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English(EN) Google's SensorFM trained on a trillion minutes of body data from 5M people. The device was never the product — the continuous stream off your wrist was. A foun

Google 的 SensorFM 在 500 万人的身体数据上进行训练

作者 PulseAugur 编辑部 · [1 个来源] ·

Google 开发了 SensorFM，这是一个在来自 500 万人的海量身体数据数据集上训练的基础模型。该模型处理来自可穿戴设备的连续数据流，超越了简单的计步功能，能够生成预测。这些数据收集了万亿分钟，凸显了用于训练的信息规模。 AI

影响 这一发展可能基于连续的生理数据，为健康和行为带来更复杂的预测模型。

排序理由 该条目描述了一个基础模型在大规模数据集上的训练，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — fosstodon.org 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Google 的 SensorFM 在 500 万人的身体数据上进行训练

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该条目描述了一个基础模型在大规模数据集上的训练，属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Google's SensorFM 训练了来自 500 万人的万亿分钟身体数据。该设备从未成为产品——持续的腕部数据流才是。一个基础

    Google's SensorFM trained on a trillion minutes of body data from 5M people. The device was never the product — the continuous stream off your wrist was. A foundation model turns that exhaust into prediction, not step-counting. # AI # MachineLearning # LLM # Threadverse # Tech

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