Apple's New AI Breakthrough: Fine-Grained Control of Generative Models with Activation Transport (AcT)

Apple machine learning researchers have developed Activation Transport (AcT), a novel technique offering fine-grained control over large generative models, including LLMs and text-to-image diffusion models, without the resource-intensive training of RLHF or fine-tuning. AcT steers model activations using optimal transport theory, achieving modality-agnostic control with minimal computational overhead. Experiments demonstrate significant improvements in toxicity mitigation, truthfulness induction in LLMs, and stylistic control in image generation. AcT paves the way for safer and more reliable generative models.