Blog
Essays and notes on machine learning, representation learning, causality, and occasional reflections.
A short take on where representation learning lives in the era of large multimodal models and limited compute.
Reflections on minds, intelligence, and knowing.
Why identifiable representations are crucial for responsible AI.
On the tension between flexibility and precision in biological and artificial systems.
Thoughts on the grounding of language, LLMs, and symbolic understanding.
Personal routine reflections for better research alignment and weekly growth.
An overview connecting rate-distortion theory, VIB, and beta-VAE under the information bottleneck lens.
Reflections on disentanglement and causality in contrastive learning frameworks.