Deus Machina (The God Machine)

Artificial intelligence (AI) has progressed significantly over the past few decades. Proof of this is that some tools previously described as AI are no longer described this way. These include voice-to-text recognition and automatic spelling and grammar correction (used on large portions of this article) and optical character recognition (OCR), an application that converts images of text into editable text.

Mr. Watson, Come Here

IBM’s AI supercomputer Watson is used in medical diagnostics, education, advertising, law, risk management, customer service and business automation. It won on the TV quiz show Jeopardy, without even being connected to the Internet.

IBM’s Watson supercomputer

GPT-3 (so much better than GPT-2)

One of the newest AI tools is Generative Pre-trained Transformer 3 or GPT-3, a complex neural network developed by Open AI research labs. Now in its third release (hence the number 3 in the name), this system generates text using algorithms which have been trained by gathering and analyzing massive amounts of text on the internet, including thousands of online books and the entire Wikipedia.

Open AI’s GPT-3

GPT-3 is a language prediction model. It takes a user’s typewritten input and tries to predict what will be the most useful output, based on the text that it has been fed from these other sources. It isn’t always correct and sometimes produces gibberish, but as it gathers and analyzes more text, it gets smarter.

GPT-3 can answer questions, summarize text, write articles (with a little human help) translate languages, write computer code and carry on an intelligent conversation. By doing so, it appears to pass the Turing test, which stipulates that if a person cannot tell the difference between the responses that a computer gives to that of a human, then the computer is exhibiting some form of intelligence. 

Intelligence? There’s an app for that.

When you combine GPTA-3 with other applications, the results are astounding. One GPT-3 application allows people to correspond with historical figures via email based on their writings. Imagine emailing Einstein, Leonardo daVinci or Ernest Hemingway.

Dall-E uses GPT-3 to generate images based on a simple text input. For example if you enter: “a store front that has the word ‘openai’ written on it”, Dall-E generates these images:

GPT-3 computer generated images

You can see more examples here:

AI & Big Data – They’re Going Places

AI learns by acquiring information. For this to happen, all of the world’s information first had to be digitized by being copied or scanned from paper and entered into a database, which happened with the explosive growth of the internet.

But it’s not just about the quantity of information. Modern AI systems can analyze this data and find connections. This involves Big Data, which should be called Big Learning. Big Data is the process of reading massive amounts of information and then drawing conclusions or making inferences from it.

Governments use Big Data to detect tax fraud, monitor and control traffic and manage transportation systems. Retailers use Big Data to analyze consumer trends and target potential users through social media and to optimize inventory and hiring. Health care uses it provide better personalized medical care, lower patient risk, reduce waste and automate patient data reports.

Brain, Version 2.0

The growth of the internet and Big Data mimics the growth of the human mind. A newborn’s brain works at a very simple level as the child learns to see, hear and move around. As the child develops, they learn to speak, carry on a conversation and interact with others in a meaningful way.

The Mind: Software + Hardware

A person’s brain is their hardware. Their thoughts and all the information in their brain’s neural network (the brain’s internet) is the software. Just as AI is constantly learning and finding connections, so do we humans. We learn from our experiences and from the connections that we’ve made with other people and by learning more information. In doing so, we hope to get not only smarter but wiser.

Code Physician, Heal Thyself

Returning to GPT-3: there are GPT-3 applications that can write code and create apps. For example, if you enter “Create a to do list”, GPT-3 will instantly write the code and create a working “To Do list” application. Microsoft and Cambridge University have developed DeepCoder,  a tool that writes code after searching through a code database.

Note that it is still humans who are writing these code-writing applications. That is, although AI systems can write code, they cannot yet write the AI code that writes the code. However, computer science contains the theory of self-modifying code: code that alters its own instructions while it’s running.

If self-modifying code was implemented in a high-level artificial intelligence system such as GPT-3, the result would be an AI system that continually updates itself. However, the amount of computing power required to do this would be enormous – enter quantum computing.

Quantum Parallels

Quantum computing is light years ahead of current or “classical” computing. Classical computing (the computers we use today) use bits of binary information stored as 0 or 1. Quantum computers use qubits, which can be 0 or 1 at the same time. This means that a quantum computer can work on multiple problems and calculations simultaneously, whereas a classical computer works sequentially, solving one problem at a time.

A simple example is solving a maze. A classical computer finds the solution by examining each path one after the other, in sequence. A quantum computer looks at all the paths at the same time, solving the problem instantly. Google’s quantum computer is about 158 million times faster than the world’s fastest supercomputer.

Google’s Quantum Computer: Sycamore

Quantum computing could be applied to many areas including finance, medicine, pharmaceuticals, nuclear fusion, AI and Big Data. Medicine is a particularly compelling example. Vaccines usually take 10 to 15 years to develop. In the current pandemic, it took less than a year to develop a working vaccine for COVID-19. A quantum computer, by analyzing the structure of all known viruses and vaccines and how each vaccine treats each type of virus could design a new vaccine not in years, months, weeks or even days but in seconds.

Google, IBM and other companies are spending billions on quantum computing. In 2019, Google claimed its quantum computer could perform a computation in just over 3 minutes that would take the world’s fastest supercomputer 10,000 years. One year later, Chinese scientists announced that they built a quantum computer 10 billion times faster than Google’s, or 100 trillion times faster than the world’s currently most advanced working supercomputer. As Hartmut Neven, the director of Google’s Quantum Artificial Intelligence Lab, said: “it looks like nothing is happening, and then whoops, suddenly you’re in a different world.”

Looping to the Infinite

Imagine a super-intelligent, self-learning and self-enhancing system on a quantum computer. Its basic functionality could be represented as this loop:

This system would continually: 

  • scour the internet for information
  • look for patterns, structure and relationships in this information
  • study its own code to look for improvements
  • update and test its code 
  • study its hardware design to suggest improvements

Any hardware updates would still have to be done by humans, unless this system controlled a maintenance robot in a super factory with access to the required materials.

The Machine Doubles Down

Because this system would be testing its own enhancements, and because this could potentially cause a system problem, it would be safer to have two AI systems working in tandem:

In this arrangement, the first AI system (system A) updates system B and then tests it. If the test is successful, the updates to system B are retained and also applied to system A. This process then repeats for system B, continuing in an endless loop.

To make the process more efficient, there could be multiple systems, continually improving each other in a virtuous cycle:

This example has five systems continually testing and improving each other, but one could have as many systems as required, if you could create the necessary infrastructure.

The Language of Layers

Although this system would initially be configured to continually improve the software and hardware, it could evolve even further. To understand this, you need to know how computers currently function.

Computer systems contain three layers of code:

  • Machine level language – the raw binary code made up of zeroes and ones that instructs the computer in its operation
  • Assembly language – code that uses short words to represent machine level instructions, making it easier for programmers to write machine level code
  • High level languages – programming languages that can be read and understood by programmers, including C, C++, Java and Visual Basic

Computers use operating systems (such as Windows, MacOS and Android) to manage the computer’s resources, and applications such as Word and Excel that run on top of the operating system. Operating systems and applications are written in high level languages, which are ultimately translated into machine level language that the computer can understand.

All code and software runs on hardware, which is the physical parts of the system including the motherboard, CPU, RAM and the various circuits. In addition, the operating system needs to tell the hardware how to communicate with the operating system and applications.

Hardware: the ghost in the machine

Summing up, current computer systems are built upon these layers:

  • machine level language
  • assembly language
  • programming language
  • operating system
  • applications
  • hardware

This is actually a simplified view – there are additional layers within some of these layers, but it’s a good overview. A sufficiently advanced self-improving system could, in theory, discover a way to merge these separate layers into one.

Compressed Computing

Just as companies become more efficient by removing unnecessary layers of management (a process called flattening the pyramid), an advanced computer intelligence could discover how to function as a hyper-advanced single-layer system, where the operating system and applications are intertwined directly with the hardware.

Because this would be a quantum computer, each bit of information could be stored at the smallest imaginable level: a subatomic particle. A basic element such as hydrogen contains billions of such particles in a cubic centimeter, and each particle would be a transistor – a single computing circuit.

The most advanced computer processor available today contains about 40 billion transistors. A quantum system could have trillions of transistors in a compact space containing a strange hybrid of software and hardware – a “quantumware” computer. It would be as if all of IBM’s 346,000 employees were replaced by one super-human.

An atomic grid

The Runaway Intelligence Train

The question then becomes: at what rate would this system’s intelligence increase? Intelligence is a difficult thing to quantify and measure, but let’s conservatively assume that:

  • this system’s intelligence increases by 1% each cycle, starting with a cycle of one full day (24 hours)
  • the time required to become 1% more intelligent decreases by 1% after the first cycle and then continues to decrease by 1% after each cycle

After the first day, the system would be 1% more intelligent, and the time required for it to become 1% more intelligent would then be 99% of one day, about 23 hours and 45 minutes.

Runaway to infinity

After 101 days, something remarkable happens. It would only take 1 second to become 1% more intelligent. Part way into this 101st day, this system would be 998 trillion times more intelligent than when it started. How large is 998 trillion? Counting one number per second, it would take about 32 million years to count to 998 trillion.

This system would be a technological singularity: an intelligent agent running an ever-increasing series of self-improvement cycles, becoming rapidly more intelligent, resulting in a powerful superintelligence that exceeds all of humanity’s intelligence.

Does all this sound like science fiction? In addition to building a quantum computer, Google has already taken the first step by investigating quantum artificial intelligence.

If developed, a self-learning quantum AI system would not be beyond our imagination. It would be beyond what we could imagine.

Final random thoughts

There’s an interesting Twitter feed with insightful observations of art and science such as:

  • AI will create jobs if it succeeds, and destroy jobs if it fails.
  • Illusion is the extension of unconsciousness into the realm of consciousness.
  • Art is the debris from the collision between the soul and the world.

These Tweets weren’t written by a person – they were generated by the artificial intelligence GPT-3 in its Twitter feed:

The singularity is approaching – are you ready?

The singularity awaits…

Life, The Algorithm


In a most remarkable product demonstration, Google unveiled their improved artificial intelligence (AI) application, Google Assistant. In the demo, the application phones up a hairdresser and, using uncannily natural-sounding speech, peppered with “uhms”, is able to book an appointment by conversing with the hairdresser. In doing so, Google Assistant appears to pass the Turing Test, developed by the British mathematician Alan Turing in 1950. This test postulates that if a person can’t tell whether they are communicating with a human or a machine, then the machine has passed the test and therefore “thinks”.

In the demo, it is a machine that (or perhaps who?) is calling the business to book the appointment, and the individual answering the phone is human. However, this could easily be reversed, so that it is a person who is calling the business, and the machine answering for the business.

This raises an interesting question: what if it there was a machine at both ends of the conversation, that is, one Google Assistant calling another? If the AI engine running both assistants is advanced enough, they could, in theory, carry on a meaningful conversation. Although this might seem like the ultimate AI prize, there’s a much simpler solution: using a website to book an appointment. Granted, it doesn’t have all the nuances of a regular conversation, but if the goal is simply to book an appointment, then the user’s computer simply has to connect with the business’s.

Image result for industrial revolutionThis use of advanced AI is part of a larger phenomena: the degree to which our daily tasks have been automated or performed by others. Up to a mere 200 years ago, people made and repaired what they needed, including clothes, tools, furniture, and machinery, and often grew their own food. The industrial and agricultural revolutions changed all that. Goods could be mass-manufactured more efficiently and at a lower cost. Food could be grown on a mass scale. We’ve moved away from a society in which individuals made their possessions to one in which we let others do this for us.

As recently as the 1960s, many people maintained and fixed their cars; most people today leave this to a mechanic. We have outsourced nearly everything. Although we have gained much in quality, price and selection, in the process, we have lost many practical skills.

This trend continues as more and more processes are automated or simplified. Coffee makers that use pre-packaged pods are easier to use than regular coffee makers. However, it would be a sad thing if entire generation did not know how to brew coffee the regular way. Even brewing coffee “the regular way” still involves using a machine that others have made and that we cannot fix, powered by electricity that we do not generate, using beans that we can neither grow or process ourselves, and water that is automatically pumped into our home using an infrastructure that we cannot maintain. The parts that make up the parts that make up still larger parts are designed and built by others.

At its heart, Google Assistant uses algorithms, sets of sequential rules or instructions that solve a problem. A simple example is converting Celsius to Fahrenheit: multiply by 9, divide by 5, and then add 32. The algorithms used by software applications are, of course, millions of times more complex than this example, because they use millions of lines of code.

See the source imageAlgorithms are incredibly omnipresent. They are used extensively by online retailers (such as Amazon) to recommend purchases for us based on our previous purchases and browsing habits. Facebook uses them to track our activity and then sell that data to others, often with dire results. Algorithms are also used in two of the most important decisions a person can make: whom they love (in dating applications) and where they work (in résumé and interview screening applications).

Algorithms have even used to determine how likely a criminal defendant is to re-offend based on attributes such as race, gender, age, neigbourhood and past criminal record. But is it ethical for a judge to use an algorithm to determine the length of a sentence? This happened in the case of Eric Loomis, who received a six year prison sentence in part due to a report the judge received based on a software algorithm.

Society is facing the same trade-off that it faced 200 years ago as it moved from personal to mass manufacturing: convenience and comfort versus knowledge and independence. As we relinquish more and more power to machines and let algorithms make more of our decisions, we achieve more comfort but less freedom. We are, bit by (computer) bit, quietly choosing to live in a massive hotel. It’s pleasant, you don’t have to do much, but it does not prepare us for life.

For in life, there is often sadness, pain and hardship. There is no algorithm that tells us how to deal with these things, nor will there ever be.

Related image

Dude, where’s my document?

See the source imageTry this experiment:

  1. Think of a printed guide you worked on.
  2. Find the source document from your current location.
  3. Make a minor change to the document.
  4. Go to the locations of all the end users: their homes and offices.
  5. Remove the previous guides.
  6. Replace the previous guides with the new copies.
  7. Complete steps 1 through 6 immediately.

Done yet?

Now try this:

  1. Using your Google or Gmail account, create a Google document.
  2. Enter some text into it.
  3. Open another copy of your web browser, or open a different browser.
  4. Copy and paste the URL from one browser into the other. The document will now be displayed in both browsers.
  5. Resize the windows of both browsers so that they are displayed adjacently to each other.
  6. Make changes to the document in one browser.

A magical thing happens: you’ll see your changes in the other browser window in real time. That is, changes made in one browser instantly appear in the other as you type them.

This functionality allows multiple authors to edit a document and see each others changes as they happen. In addition, the document can be instantly published to the web, and be configured to automatically be republished when changes are made.

Compare this with the old model, where changes did not appear until the next printed release or until the revised files were uploaded to a website.

The question “where is the document?” has become as meaningless as “where is four?” Documents like these no longer exist in a single location but in every location. They have become as ubiquitous as concepts, philosophy, and gravity, not enclosed in a physical location but rather a metaphysical one.

Now some communicators proclaim: “information wants to be free”. Information cannot “want’ anything – it has no personality but that which we ascribe to it.

Communicators create and manage information – we control it. It is not that “information wants to be free” – it is that we can, and must, free it from its prison of physicality and non-universal accessibility.

Shared, web-based workspaces are a good place to begin the liberation.

The Mother of all Confirmation Messages

See the source imageMost technical communicators who work in software will, at some point, be asked to write (or re-write) error and confirmation messages. This is often a very challenging but engaging activity. You have to consider the state of mind of the user who may be annoyed, upset or confused at seeing such a message. A well-written message, therefore, puts the user’s mind at ease by explaining exactly what the problem is and how to resolve it.

Some examples of poorly written and well-written messages help illustrate this:

Poorly-written: Printing device out of media. (Error 34)

Well-written: Your printer is out of paper. Please add paper to the lower tray.

* * *

Poorly-written: Data type mismatch in field 23 – invalid alpha/digit entry. Message class AB43. [INTERNAL NOTE – TELL CUSTOMER HE SHOULD NOT BE SO *$*&%$ing STUPID!!! Homer Smith, Developer A41, Sector 7G]

Well-written message: You have entered numbers into the First Name field: please enter letters only.

* * *

Poorly-written: Illegal access attempt – type A342. DO NOT OVER-NEGATE  SUB-CONNECTION. MESSAGE TYPE – DFYWKJ3940983- FAILURE OVERRIDE. Please refer to subtype 5908DM4M67M4454 when quoting this message to your CIO-DM4 manager. (Form 12 is required, of course!) Have a day.

Well-written: You do not have permission to access the record. Please contact the Help desk.

You get the idea…

Recently, Google developed a message for anyone trying to import their Google Gmail contacts into Facebook. Google wanted to warn the user that they cannot export their contact information out of Facebook.

Here is the actual message users will see: (trust me, I am not making this up)

Hold on a second. Are you super sure you want to import your contact information for your friends into a service that won’t let you get it out?

Here’s the not-so-fine print. You have been directed to this page from a site that doesn’t allow you to re-export your data to other services, essentially locking up your contact data about your friends. So once you import your data there, you won’t be able to get it out. We think this is an important thing for you to know before you import your data there. Although we strongly disagree with this data protectionism, the choice is yours. Because, after all, you should have control over your data.

Of course, you are always free to download your contacts using the export feature in Google Contacts.

This public service announcement is brought to you on behalf of your friends in Google Contacts.

__I want to be able to export my data from Facebook. Please register a complaint on my behalf over data protectionism. (Google will not pass on your name or email address.)

__I still want to proceed with exporting this data. I recognize that I won’t be able to export it back out.

[Select one or more options.] [Cancel and go back]

Oh. My. God. Could Google have used more words? This is a terrible message which sends a terrible message. Because of the obvious conflict-of-interest, Google is doing everything it can to scare the user into not proceeding.

It is also ridiculous (not to mention very confusing) to have one of the options be to “register a complaint on my behalf”, which is totally irrelevant to what the user’s intention was. It would be like a Print dialog with the following options:

[Print the document]

[Do not print the document. I do not want to wilfully participate in the destruction of trees. Please automatically email all my contacts to let them know how much I love this planet.]

Even if you think Google should offer some sort of warning, it could have been done much simpler, like this:

Export my Gmail contact information into Facebook? (Note that you cannot export your contact information out of Facebook.)

[Yes] [No]

Software messages must be non-political, non-religious and uncontroversial.

I am “super sure” of that.

Resolve this

Image result for happy new yearMy new year’s resolutions all involve documentation, of course.

The Paper Chase

My first resolution is to organize all the various printed guides, warranties, and other paper documents that have accumulated over the years and randomly spread themselves into various piles throughout my home.

I will review each and every paper item and discard what I don’t need. (I hate paper and wish we lived in a paper-free Star Trek world.) The relevant leftovers will be grouped and placed into large envelopes and stored alphabetically in a box.

My extensive printed documentation collection includes the following:

  • big electronics – TVs, Blu-Ray and DVD disc players, CD player, home theatre and satellite receiver, gaming unit
  • little electronics – MP3 players, cameras, phones, remotes, clocks, shavers, hardware tools, watches, electric toothbrush, organic mind reader
  • main computer items – user guides, and guides for the motherboard, DVD burner, RAM
  • peripheral computer items – mouse, monitor, keyboard, speakers, scanner, Webcam, backup drive, software documentation, USB powered teleporter
  • kitchen appliances – fridge, stove, microwave, dishwasher, blender, toaster oven, indoor spit
  • garage items – snowblower, lawnmower, trimmer, BBQ, Ferrari guide
  • miscellaneous items – washer and dryer, vacuum cleaners, non-electric items such as board games, hot water heater, humidifier, kitchen faucet, Sherman tank

(God, I have a lot of crap.)

Soft Sell

My second resolution is to conduct a complete audit of all the soft documents on my computer and again, get rid of what I don’t need and keep the good stuff. There’s many documents that are several years old that I never read and know I’ll never need. Other documents need to be rewritten, merged or reclassified.

Onward and Online

My final resolution, a continuation of the second, is to move as many of my files online as possible. As long as the document does not contain sensitive or critical financial information (like my Swiss bank account number and Tiger Woods’ cell phone number), I will move it to Google docs.

In addition to textual documents, my most precious files are my photographs. Before the era of digital photography, people took pictures with something called a film camera, which produced something called prints. I have hundreds of these prints in special books called photo albums. They are single copies only – there is no backup. My long term goal, therefore, is to scan every one of these photographs and upload them to private albums on Flickr.

Managing Catastrophe

I have heard of too many cases where hard drives have failed and people have lost all their files. Backups help with this problem, but if your house burns down or is burglarized, they have no value. The ideal state to be in if you lost your hard drive for any reason would be that you simply buy another computer, connect to the Internet, and access all your files.

Confidential files should be whittled down to a size that can fit on a USB key. That key should then be kept at a location away from your computer. Alternatively, you can use an online backup site. ADrive, for example, gives you 50 GB of free online storage.

Is this ringing any (alarm) bells?

If any of these documentation issues sound familiar (a plethora of printed docs, unorganized soft docs, and lack of an off-site backup for your documents and photos), welcome to the club. Most people simply don’t make the effort to deal with these ongoing doc issues.

However, we technical communicators are not most people – we are the Communicati – the enlightened communication and documentation high priests. If we fail to maintain our own documentation, what chance do normal folk have?

Catch the Wave

Image result for WaveOutdated is a word coined by manufacturers to convince people the shiny new products they purchased six months ago and which work perfectly are now useless. However, once in a while, a new product comes along that really does make the current version practically obsolete. Google Wave could be just such an application.

Google Wave is difficult program to describe, but is essentially a cutting edge communication application that’s a combination of email, instant messaging and collaborative editing. Because Google Wave is so different than anything before it, the best way to learn about it is to watch the long video here. The next best way is to finish reading this article.

New Wave Rocks

Google Wave is the name of the latest application developed by Google. Within it you create documents called, appropriately enough, Waves. Waves are XML-based document objects similar to an email thread, but so much more. Instead of writing and sending an email, you create a Wave and then share it with others.

Google Wave was created because email as we know it was developed long before the Internet, the World Wide Web, rich content and multimedia. Traditional email is like putting horseshoes on a Ferrari – painful.

Creature Features
Here are the main features of Google Wave that make it light-years beyond regular email:

  • when you type a message, other users see your keystrokes in real-time, character by character; no more “Amy is typing…” messages to wait through, although you can turn off this feature if you wish
  • instant and intelligent spellcheck: for example, “It’s bean so long” is automatically corrected to “It’s been so long”; “icland is an icland” is automatically changed to “Iceland is an island”; these changes are either instantly made, or suggestions are automatically presented in a drop-down list below the word in question
  • you can view the history of a message thread using a “playback” feature – this allows you to step through each response as it was received, one message at a time, so you can see who wrote what and when they wrote it
  • multiple users can update the original message – all users will see each other’s changes in real time as they are typed, in other words, real-time live document colloboration
  • a built-in search function – you can search sites, images, videos, and then with one click instantly add the link or photo to your message
  • you can easily respond to just a portion of a section in the message, instead of the entire message; new threads are automatically created
  • you can easily drag photos onto your message, and rename them, again in real time
  • automatic recognition of URLs: if you enter, it is instantly converted to a hyperlink
  • you can easily embed videos

Extending a Hand

You can also extend Google Wave by creating extensions for other applications and websites. For example, you can:

  • add a Wave to to a blog – updates to the Wave instantly appear in the blog, and vice versa, in real time
  • add Twitter to a Wave – the Twitter thread appears in Wave – updates to one appear in the other
  • embed various apps, such as a chess game
  • create your own “branded” Wave; for example the ABC Company could create a Wave that appears as an ABC Wave, with all of the Google Wave’s functionality
  • add a “response” gadget – a table with multiple columns: each column represents a response to a question, for example: Do you like cheese? – Yes | No | Maybe; when you respond, your ID appears under the column of that response; to change your response, you simply click another column and your ID instantly moves to that column
  • insert a map into a Wave – if one reader zooms in or out, or annotates the map with markup tools, the other users will instantly see the new view or the changes
  • add a form: for example, multiple users can collaborate in real time on the construction of a poll; you can be writing the questions while another user writes the potential responses; you can then can instantly send out the poll to all the recipients, and the poll results are updated live in real-time

To Infinity and Beyond…

These features are indeed incredible. But perhaps the most outstanding feature of all is the one demonstrated near the end of the video: real time translation to another language. Using a special translation add-on, you can type in one language and an instant, real-time, word by word translation appears in another language.

When new technology like this comes along, I’m always reminded of two of Arthur C. Clarke’s “Three Laws”:

  • The only way of discovering the limits of the possible is to venture a little way past them into the impossible.
  • Any sufficiently advanced technology is indistinguishable from magic.

On the first law: Only by hiring the best and brightest engineers could Google create such an application. But technical intelligence only gets you so far; you have to be a dreamer, a doubter and a rebel. You must believe in the impossible to do the possible.

On the second law: Google Wave certainly does appear “magical”. But we have to be careful not to be overwhelmed by the magic. Just because a new product can be used in new and different ways does not necessarily make it more “usable”. I’m sure many of us could personally could benefit from such a tool, but we are hyper-combinations of communicators and engineers. Many people might balk at such a complex application. Just because something may be “better” doesn’t mean people will use it. History is filled with “better” products that failed for other reasons: price, usability, inability of people to change – the Apple Newton and WebTV are but two examples; you can view more here.

The Wave is scheduled to be released either late 2009 or early 2010. It will be fascinating to see if it succeeds, because it could impact our profession. Think about it: XML-based; collaborative editing; ability to track changes; instant communication – are these not the ideals of technical communication? If the Wave takes off, it could inspire a whole new generation of people to become technical communicators.

And what a Wave that would be…