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In this video, the speaker admits a minor error in the code used to solve the game Wordle, which had little effect on the results, and provides information on how color is assigned to letters when there are repeated characters in the guess. The best possible opening guess for the game is revealed to be "soare" after weighting all possible patterns, followed by "slane." However, as humans play the game differently, this information is only useful if someone has memorized the word list and will not largely impact gameplay. The speaker discusses the joy of writing algorithms for word games like Wordle and how that contributes to improving skills needed to create more meaningful algorithms for other purposes.
In this section, the speaker admits to a minor mistake in the code used to solve Wordle, which had a negligible effect on the overall results. He explains how color is assigned to letters when there are repeated letters in the guess, and how he unintentionally deviated from Wordle conventions in some edge cases. The speaker also clarifies that the best opener for the game Wordle is actually not "crane", as he initially claimed in his previous video, due to a slight change in the code. He admits that the point of his video is not to find the best possible solution for an online game, but rather to provide an information theory lesson in an engaging and relevant context. The speaker goes on to explain how he derived the optimal opening guess by using the official list of possible Wordle answers, and discusses the trade-off between resilience and building something that is overfit to a test set.
In this section, we learn about the optimal opening guess for the Wordle game. By taking a weighted average of all the patterns that appear, the best possible word to start with is "soare", which is followed by "slane" with a deeper analysis of the next possible steps. However, in reality, humans play the game differently, and this analysis is only useful if someone has memorized the word list, which is subject to change. Ultimately, players rely on intuition and pattern recognition. While the information about the optimal opening guess may be interesting, it is not necessary for enjoying the game.
In this section, the speaker discusses the joy of writing algorithms to try to play games and how it differs from playing games as a human. They explain that the point of writing algorithms for word games like Wordle is not to impact how the game is played, but rather to improve the skills needed to create more meaningful algorithms for other purposes.
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