Taranjeet

Taranjeet

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Pritam Kumar Manohari retweeted

Taranjeet

@taranjeetio

29 Apr 2025

Today, I’m excited to share our latest research on “Building production ready AI Agents with Scalable Long-Term Memory”. We’ve achieved state-of-the-art (SOTA) performance—26% more accurate than OpenAI Memory. We evaluated Mem0 on the LOCOMO benchmark and found that it consistently outperformed all the six baselines on all types of questions from multi-hop to temporal. Mem0 reduces latency by 91% and cuts token usage by over 90% compared to full-context methods, offering fast and cost-effective performance. Today’s AI agents quickly forget important information once it moves beyond their context window, leading to broken conversations, repeated mistakes, and lost user trust. Larger context windows only delay the issue - making systems slower, more expensive, and harder to scale. Mem0 was built to solve this head on - giving AI Agents a scalable memory layer that remembers what matters, reasons faster and adapts over time. Check out the full paper below 👇🏻

ALT Mem0 outperformed six leading baselines across diverse tasks on the LOCOMO benchmark - from single-hop and multi-hop reasoning, to temporal and open-domain scenarios. Notably, Mem0 achieved up to 11% higher accuracy than leading competitive approaches on LLM-as-a-Judge metric, and surpassed OpenAI's memory by 26%.

mem0

@mem0ai

29 Apr 2025

We're excited to announce our latest advancement in building production-ready AI Agents with scalable long-term memory. Mem0 outperformed six leading baselines across diverse tasks on the LOCOMO benchmark - from single-hop and multi-hop reasoning, to temporal and open-domain scenarios. Notably, Mem0 achieved up to 11% higher accuracy than leading competitive approaches on LLM-as-a-Judge metric, and surpassed OpenAI's memory by 26%. And by intelligently leveraging both natural language and graph-based memory structures, Mem0 dramatically reduces computational overhead, resulting in 91% lower latency (p95) compared to traditional full-context methods. This efficiency unlocks powerful possibilities - enabling AI agents to reason faster, handle more complex interactions, and scale effortlessly in production environments. Read the paper here: mem0.ai/research

ALT Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory

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