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Update README to make more sense for external users.

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  1. README.md +21 -6
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@@ -7,14 +7,21 @@ sdk: docker
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  app_port: 7860
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  ---
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- # LynxKite 2024
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- This is an experimental rewrite of [LynxKite](https://github.com/lynxkite/lynxkite). It is not compatible with the
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- original LynxKite. The primary goals of this rewrite are:
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- - Target GPU clusters instead of Hadoop clusters. We use Python instead of Scala, RAPIDS instead of Apache Spark.
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- - More extensible backend. Make it easy to add new LynxKite boxes. Make it easy to use our frontend for other purposes,
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- configuring and executing other pipelines.
 
 
 
 
 
 
 
 
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  ## Structure
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@@ -65,3 +72,11 @@ To work on the documentation:
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  uv pip install mkdocs-material mkdocstrings[python]
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  mkdocs serve
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  ```
 
 
 
 
 
 
 
 
 
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  app_port: 7860
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+ # LynxKite 2000:MM
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+ LynxKite 2000:MM is a GPU-accelerated data science platform and a general tool for collaboratively edited workflows.
 
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+ Features include:
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+ - A web UI for building and executing data science workflows.
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+ - An extensive toolbox of graph analytics operations powered by NVIDIA RAPIDS (CUDA).
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+ - An integrated collaborative code editor makes it easy to add new operations.
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+ - An environment for visually designing neural network model architectures.
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+ - The infrastructure for easily creating other workflow design environments. See `lynxkite-pillow-example` for a simple example.
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+
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+ This is the next evolution of the classical [LynxKite](https://github.com/lynxkite/lynxkite).
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+ The two tools offer similar functionality, but are not compatible.
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+ Where classical LynxKite ran on Hadoop clusters, this version runs on GPU clusters.
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+ It targets CUDA instead of Apache Spark. It is much more extensible.
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  ## Structure
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  uv pip install mkdocs-material mkdocstrings[python]
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  mkdocs serve
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  ```
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+
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+ ## License
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+
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+ LynxKite 2000:MM is licensed under the GNU AGPLv3. See the [LICENSE](LICENSE) file for details.
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+
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+ [Lynx Analytics](https://www.lynxanalytics.com/) offers a commercial license of LynxKite 2000:MM
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+ that includes additional features and support. Get in touch if you are interested in life sciences tools
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+ and cluster deployment!