Industrial AI Podcast xLSTM-based time series model TiRex - why is it leading the leaderboards?
Jun 4, 2025
Sepp Hochreiter, a pioneer of LSTM and head of the Institute for Machine Learning at Johannes Kepler University, discusses TiRex, a revolutionary time series model surpassing industry giants like Amazon and Google. He explains the evolution of LSTM to XLSDM, emphasizing its strengths in forecasting. TiRex is designed for user-friendly industrial applications with impressive speed and accuracy. Hochreiter also compares TiRex with competitors and shares insights on job opportunities for those eager to join the innovative team in Linz.
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XLSDM Enhances LSTM for Time Series
- XLSDM combines strengths of LSTM and Transformer models for time-series data.
- It enables parallelization and fast processing while maintaining LSTM's state tracking ability.
Time Series Impact Across Industries
- Time series data pervades domains from weather and stock markets to healthcare and energy.
- Sepp shares examples like flood prediction using hydrology models with hidden states.
LSTM Captures Hidden System States
- LSTM excels at capturing hidden states in complex systems, outperforming traditional statistical models.
- This ability makes it especially suited for predicting time series with underlying states, like hydrology or pipes.