Cartesia 发布 Managed Agents，在 Speech Agent Arena 盲测偏好中排名第一
A cascaded voice agent just won a blind human-preference ranking against native speech-to-speech models.
Cartesia 推出面向企业的端到端语音智能体平台 Managed Agents，在 Artificial Analysis 的 Speech Agent Arena 盲测人类偏好中排名第一，并在 ServiceNow EVA-Bench 上排名第一。该平台采用级联架构，将自有语音模型与智能体 harness 作为一个系统联合调优。其 H-Nets 直接从原始字节学习，在受控扩展实验中效率提升 3–5 倍，更大规模下以约 10 倍更少的训练数据和算力匹配了用 11 万亿 token 训练的开源模型。
查看原帖隆重推出 Cartesia Managed Agents：我们面向企业的端到端语音智能体平台。 在 @ArtificialAnlys Speech Agent Arena 和 @ServiceNow EVA-Bench 上均排名第一，这得益于我们将自有语音模型与 harness 作为一个系统进行协同设计。 立即体验 → https://t.co/7kJhCYqjQo https://t.co/NVOAds9czf
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Introducing Cartesia Managed Agents: our end-to-end voice agent platform for enterprise. #1 on @ArtificialAnlys Speech Agent Arena and @ServiceNow EVA-Bench, built by co-designing our voice models and harness as one system. Check it out → https://t.co/7kJhCYqjQo https://t.co/NVOAds9czf
正文
A cascaded voice agent just won a blind human-preference ranking against native speech-to-speech models.
Today, Cartesia launched Managed Agents, ranked #1 on Artificial Analysis’ Speech Agent Arena.
Most LLMs learn from chunks of text picked by a tokenizer. But here, H-Nets learn directly from raw bytes and figure out those boundaries themselves.
This leads to 3–5x better efficiency in controlled scaling experiments. At larger scale, matching an open-source model trained on 11 trillion tokens with roughly 10x less training data and compute.
> #1 in blind human preference and #1 in enterprise accuracy > Cascaded stack that sounds as natural as speech-to-speech > Own speech models and agent harness tuned as one system