Industries updates

In the field of generative AI, latency and cost pose significant challenges. The commonly used large language models (LLMs) often process text sequentially, predicting one token at a time in an autoregressive manner. This approach can introduce delays, resulting in less-than-ideal user experiences. Additionally, the growing demand for AI-powered applications has led to a high …

Build a read-through semantic cache with Amazon OpenSearch Serverless and Amazon Bedrock Read More »

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 …

Rad AI reduces real-time inference latency by 50% using Amazon SageMaker Read More »

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 …

Read graphs, diagrams, tables, and scanned pages using multimodal prompts in Amazon Bedrock Read More »

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 …

How Crexi achieved ML models deployment on AWS at scale and boosted efficiency Read More »

New UK research commissioned by Google Cloud highlights the transformative potential of generative AI in the public sector.

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 …

Deploy Meta Llama 3.1 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium Read More »

In the rapidly evolving digital content industry, multilingual accessibility is crucial for global reach and user engagement. 123RF, a leading provider of royalty-free digital content, is an online resource for creative assets, including AI-generated images from text. In 2023, they used Amazon OpenSearch Service to improve discovery of images by using vector-based semantic search. Building …

How 123RF saved over 90% of their translation costs by switching to Amazon Bedrock Read More »

Enterprises face significant challenges accessing and utilizing the vast amounts of information scattered across organization’s various systems. What if you could simply ask a question and get instant, accurate answers from your company’s entire knowledge base, while accounting for an individual user’s data access levels? Amazon Q Business is a game changing AI assistant that’s …

Connect SharePoint Online to Amazon Q Business using OAuth 2.0 ROPC flow authentication Read More »

Today, we are excited to announce that John Snow Labs’ Medical LLM – Small and Medical LLM – Medium large language models (LLMs) are now available on Amazon SageMaker Jumpstart. Medical LLM is optimized for the following medical language understanding tasks: Summarizing clinical encounters – Summarizing discharge notes, progress notes, radiology reports, pathology reports, and …

John Snow Labs Medical LLMs are now available in Amazon SageMaker JumpStart Read More »