napsternxg

This is a very clean api and I really like the way you implemented it directly in Pandas. I worked on something similar 2 years back but the API was not as this one. Thanks a lot to making this.

We often ignore the importance of using good baseline systems and jump to the latest shiny thing.

I had a similar experience few years back when participating in a ML competitions [1,2] for detecting and typing phrases in a text. I submitted an approach based on Named Enttiy Recognition using Conditional Random Field (CRF) which has been quite robust and well known in the community and my solution beat most of tuned Deep learning solutions by quite a large margin [1].

I think a lot of folks underestimate the complexity of using some of these models (DL, LLM) and just throw them at the problem or don't compare it well against well established baselines.

[1] https://scholar.google.com/citations?view_op=view_citation&h... [2] https://scholar.google.com/citations?view_op=view_citation&h...

We also did something similar in our NTULM paper at Twitter https://youtu.be/BjAmQjs0sZk?si=PBQyEGBx1MSkeUpX

Used in non generative language models like BERT but should help with generative models as well.

Nice game, I like the idea of your, opponent and no turn. I made a similar game long time back (around 2014) also called Probabilistic Tic Tac Toe ( https://shubhanshu.com/PT3/ ), but my randomization rules were different. I used coin toss to decide on the move vetween two choices.

Old HN thread: https://news.ycombinator.com/item?id=12932183

Twitter thread from the author https://twitter.com/wkvong/status/1753132293491708027