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justinowingson Copy/paste text to highlight AI writing patterns like "It's not X. It's Y"

Here's an example of text that has many of the Lady Doth Protest patterns:

from:

https://www.fullstory.com/blog/whats-slowing-ai-down-enginee...

justinowingson Copy/paste text to highlight AI writing patterns like "It's not X. It's Y"

The words are associated with overemphasizing a point. Of those, I'd guess "just" and "only" trigger the most, and they'll often be embedded in NXY patterns.

The tool calls these "Lady doth protest:"

>Lady doth protest >The full quote from Shakespeare's Hamlet is "The lady doth protest too much, methinks." When you want to make a point, make the point. Extra words of enthusiasm, usually in the form of adverbs, can often be deleted to make writing stronger. Lady Doth Protest looks for words like "just," "truly," "really," "fully," etc. Remember what Ronald Reagan said, "If you're explaining, you're losing."

justinowingson Copy/paste text to highlight AI writing patterns like "It's not X. It's Y"

That's a good idea. Thanks!

justinowingson Copy/paste text to highlight AI writing patterns like "It's not X. It's Y"

Rather than giving an ambiguous score (or grade) regarding if something is written by AI/ChatGPT/Claude etc., Un•AI•ify works like the popular HemingwayApp:

1. paste in text

2. tool looks for overused patterns in AI-writing

3. gives a "rhetorical score"

Patterns include negation/affirmation ("It's not X. It's Y"), using words like only, just, really, truly, fully, etc., buzzwords, cliches, triads, and ...

The ubiquitous em dashes.

If you want a fun test, grab the blog post by the Jasper CMO, and drop it in:

https://www.jasper.ai/blog/context-ultimate-differentiator-a...

here's the analysis:

https://unaiify.com/un/qS05YRBY

justinowingson The hope and hype of IoT: "`Things` turned abstract, even absurd."

Reflection on the evolution of IOT into "connected products" by Steve Latham, founder/veteran/product leader who helped NCR build Redbox competitor (Blockbuster Express) and went on to found a remote device management consultancy (Banyan Hills) and ultimately develop software to help connected product teams monitor+manage remote device systmes or "connected products" (kiosks, signage, access control, POS, cameras, etc.)

justinowingson Remote device downtime causes for kiosks, lockers, cameras based on 200K tickets

New research into 200K tickets across 100K remote devices/connected products (eg smart lockers, self-checkout kiosks, camera systems) revealed the top causes of downtime:

• 18.1% configuration issue (majority = wrong device settings)

• 14.5% network issue (half of these loss of service)

• 11.8% software problem (e.g. free/crash, disk space full)

• 10.9% power issue (most of these are loss of power)

• 10.6% OS issue (half are configuration related)

TL;DR: most common device downtime issues can be resolved with remote device management software — so long as the software is able to connect to the holistic connected product (must be more capable than traditional RMM/UEM software used for IT devices or mobile device management).

The report also shares remote resolution paths and odds of success for each (e.g. loss of power = near-zero odds of success; whereas a disk space issue can be resolved automatically using remote monitoring/management software)

Research is from goCanopy.com