Synthetic Data for LLM Fine-tuning with ACT-R (Interview with Alessandro Oltramari)

Alessandro Oltramari is the President of the Carnegie-Bosch Institute and a Group Leader at Bosch Research. In this video, he gives an overview of how the ACT-R cognitive architecture can be leveraged to create synthetic data to train an LLM agent with a focus on industrial use-cases. However, the discussion goes beyond that and touches on a variety of aspects in AI including cognitive models and the limits of supervised fine-tuning.

CBI: carnegiebosch.cmu.edu/index.html

Bosch Research: https://www.bosch.com/research/

Oltramari, A. and Lebiere, C., 2012. Using ontologies in a cognitive-grounded system: automatic action recognition in video surveillance. In Proceedings of the 7th international conference on semantic technology for intelligence, defense, and security, Fairfax. https://www.academia.edu/download/822...

Binz, Marcel, and Eric Schulz. "Turning large language models into cognitive models arXiv preprint arXiv:2306.03917 (2023). https://arxiv.org/abs/2306.03917

Wu, Siyu, Alessandro Oltramari, and Frank E. Ritter. "VSM-ACT-R: Toward Using Cognitive Architecture For Manufacturing Solutions." International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Cham: Springer Nature Switzerland, 2024. https://link.springer.com/chapter/10....

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