Projekt

Just Better Data entwickelt und implementiert KI-basierte Methoden und Werkzeuge, um Daten effizient und in hoher Genauigkeit zu sammeln und an der Edge aufzubereiten anstatt unnötig große Datenmengen zu erzeugen.

Projekt

Just Better Data entwickelt und implementiert KI-basierte Methoden und Werkzeuge, um Daten effizient und in hoher Genauigkeit zu sammeln und an der Edge aufzubereiten anstatt unnötig große Datenmengen zu erzeugen.

Project

Automated driving functions are very limited in their scope of use. The reasons lie in the system architecture and the discriminative machine learning methods applied today. Based on generative methods, NXT GEN AI METHODS – nxtAIM introduces the bidirectional flow of information as a new paradigm into the chain of effects and enables massive improvements for the development of autonomous driving functions. Foundation models for driving data will emerge as an outstanding result for industry implementation.

Approach

nxtAIM will utilize the massive potential of generative methods to develop new approaches for better scalability, better transferability, and better traceability. The focus is on the development of generative methods that are complementary to the established discriminative methods of artificial intelligence and thus initiate a paradigm shift towards a bidirectional flow of information in the value chain.

Project

Automated driving functions are very limited in their scope of use. The reasons lie in the system architecture and the discriminative machine learning methods applied today. Based on generative methods, NXT GEN AI METHODS – nxtAIM introduces the bidirectional flow of information as a new paradigm into the chain of effects and enables massive improvements for the development of autonomous driving functions. Foundation models for driving data will emerge as an outstanding result for industry implementation.

Approach

nxtAIM will utilize the massive potential of generative methods to develop new approaches for better scalability, better transferability, and better traceability. The focus is on the development of generative methods that are complementary to the established discriminative methods of artificial intelligence and thus initiate a paradigm shift towards a bidirectional flow of information in the value chain.

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