NXAI unveils its first time series model, TiRex, based on the novel xLSTM architecture – and immediately claims the top spot in well-known international benchmark leaderboards. Despite having just 35 million parameters, TiRex is significantly smaller and more memory-efficient than its competitors. It not only excels in prediction accuracy but is also considerably faster. A decisive advantage lies in the model’s ability to continuously monitor, analyse, and update the system state – known as state tracking. Transformer-based approaches lack this capability. TiRex, on the other hand, can approximate hidden or latent states over time, improving predictive performance. Its architecture offers another major benefit: it is adaptable to hardware and enables embedded AI applications.
NXAI unveils its first time series model, TiRex, based on the novel xLSTM architecture – and immediately claims the top spot in well-known international benchmark leaderboards. Despite having just 35 million parameters, TiRex is significantly smaller and more memory-efficient than its competitors. It not only excels in prediction accuracy but is also considerably faster. A decisive advantage lies in the model’s ability to continuously monitor, analyse, and update the system state – known as state tracking. Transformer-based approaches lack this capability. TiRex, on the other hand, can approximate hidden or latent states over time, improving predictive performance. Its architecture offers another major benefit: it is adaptable to hardware and enables embedded AI applications.