Last week, for the ARMA InfoCon conference, I created a timeline of recent generative AI events, so I thought I would share it here!

I was part of a terrific keynote last Tuesday titled Generative AI and Information Governance: The Good, The Bad, The Ugly. Stephen Goldstein, Director of Practice Support, Squire Patton Boggs and Lenora Gray, Data Scientist, Redgrave Data were panelists, along with me. Mike Quartararo, President of ACEDS was the moderator and “choreographer” of the music (he actually got the conference team to play the theme music from the movie The Good, the Bad and the Ugly as we walked out on stage).

Most of the keynote was terrific discussion between Mike and the panelists (with a few questions from the audience), but we did have a few slides. One of those was a slide I created to represent a timeline of recent generative AI events (20 events in total). I was pleased with how it turned out and thought it was reasonably informative, so I thought I would reformat it for the blog and show it here. Here is the timeline of recent generative AI events:

A few observations about the timeline:

• The events were solely selected by me, simply based on key events I thought were notable. I’m sure plenty of other events could be included in addition to (or replacement of) some of these events.
• The progression from GPT-1 (117 million parameters, released in February 2018) to GPT-4 (1.76 trillion parameters, released in March 2023) is astounding.
• March 2023 was a very busy month for Gen AI, with the release of GPT-4, Claude and Bard, Copilot announced, and plugin support made available for ChatGPT (which is an underrated milestone, IMO).
• Of course, since the session was about “the good, the bad and the ugly”, I had to include a few negative milestones as well, including OpenAI’s data breach, the libel case filed against them in Georgia, copyright lawsuits filed by Sarah Silverman and others, and the FTC opening an investigation into OpenAI. I left out the Avianca case because the presentation was to a largely records management-oriented audience.

So, what do you think? What’s missing from this timeline of recent generative AI events? Please share any comments you might have or if you’d like to know more about a particular topic.

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