Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

The inner workings of LLMs are not easy to interpret, but within the past couple of years, researchers have begun using a type of algorithm known as a sparse autoencoder to help shed some light on how ...

Within the past few years, models that can predict the structure or function of proteins have been widely used for a variety of biological applications, such as identifying drug targets and ...

MIT researchers used sparse autoencoders to shed light on the inner workings of protein language models, an advance that could streamline the process of identifying new drugs or vaccine targets.

The inner workings of LLMs are not easy to interpret, but within the past couple of years, researchers have begun using a type of algorithm known as a sparse autoencoder to help shed some light on ...