Episode 2 of 40
Welcome back to your role as ๐๐๐ ๐ผ๐๐๐๐๐๐ฃ๐ฉ๐๐ก ๐ผ๐ ๐ฟ๐๐ง๐๐๐ฉ๐ค๐ง. Our digital intern knows how to spot patterns, but how do they actually write entire emails and reports? ๐ข
It all comes down to that massive stack of files they are carrying in our trailer image. ๐
Think about how my two year old daughter plays the “dropping the spoon” game from her high chair. ๐ฅ
When she lets go of the spoon, she immediately looks down at the floor. She has not studied the complex laws of physics. ๐
She just knows from past experience that the action of “dropping” is always followed by the outcome of “hitting the floor.” ๐ฅ
Your digital intern does the exact same thing, just on a massive scale. It read every single document in that giant stack of files it is carrying. ๐
If you ask it to “Write a polite email delaying a project,” it does not actually understand what a project is, or what it means to be polite. โณ
It just knows that in its stack of files, the word “Due” is almost always followed by “to,” then “unforeseen,” then “circumstances.” It drops those words in a perfect sequence, one after another. ๐งฉ
It is not just autocompleting a single word – it is predicting entire paragraphs based on the patterns it memorized! ๐ช
In the tech world, that giant stack of files is called the ๐๐ง๐๐๐ฃ๐๐ฃ๐ ๐ฟ๐๐ฉ๐, and the system guessing the next word is called a ๐๐๐ง๐๐ ๐๐๐ฃ๐๐ช๐๐๐ ๐๐ค๐๐๐ก (๐๐๐). ๐ป
What is a repetitive email or document you wish you could hand off to an intern to “autocomplete” for you? Drop it in the comments! ๐
Directorโs Quick Brief
Key Concept
Large Language Models (Next Word Prediction)
Simple Definition
A Large Language Model generates text by predicting the most likely next word based on patterns it learned from massive amounts of written data.
Real-world Example
When Gmail suggests the rest of your sentence while writing an email, it is predicting the next word based on patterns learned from millions of similar emails.
Playbook Progress
Season 1 – Raising the Intern
Episode 2 of 7