NLP inside your database - Query OpenAI’s GPT-3 from directly inside your database

@katherine_velasquez thank you!

@katherine_velasquez thank you!

@katherine_velasquez Thank you!

@katherine_velasquez thank you!!!

@katherine_velasquez Thanks for all the love and support.

@shubham_pratap Thanks Shubham for the support.

@shubham_pratap Thank you!

@shubham_pratap thanks

@shubham_pratap Thanks a lot.

@juanes_velasquez Thanks Juanes!

@juanes_velasquez Thank you!

@juanes_velasquez Thank you!

@juanes_velasquez thanks!

@juanes_velasquez Thank you.

@steevep Thank you.

@adam_carrigan @steevep thank you

@steevep We would love to hear your feedback once you've tried it. Thanks for all the support.

@mariomoscatiello yeah! Simplifying the ML pipeline is one of the best ways to democratize it!

@mariomoscatiello thank you

@mariomoscatiello thank you! we agree!!!

@mariomoscatiello We are glad to help our users in simplifying their data stack.

@realmaxrush Thanks, Max, would love to hear about how you use MindsDB. Always LOVE hearing a new use case.

@realmaxrush Thank you!

@realmaxrush thanks

@realmaxrush We would love if you could try the product and let us know what you think.

@kovid_batra Feel free to join our community for discussions and support! https://mindsdb.com/joincommunity

@kovid_batra Great, thank you!

@kovid_batra great. Thanks!

@kovid_batra Do let us know about your experience.

@usamaejaz thank you!! join our community on slack, we would be looking forward to hear about your discoveries.

@usamaejaz Thank you!

@usamaejaz Thanks!

@usamaejaz Thanks a lot. MindsDB community will always be there to help you in your ML journey.

@david_cardozo1 We are constantly integrating and receiving contributions for new integrations, if you are a developer I encourage you to create an integration (or many!) https://docs.mindsdb.com/contrib...

@david_cardozo1 Hey David! Thanks for your kind words. Here's a sheet that compares the default AutoML engine with other alternatives via the OpenML AutoML benchmarking suite: https://docs.google.com/spreadsh.... Hope it helps establish a rough idea on its performance! It's pretty old but we have a release procedure that helps us keep the accuracy, at the very least, so it should set a lower bound on what you should see for tabular regression and classification tasks.

@david_cardozo1 thanks

@david_cardozo1 THANK YOU! Firestore would be a great addition, lets chat about building one.

@david_cardozo1 MindsDB is constantly working on new integrations. You can easily open a Feature Request asking for the same and can even try writing the integration yourself if you want to. MindsDB does provide performance benchmarks for their battery-included models, which are available on their website. These benchmarks show the accuracy and speed of their models on a variety of datasets and tasks. Additionally, MindsDB's AutoML capabilities allow users to train custom models that can outperform the battery-included models for specific use cases. Overall, it's important to keep in mind that the performance of MindsDB's models will depend on many factors, including the size and complexity of the data, the type of task, and the computational resources available.

@new_user_18120229380de99ff Thank you

@new_user_18120229380de99ff Thank you!

@new_user_18120229380de99ff thanks!

@new_user_18120229380de99ff Thanks for the support.