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I'm happy to share that today we are releasing the Mockingbird LLM.

At <10B parameters it's an LLM trained to provide optimal results for RAG and structured outputs. Although significantly smaller (and thus faster) than GPT-4 or Gemini-1.5 Pro, it performs at a comparable level for generation, citations, and structured outputs.


I think in addition to all the benchmarks used right now for LLM evaluation (HumanEval and the like). It would be interesting to have a 'hallucination benchmark' with a summarization based hallucination dataset.


Google did something similar in 2017 (although it's overlaying your WHOLE FACE) on the headset and only when viewed through a camera: https://blog.google/products/google-ar-vr/google-research-an...


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