We provide a scalable bandit architecture for prompt tuning of decision transformers for increased downstream performance.

We develop AI research agents that achieve state-of-the-art performance on real-world Kaggle competitions by searching the space of candidate code solutions.

Learning representations on a latent space from observed and structured solutions through a differentiable constrained optimization problem