The dawn of the augmented writing era – Textio Word Nerd

Product genius @jensenharris @textio writes how machine learning is fundamental to writing.

  • It has the potential to be a fundamental breakthrough in human communication.Surprisingly, because of the slow pace of innovation in writing software, augmented writing is really only the third disruption in nearly half a century of computer-assisted writing.Let’s take a brief trip down memory lane.A brief history of writing softwareThe text mode eraThough there was once something sold called a “word processing machine” (basically a glorified typewriter with a small screen so that you didn’t have to use as much gunky Liquid Paper to correct mistakes), the true beginning of mass market word processing started with the advent of IBM’s personal computer and the subsequent PC revolution.The IBM Personal Computer.
  • The idea was that you could see on the screen exactly what a document would look like when it was printed.Microsoft had a purpose-built applications team founded with the mission to build great WYSIWYG word processing software, and they were quick to market with a little product called Microsoft Word that took full advantage of this new technology.Microsoft Word let everyone create garish documents with just the click of a button!For the first time, the printed page was right there on the screen!
  • Once people had Word, they never ever wanted to go back.WordPerfect didn’t have WYSIWYG in their blood… the team and software hadn’t been purpose-built for the graphical era.
  • Even Quip, the biggest writing exit of the last few years, is fully of this collaborative era.The missing linkSo we’ve seen writing software evolve from text mode through WYSIWYG editing to today’s focus on collaborative editing.What does all the software from all of these eras have in common?It doesn’t make your writing better.There are features galore to decorate text… to make it red and bold, or to encapsulate it in fancy bulleted lists or surround it with ornate borders.
  • There are features to quickly get back to earlier revisions of your document.But these products miss the highest, most important potential of writing software — the capability to make the human a more successful writer.The augmented writing eraAnd so now, we stand at the precipice of the next era of writing software — the era of augmented writing.Each era in writing software was fueled by a disruptive technology that changed people’s expectations of what writing software was capable ofThe rise of machine intelligenceAugmented writing builds on an incredibly disruptive technology: machine intelligence.The core tech now exists to be able to quantitatively predict with a high degree of accuracy whether a document or email you’re writing will get the outcome you want.This predictive power is paired with a new kind of writing user interface which x-rays your document in real-time.

Humans have long imagined language superpowers. Imagine if you could know — in advance — exactly how other people would react to your words. This is augmented writing, and it’s here already.
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A Development Methodology for Deep Learning – Medium

A Development Methodology for #DeepLearning.  #BigData #MachineLearning #DataScience #AI

  • The machine learning convention has been to create a training set, a validation set and a test set.
  • Although Deep Learning is built from software it is a different kind of software and a different kind of methodology is needed.
  • The observations that differs from conventional machine learning is that Deep Learning has more flexibility in that a developer has the additional options of employing either a bigger model or using more data.
  • The methodology addresses the necessary interplay of the need for more training data and the exploration of alternative Deep Learning patterns that drive the discovery of an effective architecture.
  • Deep Learning differs most from traditional software development in that a substantial portion of the process involves the machine learning how to achieve objectives.

The practice of software development has created development methodologies such agile development and lean methodology to tackle the…
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Common Sense in Artificial Intelligence… by 2026?

Common Sense in #ArtificialIntelligence… by 2026?  by @lemire

  • To replace human beings at most jobs, machines need to exhibit what we intuitively call “common sense”.
  • For example, many human beings are illiterate and they can be said to have common sense.
  • Common sense is basic knowledge about how the world of human beings works.
  • For example, if you are lying on the floor yelling “I’m hurt”, common sense dictates that we call emergency services… but it is possible that Apple’s Siri could already be able to do this.
  • If computers could be granted a generous measure of common sense, many believe that they could make better employees than human beings.

Read the full article, click here.

@kdnuggets: “Common Sense in #ArtificialIntelligence… by 2026? by @lemire”

An insightful opinion piece on the future of common sense in AI. A recommended read by an authority in the field.

Common Sense in Artificial Intelligence… by 2026?