TimeNet: Open-source data infrastructure for Temporal Foundation Models
Hi HN, Current frontier LLMs show incredible results across text, video, and audio, but don't do as well with real-world scenarios like production lines, trading, drilling operations, or demand supply forecasting. They are not capable of comprehending this data, especially given a limited context. Models exist that are able to understand temporal information natively—Temporal Foundation Models (TFMs). However, there is a data problem: unlike all the public information that frontier models train
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指标快照
points · 34 votes
2026-11-11 20:00:27.360Z
cumulative since publication
研究分析
项目记录
仓库：OpenTSLM/TimeNet。 来源描述：Hi HN, Current frontier LLMs show incredible results across text, video, and audio, but don't do as well with real-world scenarios like production lines, trading, drilling operations, or demand supply forecasting. They are not capable of comprehending this data, especially given a limited context. Models exist that are able to understand temporal information natively—Temporal Foundation Models (TFMs). However, there is a data problem: unlike all the public information that frontier models train
采用记录与比较对象
来源票数: 34 votes (2026年11月11日 UTC; cumulative since publication) 可供比较的近期同类记录：“Show HN: Open HashLMG – Local Motion Graphics by models on your device” (Show HN, 2026年11月11日)；“Show HN: FilmCraft – Free open-source video editor in Rust, like Premiere” (Show HN, 2026年11月11日)。主题相近仅用于导航，未核验其是否属于同一需求或独立证据。
采用判断
应与它要替代的工具或人工流程比较。现有记录支持发现项目，尚不能确认可靠性、运行成本优势或商业采用。
尚未核验的门槛
尚未核验：许可证权限、硬件要求、安装步骤、维护状态，以及包含失败样例的代表性任务。
下一步试验
选择一个真实任务和现有替代方案，记录 commit、环境、输入、输出、耗时与失败行为；保留结果后再给出采用建议。