Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...

Back in the ancient days of machine learning, before you could use large language models (LLMs) as foundations for tuned models, you essentially had to train every possible machine learning model on ...

Choosing flexible hardware for DNN architectures for apps like ATM camera systems. How "embeddings" can be effective in the image-recognition reidentification process. How Arcturus Networks developed ...

Google recently published research on a technique to train a model to be able to solve natural language processing problems in a way that can be applied to multiple tasks. Rather than train a model to ...

A Microsoft and Amazon joint effort makes neural networks easier to program and use with the MXNet and Microsoft Cognitive Toolkit frameworks Deep learning systems have long been tough to work with, ...

Scientists are using machine learning techniques to streamline the process of synthesizing graphene from waste through flash Joule heating. Rice University scientists are using machine-learning ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now A new study by Anthropic shows that ...