The Computers Are Getting Better at Writing

• gpt-3-experiments

  6 709 0.0 Python

  Test prompts for OpenAI's GPT-3 API and the resulting AI-generated texts.

See also my experiments with GPT-3 on sane prompts, which have wildly varying quality even after generating them in bulk: https://github.com/minimaxir/gpt-3-experiments

Creative writing hasn't been one of the super-hyped use cases by OpenAI for the OpenAI API outside of AI Dungeon, surprisingly. For just random generation, the necessary curation can detract from the time-savings advantages. (as an aside, the API is also extremely expensive for long-form content to the point I'm not sure how the economics work for these startups even with charging monthly fees).

I'm more bullish on small bespoke models for a given use case, which is what I spend my time researching.

• languagetool

  310 11,543 10.0 Java

  Style and Grammar Checker for 25+ Languages

  

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• vim-LanguageTool

  6 274 0.0 Vim Script

  A vim plugin for the LanguageTool grammar checker

Yes. You can build the command-line application Java Jar from that repo. I also combine it with vim (https://github.com/dpelle/vim-LanguageTool).

• Gleemin

  4 86 0.0 Prolog

  A Magic: the Gathering™ expert system

Representing costs in a meaningful manner is a constant problem in every M:tG generator I've seen.

The problems I highlight above are not with grammaticality, which is certainly a big step forward with respect to the past. But many of the abilities still don't make a lot of sense, or don't make sense to be on the same card, or have weird costs etc.

My intuition is that it would take a lot more than language modelling to generate M:tG cards that make enough sense that it's more fun to generate them than create them yourself. I think it would be necessary to have background knowledge of the game, at least its rules, if not some concept of a metagame.

Also, I note that the new online version of the game is capable of parsing cads as scripts in a programming language using a hand-crafted grammar rather than a machine-learned model [4] [5]. So it seems to me that the state-of-the-art for M:tG language modelling is still a hand-crafted grammar.

__________________

[1] https://github.com/stassa/Gleemin - unfortunately, doesn't run anymore after multiple changes to Prolog interepreters used to create and then port the project over.

[2] https://github.com/stassa/THELEMA - should work with older versions of Swi-Prolog, unfortunately not documented in the README.

[3] https://link.springer.com/article/10.1007/s10994-020-05945-w - see Section 3.3 "Experiment 3: M:tG fragment".

[4] https://www.reddit.com/r/magicTCG/comments/74hw1z/magic_aren...

[5] https://www.reddit.com/r/magicTCG/comments/9kxid9/mtgadisper...

• THELEMA

  1 13 0.0 Prolog

  My MSc thesis: a grammar induction system

Representing costs in a meaningful manner is a constant problem in every M:tG generator I've seen.

The problems I highlight above are not with grammaticality, which is certainly a big step forward with respect to the past. But many of the abilities still don't make a lot of sense, or don't make sense to be on the same card, or have weird costs etc.

My intuition is that it would take a lot more than language modelling to generate M:tG cards that make enough sense that it's more fun to generate them than create them yourself. I think it would be necessary to have background knowledge of the game, at least its rules, if not some concept of a metagame.

Also, I note that the new online version of the game is capable of parsing cads as scripts in a programming language using a hand-crafted grammar rather than a machine-learned model [4] [5]. So it seems to me that the state-of-the-art for M:tG language modelling is still a hand-crafted grammar.

__________________

[1] https://github.com/stassa/Gleemin - unfortunately, doesn't run anymore after multiple changes to Prolog interepreters used to create and then port the project over.

[2] https://github.com/stassa/THELEMA - should work with older versions of Swi-Prolog, unfortunately not documented in the README.

[3] https://link.springer.com/article/10.1007/s10994-020-05945-w - see Section 3.3 "Experiment 3: M:tG fragment".

[4] https://www.reddit.com/r/magicTCG/comments/74hw1z/magic_aren...

[5] https://www.reddit.com/r/magicTCG/comments/9kxid9/mtgadisper...

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

Suggest a related project