the spend more time engaged in high-level thinking, creativity, and decision-making.”
I also recommend the article: “Everyone is talking About AI But do they mean the same thing?” by David Pring-Lee.
Mr. Pring-Lee introduces so many topics and attributes so many statements you will find it easier to read the article and take your own notes rather than relying on my version of “Cliff Notes”.
Today’s Blue Moon is the last until 2020. It is also known as the Paschal Moon- for Easter!
Veterans Crisis Line: 800.273.8255 Press 1.
I am maintaining my promise to provide information to veterans regarding information I would have covered in my blog “Lodestarandyou.com” before I melded it into dabblerduckbutts.com.
Paul Szoldra is a US Marine. He describes the history (short and personal) of US Military blogs and how they gained recognition as real spaces for the military member could tell his or her story. “At War” as it came of age in Afghanistan and Iraq Wars, as told by C.J.Chivers, a Marine Corps veteran, and Pulitzer Prize-winning reporter for the New York Times. He tells of Teresa Fazio who offered a deeply personal account of a “mortuary affair in Iraq” and Thomas Gibbons-Neff who is now a Pentagon correspondent for The Times. Other writers got their start at Task & Purpose, War on the Rocks and Strategy Bridge.
These stories, written by combat veterans bring a level of credibility that other journalists don’t have.
The Times has relaunched its “renegade” ‘At War’ blog in March 2018. Its new editor Lauren Katzenberg “hopes that At War will inspire more people to share their voices and stories at a time when there is less transparency around wars being carried out in American’s name”. Paul Szoldra March 2018.
I ask your forbearance in getting this post out to you so late. I was in the hospital three times (almost three weeks since January 1st) and in rehab for two weeks all since the first of January.
First, my diabetes attacked my legs in what I can only describe as hellish. I have read that it can take up to two years to heal! Then one of the grafts that were hooked up during a quadruple bypass 17 years ago had to have a stent inserted. So now I am back to my old self, just as ornery as ever.
So we saddle up our keyboards and begin anew.
I have been researching two topics simultaneously, The Singularity for this post and Populism for my dabberduckbutts.com blog. I honestly cannot say which scares me more. In the short term, the populist and nativism have bent in this country and many others around the world are doing the most damage I think. The groundswell of its noise is becoming deafening mostly due to the antics of its chief proponent Trump. Yes, I will get to that topic before long.
The Singularity caught my eye last year. I don’t know how or where I came across the article regarding the Singularity Hub.
His best-known concept is Artilect War. “He predicts that a sizable proportion of humanity will not accept being cyborged and will not permit the risk of human extinction at the hands of advanced cyborgs and artilects.”
Professor de Garis is the author of two books “The Artilect War: Cosmists vs Terrans: A Bitter Controversy Concerning Whether Humanity Should Build Godlike Massively Intelligent Machines” and the other “Multis and Monos: What the Multicultured Can Teach the Monoclultutered Towards the Creation for a Global State.”
The thought that just crossed my mind regarding two battles currently being waged in rage by those for populism and nativism vs those that oppose those forces in the US and around the world.
Before going any further we should define the ideas espoused by the proponents of The Singularity.
Vernor Vinge, in a paper for a symposium by NASA Lewis Research Center and the Ohio Aerospace Institute, categorically states that “within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended.”
This pronouncement is by a retired professor of mathematics and computer science who is also a science fiction writer. His thinking appears in his paper “The Coming Technological Singularity: How to Survive in the Post-Human Era.” Professor Vinge states the acceleration of technological progress has been a central feature of this century. He argues that we are on the edge of change comparable to the rise of human life on earth. This change will be wrought by “entities” with greater human intelligence.
He postulates if we are able to answer the question: if artificial intelligence (AI) can create the human equivalent in a machine in the affirmative “yes, we can” so then there is little doubt that beings more intelligent can be constructed shortly thereafter.”
The Singularity then is the point of no return, technology will overtake humanness.
Another well-known futurist, Ray Kurzweil, is Google’s Director of Engineering. He claims an 86% accuracy rate relating to his 147 predictions since the 1990s. He predicts that “2029 is the consistent date I have predicted for when an AI will pass a valid Turing test and therefore achieve human levels of intelligence.”
He continues “I have set 2045 for the ‘Singularity’ which is when we will multiply our effective intelligence a billion-fold by merging with the intelligence we have created.”
Mr. Kurzweil is not alone in his prediction. He is joined by Softbank CEO Masayoshi Son who predicts this will happen by 2047. Kurzweil believes that process has already begun.
On his site: http://www.kurzweilai.net/, he also discusses Universal Basic Income, the end to human disease, the future of human longevity and so on. It is a clearinghouse for other fascinating articles and predictions.
Mr. Kurzweil proposes his ‘Law of Accelerating Returns’. He believes some of the incredibly fast revelations of the power and might of AI such as Machine Learning, Deep Learning, Neural Networks and so on have already crashed into our psyche.
Additional notable references to The Singularity are made by Peter Rejcek in an article “Can Futurists Predict the Year of The Singularity” March 31, 2017, posted at http://www.singularityhub.com.
He notes that many futurists are restless while waiting for The Singularity to occur. They see it as a positive event to free us mere mortals so we can dedicate ourselves and our intellect to more high brow tasks than merely working, eating, living as humans.
Even Elon Musk, of the Space X rocket and driverless AI-powered semi-trailer trucks fame, has a strong interest in The Singularity.
Mr. Musk has a company, Open AI, that is dedicated to developing artificial general intelligence (AGI) to ensure the development of AGI is beneficial to humanity. AGI is another term for human-level intelligence.
Another futurist is Ben Goertzel, chief scientist at financial prediction company ‘Aidyia Holdings’ and robotics company ‘Hanson Robotics’. Hanson is an advisor to Singularity University.
Hanson Robotics has built the most advanced robot to date (March 2017). Sophia is her name. She is a media darling starring on The Tonight Show with Jimmy Fallon. Her press coverage has a potential to reach over ten billion readers. Breathtaking! She even has her own website.
Dr. Hanson believes that three main characteristics have to be developed in intelligent machines namely creativity, empathy and compassion. He believes that genius machines can evolve to solve the world’s problems that seem to be insurmountable problems to humans.
So we have divergent views of what ‘The Singularity’ will bring. Will it be creative and compassionate as Dr. Hanson wishes? Will it be benevolent per Elon Musk? Will it have the level of human intelligence of Ray Kurzweil or will it be foreboding as Dr. de Garis envisions?
Just maybe The Singularity will not occur by 2045 as Paul Allen, co-founder of Microsoft asserts. His article “The Singularity Isn’t Near” appeared in the MIT Technology Review.
One of Mr. Allen’s assertations for predicting that the 2045 expected date will fail is that he believes that there will not be enough computing power by 2045. He also believes that software complex enough to calculate the components of the human brain will not be available by then either. This article was written in 2011 but seems as current today as it was then – until last month.
However, enormous progress has been made in quantum computing. This progress has just exploded in the last month or two.
Albert Einstein had trouble with Quantum Computing. “The Nobel Prize Winning physicist declared that the thinking behind quantum mechanics was fundamentally flawed. Scientists have since proved the theory repeatedly and conclusively.” Jack Nicas October 16, 2017, How Google’s Quantum Computer Changed the World in the Wall Street Journal.
In his article, Jack Nicas interviewed Hartmut Neven, the German computer scientist that led the Google Glasses project. Jack tried to use a “Cliff Notes” version of the theory of quantum mechanics and I must confess even the simplified version is way over my head. I think I need a really ‘dumbed down’ version.
My simple explanation, and it may not be correct since it misses so much ‘meat’ is a single atom can be in two locations at the same time. This, of course, leads to speculation of objects existing in multiple dimensions, or parallel universes.
In practical terms, I made mention in a recent post ( “Slamma Jamma” published on January 29, 2018.) of the Chinese developing the perfectly secure system for transmitting documents using quantum mechanics. Per quantum mechanics, rules state once a bit (the “secret key”) has engaged any attempt to ‘hack’ into the record will destroy it.
It would seem that is a pretty secure way to keep something. If someone tries to look in, boom, it vanishes.
The experiment that demonstrated this successfully was between China and Austria. It has led to the thinking of the ‘quantum internet”.
Just last month Intel joined Google and IBM in the race to build the first practical quantum computer by announcing a new 49 qubit neuromorphic chip designed
for computing research. Intel made the announcement at the Consumer Electronics Show in Las Vegas in January 2018.
In an oversimplified explanation of how quantum computers work: regular semiconductors represent information as a series of 1s and 0s. The unit of computing in a quantum computer is a qubit. Qubits can compute as both a 1 and a 0 simultaneously. Two qubits can represent the sequence 1-0, 1-1,0-1,0-0 at the same moment in time. A quantum computer with as little as 50 qubits can pack more computing power than the most powerful supercomputers.
The basis of computing power is found in Moore’s Law. It dictates that computing power per unit would double every 18 months while the price per unit would drop by half.
However, the point has now been reached where the amount of money needed to squeeze out improvements is greater than in the past.
Quantum computing is a way to move past that.
In November 2017 IBM announced it had built a quantum machine that uses 50 qubits. This is a major breakthrough because it represents the critical barrier where quantum computers are believed to accelerate past traditional supercomputers.
A major issue with quantum computing is displayed in the IBM machine. It can only maintain the quantum computing state for 90 microseconds at a time. These machines must be supercooled to work and a separate set of calculations must be run to correct errors in the original calculations.
Google’s quantum computer is racing to achieve “quantum supremacy” in 2019. The test needed to pass to achieve this prize is an obscure computational problem that would take a classic computer a billion years to complete.
Success means that this computer will achieve something that even a few years ago would have been thought to be impossible. This computer will mark the end of the ‘classical age’ of computing.
Hand in hand, the end of the classical age in computing and the beginning of the age of machine intelligence will mark extreme changes. The next few years will mark advancements in human knowledge that have taken the time since man-made cave paintings to achieve. When accomplished, the very next few minutes of time will eclipse that sum of knowledge.
Veering off Course
Another Googler, Google co-founder Larry Page has a flying taxi service. It is cleared for takeoff in New Zealand. This all-electric vertical take-off and landing machine has taken flight.
Seemingly a cross between the Delorean of “Back to the Future” meets the hovercraft of “The Jetsons”, Cora is on the move. The comparison is presented in an article by Sherisse Pham of CNN Tech March 13, 2018.
“Cora” the vehicle takes off like a helicopter and transitions to a plane. Cora is self-piloting, can fly at 93 miles per hour and can travel 62 miles. Fred Reid of the company Kitty Hawk which has its operations in New Zealand boasts of a “pollution-free, emission-free vehicle that flies independently.”
Uber and Airbus are also racing to commercialize flying taxis.
Meanwhile, in China, a company ‘Ehang’ released a video of passengers climbing aboard its autonomous drone and taking off with the push of a button.
This still is taken from a video of a Ehang drone taxi carrying a passenger.
Ehang boasts at least 40 successful journeys. It wasn’t until January 2018 that it shared footage of the flights.Video of Ehang 184.
It would appear that America’s first entry into the market, Boeing, has some catching up to do.
The Singularity, that potential “paradise” where humans won’t have to work. Quantum computing where all the intransigent problems of the world can now be solved by computers. Both of these ‘futures’ are still developing in the wings.
In the present, wings are being flown by a Chinese company Ehang and a New Zealand company Kitty Hawk.
These two companies are really the ‘disruptors’ today. They are showing the rest of the world the possibilities that can be realized now.
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”
Well, it’s a new morning. I am in a hospital room waiting for breakfast to be delivered. This hospital stay has really wrecked 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!
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 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.
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
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 awhile. 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 keep the grocery store’s runnng are going to be left behind by the Fourth Industrial Revolution just like the coal miners of West Virginia?
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
be gipped of the finale since dawn will ruin the show.
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.
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?
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!
150 years ago, January 1918 from Scientific American
“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.”
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 to 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 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.)