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# Introducing Lamini Memory Tuning: 95% LLM Accuracy, 10x Fewer Hallucinations

**[Hacker News](https://daily.dev/sources/hn)** · 7 min read · 43 upvotes · 1 comments

## Summary

Introducing Lamini Memory Tuning, a new approach to embedding facts into LLMs that improves factual accuracy and reduces hallucinations. Lamini Memory Tuning achieves 95% accuracy compared to 50% with other approaches, and reduces hallucinations from 50% to 5%. It overcomes the challenge of achieving precise factual accuracy while maintaining generalization capabilities. The method involves tuning millions of expert adapters with precise facts on top of open-source LLMs, resulting in high accuracy, high speed, and low cost.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.lamini.ai/blog/lamini-memory-tuning>

## Community discussion

Top comments from developers on daily.dev.

**@mattybilly** · 2 upvotes

> I would love to see this implemented and open-sourced. Imagine being able to see some ablation studies like removing some of the roughly ~1 million experts their setup uses and seeing how that affects memory. Or maybe see how the logprobs change for both memory based facts and creative reasoning problems as the number of experts increases/decreases.

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---

Tags: [#ai](https://daily.dev/tags/ai), [#llm](https://daily.dev/tags/llm)

[View this post on daily.dev](https://daily.dev/posts/introducing-lamini-memory-tuning-95-llm-accuracy-10x-fewer-hallucinations-u4c12aa1h)

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