OpenTSLM: Language Models That Understand Time-Series (Stanford, ETH, Google)
13 hours ago
- #Foundation Models
- #Time-Series Analysis
- #Artificial Intelligence
- AI currently understands text, images, audio, and video but struggles with temporal signals like heartbeats, price ticks, and sensor pulses.
- Time-Series Language Models (TSLMs) introduce time series as a native modality alongside text, enabling direct reasoning, explanation, and forecasting over temporal data.
- OpenTSLM offers lightweight base models trained on public data, setting standards for temporal reasoning and supporting a global developer ecosystem.
- Frontier TSLMs are advanced proprietary models for enterprise-grade performance, APIs, fine-tuning, and vertical solutions.
- The vision includes a temporal interface for AI, connecting real-world signals to intelligent decisions, enhancing healthcare, robotics, infrastructure, and human-AI collaboration.
- The team behind OpenTSLM comprises experts from prestigious institutions and companies like ETH, Stanford, Google, and Meta, with original authorship of the OpenTSLM paper.