Observed Signal · Jul 16, 2024 · Technical Release · Source: Trending Topics · Impact: 2/5 · Sentiment: Positive
xLSTM: Linz AI Model Gains Attention With Forecasting Study
An Austrian AI startup, NXAI, is drawing renewed attention to xLSTM, a new model architecture developed by Sepp Hochreiter and his team as an alternative to transformer-based models such as GPT-4, Claude 3.5, and Gemini 1.5. A new study by researchers at the University of Bridgeport shows that xLSTM performs strongly in multivariate long-term time series forecasting for traffic, electricity, weather, and flu-like illness data, claiming superior accuracy compared with state-of-the-art transformer-based models. The xLSTM research reached the top spot on Hacker News. NXAI is also working on simulations in its AI4Simulation unit and is currently raising a large financing round after securing a mid-double-digit million amount earlier in 2024. The company has announced plans to release its first competitive AI model before the end of the year.
The article covers a promising alternative to transformer-based AI models with strong forecasting benchmarks; it matters for the broader AI infrastructure landscape but has no direct near-term impact on adtech or martech operations.
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Key Takeaways & Evidence Grounding
- NXAI, an AI startup connected to Sepp Hochreiter, is developing xLSTM as an alternative to transformer-based models such as GPT-4, Claude 3.5, and Gemini 1.5.
- Researchers Musleh Alharthi and Ausif Mahmood from the University of Bridgeport published a study showing xLSTM performs strongly in multivariate long-term time series forecasting.
- The study reports that xLSTM outperforms state-of-the-art transformer-based models in accuracy for forecasts involving traffic, electricity, weather, and flu-like illnesses.
- xLSTM research was listed as the top topic on Hacker News.
- NXAI is raising a large financing round after already securing a mid-double-digit million amount earlier in 2024, and plans to release its first competitive AI model before the end of the year.
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