Many LLM calls in Java apps are multiple choice. dukehoff-decide answers them with a small local model and returns a typed value with calibrated probabilities.
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Try itLarge language models remain far less efficient than biological brains at learning, representing knowledge, and planning, the post argues. A child hears roughly one token per second, reaching a billion tokens only after 31 years, while GPT-4-class models reportedly use four orders of magnitude more data. The Phi model series, trained on 10 trillion tokens, still trails GPT-4 along most axes. A Portia spider plans prey-catching behavior with a brain a million times smaller than a human's, and squirrels recall cached food after months, suggesting that existing models may be far less representationally and memory efficient.
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Run an LLM locally with Ollama. See how much memory you need, where LM Studio and llama.cpp fit, and how to call the model from code.
...explained visually (with tradeoffs in production).
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If you’ve been watching the tech sector and macroeconomic feeds over the last 48 hours, you’ve... Tagged with discuss, ai, webdev, programming.
The Netflix engineering team has developed an autonomous performance agent system. In this article, we’ll be learning more about it.
Not all my information is meant to reach OpenAI's servers
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