| 1. | | LLM Inference Endpoint Performance Benchmarking Tool (github.com/ray-project) |
| 4 points by richardliaw on Nov 1, 2023 | past |
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| 2. | | A comprehensive guide to building RAG-based LLM applications for production (github.com/ray-project) |
| 3 points by richardliaw on Oct 25, 2023 | past |
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| 3. | | Ray – an open source project for scaling AI workloads (github.com/ray-project) |
| 2 points by richardliaw on Aug 11, 2023 | past |
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| 4. | | Continuous batching enables 23x throughput in LLM inference (anyscale.com) |
| 2 points by richardliaw on June 23, 2023 | past |
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| 5. | | Anyscale's Aviary is a dashboard for evaluating Open Source LLMs (anyscale.com) |
| 14 points by richardliaw on May 31, 2023 | past | 3 comments |
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| 6. | | Numbers every LLM developer should know (github.com/ray-project) |
| 428 points by richardliaw on May 17, 2023 | past | 103 comments |
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| 7. | | How to build a LLM search engine using a self-hosted LLM (anyscale.com) |
| 3 points by richardliaw on April 21, 2023 | past |
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| 8. | | Ray is the next generation ML framework (super.site) |
| 5 points by richardliaw on Jan 12, 2023 | past | 1 comment |
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| 9. | | Anyscale raises $40M Series B to revolutionize serverless computing (techcrunch.com) |
| 20 points by richardliaw on Oct 21, 2020 | past |
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| 10. | | Cloud Computing in Python for all major clouds (medium.com/distributed-computing-with-ra...) |
| 1 point by richardliaw on May 22, 2020 | past |
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| 11. | | Large Scale Training at Berkeley AI Research (bair.berkeley.edu) |
| 2 points by richardliaw on Jan 16, 2020 | past |
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| 12. | | Ray (from UC Berkeley), for the Curious (medium.com/distributed-computing-with-ra...) |
| 1 point by richardliaw on Jan 10, 2020 | past |
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| 13. | | Ray for the Curious (medium.com/distributed-computing-with-ra...) |
| 1 point by richardliaw on Jan 6, 2020 | past |
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| 14. | | Tune: A scalable framework for hyperparameter tuning from UC Berkeley (medium.com/riselab) |
| 5 points by richardliaw on Aug 28, 2019 | past |
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