But that’s unironically a good idea so I decided to try and do it anyways. With the use of agents, I am now developing rustlearn (extreme placeholder name), a Rust crate that implements not only the fast implementations of the standard machine learning algorithms such as logistic regression and k-means clustering, but also includes the fast implementations of the algorithms above: the same three step pipeline I describe above still works even with the more simple algorithms to beat scikit-learn’s implementations. This crate can therefore receive Python bindings and even expand to the Web/JavaScript and beyond. This also gives me the oppertunity to add quality-of-life features to resolve grievances I’ve had to work around as a data scientist, such as model serialization and native integration with pandas/polars DataFrames. I hope this use case is considered to be more practical and complex than making a ball physics terminal app.
They used AI to create actors who don't exist based on a screenplay from a writer. They asked it to generate an image of the "actors" - recording their voice and then feeding the image back to the AI tool, asking it to create a fitting voice.
Much of this is powered by a powerful custom conditional language that we created. Designers use this language throughout the game’s systems to configure when and how different parts of the game should change based on player actions that flow through the backend services. This includes the entirety of the game’s quest progression system, defining what actions the player needs to take to progress through the campaign.。业内人士推荐夫子作为进阶阅读
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