AI

This post is co-written with Ken Kao and Hasan Ali Demirci from Rad AI. Rad AI has reshaped radiology reporting, developing solutions that streamline the most tedious and repetitive tasks, and saving radiologists’ time. Since 2018, using state-of-the-art proprietary and open source large language models (LLMs), our flagship product—Rad AI Impressions— has significantly reduced the […]

Large language models (LLMs) have come a long way from being able to read only text to now being able to read and understand graphs, diagrams, tables, and images. In this post, we discuss how to use LLMs from Amazon Bedrock to not only extract text, but also understand information available in images. Amazon Bedrock

This post is co-written with Isaac Smothers and James Healy-Mirkovich from Crexi.  With the current demand for AI and machine learning (AI/ML) solutions, the processes to train and deploy models and scale inference are crucial to business success. Even though AI/ML and especially generative AI progress is rapid, machine learning operations (MLOps) tooling is continuously

Billions of dollars in hardware and exorbitant use costs are squashing AI innovation. LLMs need to get leaner and cheaper if progress is to be made.

The genome-editing technology can be supercharged by artificial intelligence—and the results are already being felt.

Beyond the deepfakes and disinformation, the potential for AI to make politics more accessible and equitable cannot be ignored.

A growing movement to allow access to algorithmic workings won’t stop the ubiquitous spread of artificial intelligence, but it could restore public confidence in it.

We’re excited to announce the availability of Meta Llama 3.1 8B and 70B inference support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. Meta Llama 3.1 multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models. Trainium and Inferentia, enabled by the AWS Neuron software development kit

Captivated as a child by video games and puzzles, Marzyeh Ghassemi was also fascinated at an early age in health. Luckily, she found a path where she could combine the two interests.  “Although I had considered a career in health care, the pull of computer science and engineering was stronger,” says Ghassemi, an associate professor in