Man v. Machine

Smart machines learn by playing games, making mistakes and learning from them. To solve new challenges not stored in past experience, machines create new paths through data.  Machines learn quickly, forge their way in unanticipated directions through the neural network frameworks constructed by Google, Facebook, Amazon, etc.  This burrowing through networks of neuron-aping nodes, called deep-learning sometimes results in unpredictable behavior. If machines behave in unexpected ways, their human creators have lost control.

Organizations have formed to develop ethics standards for robotics and AI. Refer to Open Roboethics and the Foundation for Responsible Robotics to watch the progress of Robot ethics standards development.

Dr Jason Millar,  The Guardian, March, 2017  “The momentous advance in artificial intelligence demands a new set of ethics”

Big Data

You might want to take a look at Managing Big Data Workflows for Dummies

The book is free to download and makes quite clear that Data Warehouses are inadequate for many of today’s industries as their data grows.

Think of all the data required to run all the items connected in the IoT (Internet of Things)

The prevalence of clouds, megla-server clusters spread throughout the world have room to store seemingly infinite data, called Big Data. Big Data requires new architectures and processes to store and process. Some examples: Data Lakes are large, flat accumulations of data, each with its own processing engine–similar to splitting Big Data into multiple data warehouses. NoSQL is a nonRelational, scalable collection of large volumes of multi-variety data. Schema-on-read enables you to structure data on retrieval to fit the task requiring that data.


To learn more about Big Data storage and retrieval, take one or more tutorials at

The end of computer programming

The brain has functions analogous to a computer –writing (communicating), storing, recalling via a formal syntax.  For decades, human programmers have been coding behavior using languages such as machine-command Assembly Language, and higher-level Basic, C#, Java, HTML/XML, IOS, etc. These language programs consist of step-by-step instructions that instruct a machine to create, manipulate, store and recall data.

In contrast, programmers have begun to train computational systems (computers, phones, smart gadgets) by exposing them to myriads of examples. Wired magazine, June 2016   describes this phenomenon in “/*The End of Code*/”

” If you want to teach a neural network to recognize a cat, for instance, you don’t tell it to look for whiskers, ears, fur, and eyes. You simply show it thousands and thousands of photos of cats, and eventually it works things out.”

Facebook, Google, Microsoft use massive distributed computational systems mimic the multilayered neural connections of the human brain. Thus, Facebook knows what tidbits to assemble as your news feed, Google Search is moving from human-written algorithms to reliance on deep neural networks.

Soon We Won’t Program Computers. We’ll Train Them Like Dogs

Neural Networks

Your brain consists of a network of neural cells that transport and combine charges or message fragments. The network configures new paths to accommodate learning (new information or perceptions).

Per Wired Magazine, July 2016 issue, “Neural networks are changing the Internet. Inspired by the networks of neurons inside the human brain, these deep mathematical models can learn discrete tasks by analyzing enormous amounts of data. They’ve learned torecognize faces in photos, identify spoken commands, and translate text from one language to another. And that’s just a start. They’re also moving into the heart of tech giants like Google and Facebook. They’re helping to choose what you see when you query the Google search engine or visit your Facebook News Feed.”

In other words, information on the Internet is not linear or programmed in static HTML. The Information Highway is a living, learning , hopefully self-correcting entity.



World without private Cars

Imagine a future without car payments, auto insurance bills (Sorry Flo) and maintenance.
Uber finds a driver and vehicle near you.
Zipcar finds car that you can drive.
You pay on a pay per use basis..
Driver-less cars exist today.

We will need technology, regulation and social acceptance. (Taken from an article called the future of mobility.Published by Deloitte University Press)


3D Printers –Build What You Can’t Buy

Any citizen, terrorist or nut case with a 3D printer can create an unregistered (ghost) gun. The picture below shows the components of a gun prior to assembly. (Wired Magazine, August 2015)

3D printed gun

Gun parts

The keys below fit “restricted keyways”. They are distributed to only those few people who are approved for access to whatever lies behind a matching locked entry. (Wired newsletter, August 4, 2015)

metal copy-protected keys

Normal secure metal keys has an app that generates a CAD model of a key blank from a single picture of a lock.  The generated key can be modeled by the 3D printer in either plastic or metal.



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Virtual Reality you can afford

Intercom, the Society of Technical Communications magazine,included an article called “Trying Virtual Reality on the Cheap With Google Cardboard” by Neil Perlin. If you have an Android phone, order a Google Virtual Reality cardboard viewer from Amazon for under $30.
The viewer comes as a flat piece cardboard with built-in lenses and instructions to fold it .
After you fold your viewer, it will look something like this.

Cardboard VR viewer

Get a VR app on your phone from Google play, slip the phone in front of your viewer and enjoy. So far, available apps for a cardboard viewer budget are games and stories in which you are one of the characters.
Future plans are training experiences, such as showing technicians how to how to maintain large equipment, or placing fledgling firefighters in simulated virtual reality fires. See the Samsung Gear VR.

For a more sophisticated viewer that is currently available, check out the Samsung Gear VR .SamsungVR




google it

When I first entered the micro-computer world, I was the only one of my friends who purchased an assembled PC. All the guys in the NYC Amateur Computer Club built theirs. I bought Apple #3, a small white case with a keyboard and a cable to connect my TV as the screen.  I loved that machine, carried it around town on the back of my bicycle.  I showed it to a junior HS class I was teaching. We opened it, looked inside at the boards–One of my students wanted to see the   software.
I met a fellow hobbyist who had a machine that displayed bits travelling over wires–we could see software!

I bought a Pascal card for my Apple. I knew something about programming big machines, so I tried my luck with Pascal.  I drew a graphic- an apple logo! Imagine that-a picture on a screen that normally spewed text.  I waited all night, the apple slowly took on an outline. When complete, my apple was upside down. No matter. What a magic world where computers could draw pictures.

I had the enormous fortune to land a small job as a technical writer at Carnegie Mellon U Robotics Institute.  Carnegie was one of the universities connected to the military’s Arpanet, the pre-cursor to today’s Internet. I had an email account– I could exchange memos with other Arpanet-connected folks.

Years later, I moved to CA where a young Stanford student named Jerry Yahoo created a search engine. Soon there were competitors. A small campus emerged in Mountain View called Google. I watched it grow as I rode by each day on my bike.

Today, 20+ years later, I find everything I want out in the world by querying Google. Our world is completely knit together and indexed to facilitate retrieval. Usually I am thankful to have these years since 1970 to watch the cyber world evolve. It is my world and keeps me alert. But we lost privacy along the way.

Writing for Reader Experience

Society of Technical Communication (STC) Intercom Magazine contained the article cited below describing how we technical writers should present information to users. Today’s emphasis has shifted from cost-efficient content management to consumer experience. Our job is to delight users and simplify the message. Ways to do this include:

> Invert the relationship between text and image. Choose key images first then choose text to support the image.  Start with a screenshot, insert numbered callouts and write a very brief action for each numbered item.

>Do not waste the reader’s time with instructions for intuitive GUI (Graphical User Interface-the window) buttons and menus. Your reader is already overloaded with information and just has a task s/he needs to know how to accomplish.

>Ignore constraints of tools for maintaining content, such as DITA or XML. Reused content has no context, is repetitive and boring.

>Optimize for the web, not for PDFs.

>Use a clean page layout, sharp photographs and screenshots and lots of white space to make your information easy to consume.

Make connecting with you users your first priority.  Start by asking them what they need.

Another note about DITA, XML and what version of Adobe software you last used. In my job hunting experience, tool proficiency interferes with the hiring process, making it difficult to hire non-writers who have so much knowledge to add but no authoring platform experience.  For myself, I have 35 years experience writing documentation,  Web Design Certification and a comprehensive online portfolio, but recruiters invariably ask what version of FrameMaker, Captivate, etc. I last used.

Reference: STC Intercom February 2015 issue, Writer’s Block: How to Write Content That Delights, and Why We So Often Don’t by Barry Grenon