Time to Guess! (+ Reflections on the Results)
The time has come to make your guess! How close will you get??
Answer the questionnaire below to make your guess. After you submit your guess, the answer will be revealed, along with some reflections on the purpose of this activity.
When playing the guessing game, please remember to keep things fair and do not attempt to find the original, "uncensored" text on the internet. You should also generally avoid googling for anything that would give away the answer. If you coincidentally already know the original blog post (and therefore have had the answer "spoiled"), please abstain from the game by entering "I already know the original blog post" in the answer box.
One exception to the "no googling" rule: if you think you know what specific NLP algorithm the blog post was about, but you just don't know what year that algorithm was invented, you are allowed to look that up. For example, if you already think the blog post is about Markov Chains, you are allowed to search for something like "what year was the Markov Chain invented".
-
BTW, the fact that we used Markov Chains for that hypothetical example should clue you in that the answer to the guessing game is not "Markov Chain" :)
Make Your Guess!
The Answer Revealed!
-
Drumroll please!
And the answer is...the blog post was written in 2015!
Aw man, I was way off...I guessed that it was, like, 2022, closer to the ChatGPT era.
Really? I guessed, like, 1990. The quality of the generated text is way too poor to even be first-generation GPT.
-
Actually, you'd be surprised at that last part—first-generation GPT was pretty bad, and was more similar in quality to the model this blog post talks about than to modern GPTs.
-
Speaking of which, we should actually reveal what model this blog post was about...
The blog post was specifically about a model called Recurrent Neural Networks, or RNNs. We won't learn about RNNs specifically in this class, but (when applied to text, as done in this blog post) they belong to a broad family of models known as language models, which we will be spending quite a bit of time on.
For those who are curious, the original blog post was "The Unreasonable Effectiveness of Recurrent Neural Networks" by Andrej Karpathy.
-
Some of you may be more familiar with Andrej Karpathy as one of the founders of OpenAI. But this blog post was written back when he was a grad student.
-
Another fun fact: the blog post's title is, presumably, a reference to an older lecture called "The Unreasonable Effectiveness of Mathematics in the Natural Sciences.
(When logged in, completion status appears here.)