Joining Rus on the founding Liquid AI team are Ramin Hasani (CEO), Mathias Lechner (CTO) and Alexander Amini (chief scientific officer).
“The idea was invented originally at the Vienna University of Technology, Austria at professor Radu Grosu’s lab, where I completed my Ph.D. and Mathias Lechner his master’s degree,” Hasani told TechCrunch in an email interview.
In tests, liquid neural networks have edged out other state-of-the-art algorithms in predicting future values in datasets spanning atmospheric chemistry to car traffic.
They then deployed the algorithm on a fleet of quadrotors, which underwent long-distance, target-tracking and other tests in a range of outdoor environments, including a forest and dense city neighborhood.
According to the team, the liquid neural network beat other models trained for navigation — managing to make decisions that led the drones to targets in previously unexplored spaces even in the presence of noise and other challenges.
But Rus and the rest of the Liquid AI team assert that the architecture is suited to analyzing any phenomena that fluctuate over time, including electric power grids, medical readouts, financial transactions and severe weather patterns.
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Joining Rus on the founding Liquid AI team are Ramin Hasani (CEO), Mathias Lechner (CTO) and Alexander Amini (chief scientific officer).
“The idea was invented originally at the Vienna University of Technology, Austria at professor Radu Grosu’s lab, where I completed my Ph.D. and Mathias Lechner his master’s degree,” Hasani told TechCrunch in an email interview.
In tests, liquid neural networks have edged out other state-of-the-art algorithms in predicting future values in datasets spanning atmospheric chemistry to car traffic.
They then deployed the algorithm on a fleet of quadrotors, which underwent long-distance, target-tracking and other tests in a range of outdoor environments, including a forest and dense city neighborhood.
According to the team, the liquid neural network beat other models trained for navigation — managing to make decisions that led the drones to targets in previously unexplored spaces even in the presence of noise and other challenges.
But Rus and the rest of the Liquid AI team assert that the architecture is suited to analyzing any phenomena that fluctuate over time, including electric power grids, medical readouts, financial transactions and severe weather patterns.
The original article contains 1,141 words, the summary contains 183 words. Saved 84%. I’m a bot and I’m open source!