Portions of this post are taken from the January 2018 article written by John Lewis of “Vision Systems”.

I feel there is considerable confusion between Artificial Intelligence (AI), Machine Learning and Deep Learning.  Seemingly, we use these terms and phrases interchangeably and they certainly have different meanings.  Natural Learning is the intelligence displayed by humans and certain animals. Why don’t we do the numbers:

AI:

Artificial Intelligence refers to machines mimicking human cognitive functions such as problem solving or learning.  When a machine understands human speech or can compete with humans in a game of chess, AI applies.  There are several surprising opinions about AI as follows:

  • Sixty-one percent (61%) of people see artificial intelligence making the world a better place
  • Fifty-seven percent (57%) would prefer an AI doctor perform an eye exam
  • Fifty-five percent (55%) would trust an autonomous car. (I’m really not there as yet.)

The term artificial intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage.

Early AI research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names. This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.

While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, the current evolution of AI technologies isn’t that scary – or quite that smart. Instead, AI has evolved to provide many specific benefits in every industry.

MACHINE LEARNING:

Machine Learning is the current state-of-the-art application of AI and largely responsible for its recent rapid growth. Based upon the idea of giving machines access to data so that they can learn for themselves, machine learning has been enabled by the internet, and the associated rise in digital information being generated, stored and made available for analysis.

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level understanding. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

DEEP LEARNING:

Deep Learning concentrates on a subset of machine-learning techniques, with the term “deep” generally referring to the number of hidden layers in the deep neural network.  While conventional neural network may contain a few hidden layers, a deep network may have tens or hundreds of layers.  In deep learning, a computer model learns to perform classification tasks directly from text, sound or image data. In the case of images, deep learning requires substantial computing power and involves feeding large amounts of labeled data through a multi-layer neural network architecture to create a model that can classify the objects contained within the image.

CONCLUSIONS:

Brave new world we are living in.  Someone said that AI is definitely the future of computing power and eventually robotic systems that could possibly replace humans.  I just hope the programmers adhere to Dr. Isaac Asimov’s three laws:

 

  • The First Law of Robotics: A robot may not injure a human being or, through inaction, allow a human being to come to harm.

 

  • The Second Law of Robotics: A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law.

 

  • The Third Law of Robotics: A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

With those words, science-fiction author Isaac Asimov changed how the world saw robots. Where they had largely been Frankenstein-esque, metal monsters in the pulp magazines, Asimov saw the potential for robotics as more domestic: as a labor-saving device; the ultimate worker. In doing so, he continued a literary tradition of speculative tales: What happens when humanity remakes itself in its image?

As always, I welcome your comments.

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DARK NET

December 6, 2017


Most of the individuals who read my posting are very well-informed and know that Tim Berners-Lee “invented” the internet.  In my opinion, the Internet is a resounding technological improvement in communication.  It has been a game-changer in the truest since of the word.  I think there are legitimate uses which save tremendous time.  There are also illegitimate uses as we shall see.

A JPEG of Mr. Berners-Lee is shown below:

BIOGRAPHY:

In 1989, while working at CERN, the European Particle Physics Laboratory in Geneva, Switzerland, Tim Berners-Lee proposed a global hypertext project, to be known as the World Wide Web. Based on the earlier “Enquire” work, his efforts were designed to allow people to work together by combining their knowledge in a web of hypertext documents.  Sir Tim wrote the first World Wide Web server, “httpd“, and the first client, “WorldWideWeb” a what-you-see-is-what-you-get hypertext browser/editor which ran in the NeXTStep environment. This work began in October 1990.k   The program “WorldWideWeb” was first made available within CERN in December, and on the Internet at large in the summer of 1991.

Through 1991 and 1993, Tim continued working on the design of the Web, coordinating feedback from users across the Internet. His initial specifications of URIs, HTTP and HTML were refined and discussed in larger circles as the Web technology spread.

Tim Berners-Lee graduated from the Queen’s College at Oxford University, England, in 1976. While there he built his first computer with a soldering iron, TTL gates, an M6800 processor and an old television.

He spent two years with Plessey Telecommunications Ltd (Poole, Dorset, UK) a major UK Telecom equipment manufacturer, working on distributed transaction systems, message relays, and bar code technology.

In 1978 Tim left Plessey to join D.G Nash Ltd (Ferndown, Dorset, UK), where he wrote, among other things, typesetting software for intelligent printers and a multitasking operating system.

His year and one-half spent as an independent consultant included a six-month stint (Jun-Dec 1980) as consultant software engineer at CERN. While there, he wrote for his own private use his first program for storing information including using random associations. Named “Enquire” and never published, this program formed the conceptual basis for the future development of the World Wide Web.

From 1981 until 1984, Tim worked at John Poole’s Image Computer Systems Ltd, with technical design responsibility. Work here included real time control firmware, graphics and communications software, and a generic macro language. In 1984, he took up a fellowship at CERN, to work on distributed real-time systems for scientific data acquisition and system control. Among other things, he worked on FASTBUS system software and designed a heterogeneous remote procedure call system.

In 1994, Tim founded the World Wide Web Consortium at the Laboratory for Computer Science (LCS). This lab later merged with the Artificial Intelligence Lab in 2003 to become the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). Since that time he has served as the Director of the World Wide Web Consortium, a Web standards organization which develops interoperable technologies (specifications, guidelines, software, and tools) to lead the Web to its full potential. The Consortium has host sites located at MIT, at ERCIM in Europe, and at Keio University in Japan as well as offices around the world.

In 1999, he became the first holder of 3Com Founders chair at MIT. In 2008 he was named 3COM Founders Professor of Engineering in the School of Engineering, with a joint appointment in the Department of Electrical Engineering and Computer Science at CSAIL where he also heads the Decentralized Information Group (DIG). In December 2004 he was also named a Professor in the Computer Science Department at the University of Southampton, UK. From 2006 to 2011 he was co-Director of the Web Science Trust, launched as the Web Science Research Initiative, to help create the first multidisciplinary research body to examine the Web.

In 2008 he founded and became Director of the World Wide Web Foundation.  The Web Foundation is a non-profit organization devoted to achieving a world in which all people can use the Web to communicate, collaborate and innovate freely.  The Web Foundation works to fund and coordinate efforts to defend the Open Web and further its potential to benefit humanity.

In June 2009 then Prime Minister Gordon Brown announced that he would work with the UK Government to help make data more open and accessible on the Web, building on the work of the Power of Information Task Force. Sir Tim was a member of The Public Sector Transparency Board tasked to drive forward the UK Government’s transparency agenda.  He has promoted open government data globally, is a member of the UK’s Transparency Board.

In 2011 he was named to the Board of Trustees of the Ford Foundation, a globally oriented private foundation with the mission of advancing human welfare. He is President of the UK’s Open Data Institute which was formed in 2012 to catalyze open data for economic, environmental, and social value.

He is the author, with Mark Fischetti, of the book “Weaving the Web” on the past, present and future of the Web.

On March 18 2013, Sir Tim, along with Vinton Cerf, Robert Kahn, Louis Pouzin and Marc Andreesen, was awarded the Queen Elizabeth Prize for Engineering for “ground-breaking innovation in engineering that has been of global benefit to humanity.”

It should be very obvious from this rather short biography that Sir Tim is definitely a “heavy hitter”.

DARK WEB:

I honestly don’t think Sir Tim realized the full gravity of his work and certainly never dreamed there might develop a “dark web”.

The Dark Web is the public World Wide Web content existing on dark nets or networks which overlay the public Internet.  These networks require specific software, configurations or authorization to access. They are NOT open forums as we know the web to be at this time.  The dark web forms part of the Deep Web which is not indexed by search engines such as GOOGLE, BING, Yahoo, Ask.com, AOL, Blekko.com,  Wolframalpha, DuckDuckGo, Waybackmachine, or ChaCha.com.  The dark nets which constitute the Dark Web include small, friend-to-friend peer-to-peer networks, as well as large, popular networks like FreenetI2P, and Tor, operated by public organizations and individuals. Users of the Dark Web refer to the regular web as the Clearnet due to its unencrypted nature.

A December 2014 study by Gareth Owen from the University of Portsmouth found the most commonly requested type of content on Tor was child pornography, followed by black markets, while the individual sites with the highest traffic were dedicated to botnet operations.  Botnet is defined as follows:

“a network of computers created by malware andcontrolled remotely, without the knowledge of the users of those computers: The botnet was usedprimarily to send spam emails.”

Hackers built the botnet to carry out DDoS attacks.

Many whistle-blowing sites maintain a presence as well as political discussion forums.  Cloned websites and other scam sites are numerous.   Many hackers sell their services individually or as a part of groups. There are reports of crowd-funded assassinations and hit men for hire.   Sites associated with Bitcoinfraud related services and mail order services are some of the most prolific.

Commercial dark net markets, which mediate transactions for illegal drugs and other goods, attracted significant media coverage starting with the popularity of Silk Road and its subsequent seizure by legal authorities. Other markets sells software exploits and weapons.  A very brief look at the table below will indicate activity commonly found on the dark net.

As you can see, the uses for the dark net are quite lovely, lovely indeed.  As with any great development such as the Internet, nefarious uses can and do present themselves.  I would stay away from the dark net.  Just don’t go there.  Hope you enjoy this one and please send me your comments.


OKAY first, let us define “OPEN SOURCE SOFTWARE” as follows:

Open-source software (OSS) is computer software with its source-code made available with a license in which the copyright holder provides the rights to study, change, and distribute the software to anyone and for any purpose. Open-source software may be developed in a collaborative public manner. The benefits include:

  • COST—Generally, open source software if free.
  • FLEXIBILITY—Computer specialists can alter the software to fit their needs for the program(s) they are writing code for.
  • FREEDOM—Generally, no issues with patents or copyrights.
  • SECURITY—The one issue with security is using open source software and embedded code due to compatibility issues.
  • ACCOUNTABILITY—Once again, there are no issues with accountability and producers of the code are known.

A very detailed article written by Jacob Beningo has seven (7) excellent points for avoiding, like the plague, open source software.  Given below are his arguments.

REASON 1—LACKS TRACEABLE SOFTWARE DEVELOPMENT LIFE CYCLE–Open source software usually starts with an ingenious developer working out their garage or basement hoping to create code that is very functional and useful. Eventually multiple developers with spare time on their hands get involved. The software evolves but it doesn’t really follow a traceable design cycle or even follow best practices. These various developers implement what they want or push the code in the direction that meets their needs. The result is software that works in limited situations and circumstances and users need to cross their fingers and pray that their needs and conditions match them.

REASON 2—DESIGNED FOR FUNCTIONALITY AND NOT ROBUSTNESS–Open source software is often written for functionality only. Accessed and written to an SD card for communication over USB connections. The issue here is that while it functions the code, it generally is not robust and is never designed to anticipate issues.  This is rarely the case and while the software is free, very quickly developers can find that their open source software is just functional and can’t stand up to real-world pressures. Developers will find themselves having to dig through unknown terrain trying to figure out how best to improve or handle errors that weren’t expected by the original developers.

REASON 3—ACCIDENTIALLY EXPOSING CONFIDENTIAL INTELLECTURAL PROPERTY–There are several different licensing schemes that open source software developers use. Some really do give away the farm; however, there are also licenses that require any modifications or even associated software to be released as open source. If close attention is not being paid, a developer could find themselves having to release confidential code and algorithms to the world. Free software just cost the company in revealing the code or if they want to be protected, they now need to spend money on attorney fees to make sure that they aren’t giving it all away by using “free” software.

REASON 4—LACKING AUTOMATED AND/OR MANUAL TESTING–A formalized testing process, especially automated tests are critical to ensuring that a code base is robust and has sufficient quality to meet its needs. I’ve seen open source Python projects that include automated testing which is encouraging but for low level firmware and embedded systems we seem to still lag behind the rest of the software industry. Without automated tests, we have no way to know if integrating that open source component broke something in it that we won’t notice until we go to production.

REASON 5—POOR DOCUMENTATION OR DOCUMENTATION THAT IS LACKING COMPLETELY–Documentation has been getting better among open source projects that have been around for a long time or that have strong commercial backing. Smaller projects though that are driven by individuals tend to have little to no documentation. If the open source code doesn’t have documentation, putting it into practice or debugging it is going to be a nightmare and more expensive than just getting commercial or industrial-grade software.

REASON 6—REAL-TIME SUPPORT IS LACKING–There are few things more frustrating than doing everything you can to get something to work or debugged and you just hit the wall. When this happens, the best way to resolve the issue is to get support. The problem with open source is that there is no guarantee that you will get the support you need in a timely manner to resolve any issues. Sure, there are forums and social media to request help but those are manned by people giving up their free time to help solve problems. If they don’t have the time to dig into a problem, or the problem isn’t interesting or is too complex, then the developer is on their own.

REASON 7—INTEGRATION IS NEVER AS EASY AS IT SEEMS–The website was found; the demonstration video was awesome. This is the component to use. Look at how easy it is! The source is downloaded and the integration begins. Months later, integration is still going on. What appeared easy quickly turned complex because the same platform or toolchain wasn’t being used. “Minor” modifications had to be made. The rabbit hole just keeps getting deeper but after this much time has been sunk into the integration, it cannot be for naught.

CONCLUSIONS:

I personally am by no means completely against open source software. It’s been extremely helpful and beneficial in certain circumstances. I have used open source, namely JAVA, as embedded software for several programs I have written.   It’s important though not to just use software because it’s free.  Developers need to recognize their requirements, needs, and level of robustness that required for their product and appropriately develop or source software that meets those needs rather than blindly selecting software because it’s “free.”  IN OTHER WORDS—BE CAREFUL!

AMAZING GRACE

October 3, 2017


There are many people responsible for the revolutionary development and commercialization of the modern-day computer.  Just a few of those names are given below.  Many of whom you probably have never heard of.  Let’s take a look.

COMPUTER REVOLUNTARIES:

  • Howard Aiken–Aiken was the original conceptual designer behind the Harvard Mark I computer in 1944.
  • Grace Murray Hopper–Hopper coined the term “debugging” in 1947 after removing an actual moth from a computer. Her ideas about machine-independent programming led to the development of COBOL, one of the first modern programming languages. On top of it all, the Navy destroyer USS Hopper is named after her.
  • Ken Thompson and David Ritchie–These guys invented Unix in 1969, the importance of which CANNOT be overstated. Consider this: your fancy Apple computer relies almost entirely on their work.
  • Doug and Gary Carlson–This team of brothers co-founded Brøderbund Software, a successful gaming company that operated from 1980-1999. In that time, they were responsible for churning out or marketing revolutionary computer games like Myst and Prince of Persia, helping bring computing into the mainstream.
  • Ken and Roberta Williams–This husband and wife team founded On-Line Systems in 1979, which later became Sierra Online. The company was a leader in producing graphical adventure games throughout the advent of personal computing.
  • Seymour Cray–Cray was a supercomputer architect whose computers were the fastest in the world for many decades. He set the standard for modern supercomputing.
  • Marvin Minsky–Minsky was a professor at MIT and oversaw the AI Lab, a hotspot of hacker activity, where he let prominent programmers like Richard Stallman run free. Were it not for his open-mindedness, programming skill, and ability to recognize that important things were taking place, the AI Lab wouldn’t be remembered as the talent incubator that it is.
  • Bob Albrecht–He founded the People’s Computer Company and developed a sincere passion for encouraging children to get involved with computing. He’s responsible for ushering in innumerable new young programmers and is one of the first modern technology evangelists.
  • Steve Dompier–At a time when computer speech was just barely being realized, Dompier made his computer sing. It was a trick he unveiled at the first meeting of the Homebrew Computer Club in 1975.
  • John McCarthy–McCarthy invented Lisp, the second-oldest high-level programming language that’s still in use to this day. He’s also responsible for bringing mathematical logic into the world of artificial intelligence — letting computers “think” by way of math.
  • Doug Engelbart–Engelbart is most noted for inventing the computer mouse in the mid-1960s, but he’s made numerous other contributions to the computing world. He created early GUIs and was even a member of the team that developed the now-ubiquitous hypertext.
  • Ivan Sutherland–Sutherland received the prestigious Turing Award in 1988 for inventing Sketchpad, the predecessor to the type of graphical user interfaces we use every day on our own computers.
  • Tim Paterson–He wrote QDOS, an operating system that he sold to Bill Gates in 1980. Gates rebranded it as MS-DOS, selling it to the point that it became the most widely-used operating system of the day. (How ‘bout them apples.?)
  • Dan Bricklin–He’s “The Father of the Spreadsheet. “Working in 1979 with Bob Frankston, he created VisiCalc, a predecessor to Microsoft Excel. It was the killer app of the time — people were buying computers just to run VisiCalc.
  • Bob Kahn and Vint Cerf–Prolific internet pioneers, these two teamed up to build the Transmission Control Protocol and the Internet Protocol, better known as TCP/IP. These are the fundamental communication technologies at the heart of the Internet.
  • Nicklus Wirth–Wirth designed several programming languages, but is best known for creating Pascal. He won a Turing Award in 1984 for “developing a sequence of innovative computer languages.”

ADMIREL GRACE MURRAY HOPPER:

At this point, I want to highlight Admiral Grace Murray Hopper or “amazing Grace” as she is called in the computer world and the United States Navy.  Admiral Hopper’s picture is shown below.

Born in New York City in 1906, Grace Hopper joined the U.S. Navy during World War II and was assigned to program the Mark I computer. She continued to work in computing after the war, leading the team that created the first computer language compiler, which led to the popular COBOL language. She resumed active naval service at the age of 60, becoming a rear admiral before retiring in 1986. Hopper died in Virginia in 1992.

Born Grace Brewster Murray in New York City on December 9, 1906, Grace Hopper studied math and physics at Vassar College. After graduating from Vassar in 1928, she proceeded to Yale University, where, in 1930, she received a master’s degree in mathematics. That same year, she married Vincent Foster Hopper, becoming Grace Hopper (a name that she kept even after the couple’s 1945 divorce). Starting in 1931, Hopper began teaching at Vassar while also continuing to study at Yale, where she earned a Ph.D. in mathematics in 1934—becoming one of the first few women to earn such a degree.

After the war, Hopper remained with the Navy as a reserve officer. As a research fellow at Harvard, she worked with the Mark II and Mark III computers. She was at Harvard when a moth was found to have shorted out the Mark II, and is sometimes given credit for the invention of the term “computer bug”—though she didn’t actually author the term, she did help popularize it.

Hopper retired from the Naval Reserve in 1966, but her pioneering computer work meant that she was recalled to active duty—at the age of 60—to tackle standardizing communication between different computer languages. She would remain with the Navy for 19 years. When she retired in 1986, at age 79, she was a rear admiral as well as the oldest serving officer in the service.

Saying that she would be “bored stiff” if she stopped working entirely, Hopper took another job post-retirement and stayed in the computer industry for several more years. She was awarded the National Medal of Technology in 1991—becoming the first female individual recipient of the honor. At the age of 85, she died in Arlington, Virginia, on January 1, 1992. She was laid to rest in the Arlington National Cemetery.

CONCLUSIONS:

In 1997, the guided missile destroyer, USS Hopper, was commissioned by the Navy in San Francisco. In 2004, the University of Missouri has honored Hopper with a computer museum on their campus, dubbed “Grace’s Place.” On display are early computers and computer components to educator visitors on the evolution of the technology. In addition to her programming accomplishments, Hopper’s legacy includes encouraging young people to learn how to program. The Grace Hopper Celebration of Women in Computing Conference is a technical conference that encourages women to become part of the world of computing, while the Association for Computing Machinery offers a Grace Murray Hopper Award. Additionally, on her birthday in 2013, Hopper was remembered with a “Google Doodle.”

In 2016, Hopper was posthumously honored with the Presidential Medal of Freedom by Barack Obama.

Who said women could not “do” STEM (Science, Technology, Engineering and Mathematics)?

HACKED OFF

October 2, 2017


Portions of this post are taken from an article by Rob Spiegel of Design News Daily.

You can now anonymously hire a cybercriminal online for as little as six to ten dollars ($6 to $10) per hour, says Rodney Joffe, senior vice president at Neustar, a cybersecurity company. As it becomes easier to engineer such attacks, with costs falling, more businesses are getting targeted. About thirty-two (32) percent of information technology professionals surveyed said DDoS attacks cost their companies $100,000 an hour or more. That percentage is up from thirty (30) percent reported in 2014, according to Neustar’s survey of over 500 high-level IT professionals. The data was released Monday.

Hackers are costing consumers and companies between $375 and $575 billion, annually, according to a study published this past Monday, a number only expected to grow as online information stealing expands with increased Internet use.  This number blows my mind.   I actually had no idea the costs were so great.  Great and increasing.

Online crime is estimated at 0.8 percent of worldwide GDP, with developed countries in regions including North America and Europe losing more than countries in Latin American or Africa, according to the new study published by the Center for Strategic and International Studies and funded by cybersecurity firm McAfee.

That amount rivals the amount of worldwide GDP – 0.9 percent – that is spent on managing the narcotics trade. This difference in costs for developed nations may be due to better accounting or transparency in developed nations, as the cost of online crime can be difficult to measure and some companies do not do disclose when they are hacked for fear of damage to their reputations, the report said.

Cyber attacks have changed in recent years. Gone are the days when relatively benign bedroom hackers entered organizations to show off their skills.  No longer is it a guy in the basement of his or her mom’s home eating Doritos.  Attackers now are often sophisticated criminals who target employees who have access to the organization’s jewels. Instead of using blunt force, these savvy criminals use age-old human fallibility to con unwitting employees into handing over the keys to the vault.  Professional criminals like the crime opportunities they’ve found on the internet. It’s far less dangerous than slinging guns. Cybersecurity is getting worse. Criminal gangs have discovered they can carry out crime more effectively over the internet, and there’s less chance of getting caught.   Hacking individual employees is often the easiest way into a company.  One of the cheapest and most effective ways to target an organization is to target its people. Attackers use psychological tricks that have been used throughout mankind.   Using the internet, con tricks can be carried out on a large scale. The criminals do reconnaissance to find out about targets over email. Then they effectively take advantage of key human traits.

One common attack comes as an email impersonating a CEO or supplier. The email looks like it came from your boss or a regular supplier, but it’s actually targeted to a specific professional in the organization.   The email might say, ‘We’ve acquire a new organization. We need to pay them. We need the company’s bank details, and we need to keep this quiet so it won’t affect our stock price.’ The email will go on to say, ‘We only trust you, and you need to do this immediately.’ The email comes from a criminal, using triggers like flattery, saying, ‘You’re the most trusted individual in the organization.’ The criminals play on authority and create the panic of time pressure. Believe it or not, my consulting company has gotten these messages. The most recent being a hack from Experian.

Even long-term attacks can be launched by using this tactic of a CEO message. “A company in Malaysia received kits purporting to come from the CEO.  The users were told the kit needed to be installed. It took months before the company found out it didn’t come from the CEO at all.

Instead of increased technology, some of the new hackers are deploying the classic con moves, playing against personal foibles. They are taking advantage of those base aspects of human nature and how we’re taught to behave.   We have to make sure we have better awareness. For cybersecurity to be engaging, you have to have an impact.

As well as entering the email stream, hackers are identifying the personal interests of victims on social media. Every kind of media is used for attacks. Social media is used to carry out reconnaissance, to identify targets and learn about them.  Users need to see what attackers can find out about them on Twitter or Facebook. The trick hackers use is to pretend they know the target. Then the get closes through personal interaction on social media. You can look at an organization on Twitter and see who works in finance. Then they take a good look across social platform to find those individuals on social media to see if they go to a class each week or if they traveled to Iceland in 1996.  You can put together a spear-phishing program where you say, Hey I went on this trip with you.

CONCLUSIONS:

The counter-action to personal hacking is education and awareness. The company can identify potential weaknesses and potential targets and then change the vulnerable aspects of the corporate environment.  We have to look at the culture of the organization. Those who are under pressure are targets. They don’t have time to study each email they get. We also have to discourage reliance on email.   Hackers also exploit the culture of fear, where people are punished for their mistakes. Those are the people most in danger. We need to create a culture where if someone makes a mistake, they can immediately come forward. The quicker someone comes forward, the quicker we can deal with it.


In preparation for this post, I asked my fifteen-year old grandson to define product logistics and product supply chain.  He looked at me as though I had just fallen off a turnip truck.  I said you know, how does a manufacturer or producer of products get those products to the customer—the eventual user of the device or commodity.  How does that happen? I really need to go do my homework.  Can I think about this and give you an answer tomorrow?

SUPPLY CHAIN LOGISTICS:

Let’s take a look at Logistics and Supply Chain Management:

“Logistics typically refers to activities that occur within the boundaries of a single organization and Supply Chain refers to networks of companies that work together and coordinate their actions to deliver a product to market. Also, traditional logistics focuses its attention on activities such as procurement, distribution, maintenance, and inventory management. Supply Chain Management (SCM) acknowledges all of traditional logistics and also includes activities such as marketing, new product development, finance, and customer service” – from Essential of Supply Chain Management by Michael Hugos.

“Logistics is about getting the right product, to the right customer, in the right quantity, in the right condition, at the right place, at the right time, and at the right cost (the seven Rs of Logistics)” – from Supply Chain Management: A Logistics Perspective By John J. Coyle et al

Now, that wasn’t so difficult, was it?  A good way to look at is as follows:

MOBILITY AND THE SUPPLY CHAIN:

There have been remarkable advancements in supply chain logistics over the past decade.  Most of those advancements have resulted from companies bringing digital technologies into the front office, the warehouse, and transportation to the eventual customer.   Mobile technologies are certainly changing how products are tracked outside the four walls of the warehouse and the distribution center.  Realtime logistics management is within the grasp of many very savvy shippers.  To be clear:

Mobile networking refers to technology that can support voice and/or data network connectivity using wireless, via a radio transmission solution. The most familiar application of mobile networking is the mobile phone or tablet or i-pad.  From real-time goods tracking to routing assistance to the Internet of Things (IoT) “cutting wires” in the area that lies between the warehouse and the customer’s front door is gaining ground as shippers grapple with fast order fulfillment, smaller order sizes, and ever-evolving customer expectations.

In return for their tech investments, shippers and logistics managers are gaining benefits such as short-ended lead times, improved supply chain visibility, error reductions, optimized transportation networks and better inventory management.  If we combine these advantages we see that “wireless” communications are helping companies work smarter and more efficiently in today’s very fast-paced business world.

MOBILITY TRENDS:

Let’s look now at six (6) mobility trends.

  1. Increasingly Sophisticated Vehicle Communications—There was a time when the only contact a driver had with home base was after an action, such as load drop-off, took place or when there was an in-route problem. Today, as you might expect, truck drivers, pilots and others responsible for getting product to the customer can communicate real-time.  Cell phones have revolutionized and made possible real-time communication.
  2. Trucking Apps—By 2015, Frost & Sullivan indicated the size of the mobile trucking app market hit $35.4 billion dollars. Mobile apps are being launched, targeting logistics almost constantly. With the launch of UBER Freight, the competition in the trucking app space has heated up considerably, pressing incumbents to innovate and move much faster than ever before.
  3. Its’ Not Just for the Big Guys Anymore: At one time, fleet mobility solutions were reserved for larger companies that could afford them.  As technology has advanced and become more mainstream and affordable, so have fleet mobility solution.
  4. Mobility Helps Pinpoint Performance and Productivity Gaps: Knowing where everything is at any one given time is “golden”. It is the Holy Grail for every logistics manager.  Mobility is putting that goal within their reach.
  5. More Data Means More Mobile Technology to Generate and Support Logistics: One great problem that is now being solved, is how to handle perishable goods and refrigerated consumer items.  Shippers who handle these commodities are now using sensors to detect trailer temperatures, dead batteries, and other problems that would impact their cargos.  Using sensors, and the data they generate, shippers can hopefully make much better business decisions and head off problems before they occur.  Sensors, if monitored properly, can indicate trends and predict eventual problems.
  6. Customers Want More Information and Data—They Want It Now: Customer’s expectations for real-time shipment data is now available at their fingertips without having to pick up a telephone or send an e-mail.  Right now, that information is available quickly online or with a smartphone.

CONCLUSIONS: 

The world is changing at light speed, and mobility communications is one technology making this possible.  I have no idea as to where we will be in ten years, but it just might be exciting.

MULTITASKING

September 14, 2017


THE DEFINITION:

“Multitasking, in a human context, is the practice of doing multiple things simultaneously, such as editing a document or responding to email while attending a teleconference.”

THE PROCESS:

The concept of multitasking began in a computing context. Computer multitasking, similarly to human multitasking, refers to performing multiple tasks at the same time. In a computer, multitasking refers to things like running more than one application simultaneously.   Modern-day computers are designed for multitasking. For humans, however, multitasking has been decisively proven to be an ineffective way to work. Research going back to the 1980s has indicated repeatedly that performance suffers when people multitask.

REALITY:

Multitasking is not a natural human trait.  In a few hundred years, natural evolution may improve human abilities but for now, we are just not good at it.  In 2007, an ABC Evening News broadcast cited, “People are interrupted once every ten and one-half minutes (10.5).  It takes twenty-three (23) minutes to regain your train of thought.  People lose two point one (2.1) hours each day in the process of multitasking.”

A great article entitled “No Task Left Behind” by Mark Gloria, indicated that a person juggled twelve (12) work spheres each day and fifty-seven percent (57%) of the work got interrupted.  As a result, twenty-three percent (23%) of the work to be accomplished that day got pushed to the next day and beyond. That was the case twelve years ago.  We all have been there trying to get the most of each day only to return home with frustration and more to do the next day.

Experience tells us that:

  • For students, an increase in multitasking predicted poorer academic results.
  • Multitaskers took longer to complete tasks and produced more errors.
  • People had more difficulty retaining new information while multitasking.
  • When tasks involved making selections or producing actions, even very simple tasks performed concurrently were impaired.
  • Multitaskers lost a significant amount of time switching back and forth between tasks, reducing their productivity up to forty percent (40%).
  • Habitual multitaskers were less effective than non-multitaskers even when doing one task at any given time because their ability to focus was impaired.
  • Multitasking temporarily causes an IQ drop of 10 points, the equivalent of going without sleep for a full night.
  • Multitaskers typically think they are more effective than is actually the case.
  • There are limited amounts of energy for any one given day.
  • Multitasking can lessen inter-personal skills and actually detract from the total work force.
  • It encourages procrastination.
  • A distracted mind may become permanent.

THE MYTH OF MULTITASKING:

People believe multitasking is a positive attribute, one to be admired. But multitasking is simply the lack of self-discipline. Multitasking is really switching your attention from one to task to another to another, instead of giving yourself over to a single task. Multitasking is easy; disciplined focus and attention is difficult.

The quality of your work is determined by how much of your time, your focus and your attention you give it. While multitasking feels good and feels busy, the quality of the work is never what it could be with the creator’s full attention. More and more, this is going to be apparent to those who are judging the work, especially when compared to work of someone who is disciplined and who has given the same or similar project their full focus and attention.

MENTAL FLOW:

In positive psychology, flow, also known as the zone, is the mental state of operation in which a person performing an activity is fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity.

The individual who coined the phrase “flow” was Mihaly Csikszentmihalyi. (Please do NOT ask me to pronounce Dr. Csikszentmihalyi’s last name.)  He made the following statement:

“The best moments in our lives are not the passive, receptive, relaxing times… The best moments usually occur if a person’s body or mind is stretched to its limits in a voluntary effort to accomplish something difficult and worthwhile.”

– Mihaly Csikszentmihalyi  

EIGHT CHARACTERISTICS OF “FLOW”:

  1. Complete concentration on the task.  By this we mean really complete.
  2. Clarity of goals and reward in mind and immediate feedback. No need to focus and concentrate when there are no goals in mind to indicate completion.
  3. Transformation of time (speeding up/slowing down of time). When in full “flow” mode, you lost time.
  4. The experience is intrinsically rewarding, has an end itself.
  5. Effortlessness and ease.
  6. There is a balance between challenge and skills.
  7. Actions and awareness are merged, losing self-conscious rumination.
  8. There is a feeling of control over the task.

I personally do not get there often but the point is—you cannot get in the “zone”, you will not be able to achieve mental “flow” when you are in the multitasking mode.  I just will not happen.

As always, I welcome your comments.

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