Taranjeet(@taranjeetio)
This is what token-efficient memory looks like @mem0ai You can now run agent memory that is cost-e...
5.5内容质量
TL;DR · AI 摘要
mem0ai 开源了一种 token 高效的记忆算法，在保持准确率的同时将每查询 token 消耗降至约7000，显著低于行业平均25000+。
核心要点
- 新算法在 LoCoMo、LongMemEval 和 BEAM 基准上达到有竞争力的准确率
- 每查询仅需约7000 tokens，比主流系统节省3-4倍
- 项目已完全开源，定位为AI智能体的记忆层
#AI Agent#Memory System#Token Efficiency#Open Source
打开原文You can now run agent memory that is cost-efficient at production scale without sacrificing quality.
Open source" / X
Taranjeet on X: "This is what token-efficient memory looks like @mem0ai You can now run agent memory that is cost-efficient at production scale without sacrificing quality. Open source" / X
Don’t miss what’s happening
Taranjeet 
This is what token-efficient memory looks like
You can now run agent memory that is cost-efficient at production scale without sacrificing quality. Open source
Quote
mem0
@mem0ai
·
Apr 16
Article
How We Built the Token-Efficient Memory Algorithm
New @mem0ai memory algorithm hits competitive accuracy across LoCoMo, LongMemEval, and BEAM at <7,000 tokens/query (≈3–4x fewer tokens), while most systems run at 25,000+. Fully open source. We...
·
3
2
20
5