AWS’ 5 New Generative AI Tools For Nvidia, Anthropic And LLMs

New AWS generative AI tools include HealthScribe and Entity Resolution, as well as integrations with Nvidia H100 GPUs and Anthropic’s foundation models.

Amazon Web Services’ generative AI charge continued this week as the cloud giant unveiled five new tools that included integrations with the likes of Nvidia and Anthropic, as well as brand new AWS services such as HealthScribe and Entity Resolution.

“ Generative AI has captured our imaginations,” said AWS’ Swami Sivasubramanian, vice president of database, analytics and machine learning, during AWS Summit 2023 this week. “This technology has reached its tipping point.”

The $85 billion Seattle-based cloud computing market leader has launched a slew of new services, solutions and capabilities around generative AI in 2023 with CEO Adam Selipsky leading the charge.

This week, Selipsky touted his company’s generative AI innovation engine on display at AWS Summit in New York, particularly, Amazon Bedrock which is used to build and scale generative AI applications.

“We announced agents for Amazon Bedrock, a new capability that enables generative AI applications to complete tasks in just a few clicks—based on organization data and user input without any manual code,” said AWS’ CEO on LinkedIn. “Developers can easily integrate the agents and accelerate delivery of generative AI applications saving weeks of development effort. You’re going to be hearing a lot more about this exciting capability!”

AWS: Generative AI Can ‘Transform’ Tech Industry

AWS’ Sivasubramanian said through services like Amazon Bedrock and collaborations with other technology leaders like Nvidia, Amazon is “democratizing access to generative AI,” so wherever customers are on their machine learning journey,” they can use AWS to innovate and create new products.

“Generative AI has the potential to transform every application, business, and industry. Advancements across data processing, compute, and machine learning are expediting the shift from experimentation to deployment for AWS customers of all sizes,” said Sivasubramanian in a blog post.

CRN breaks down the five most important generative AI launches from AWS at its summit this week that AWS partners, investors and customers need to know about.

Amazon Bedrock Adds New FMs With Cohere, Anthropic And Stability AI

AWS’ fully managed foundation model (FM) service Amazon Bedrock will now include Cohere as a FM provider as well as the latest FMs from Anthropic and Stability AI.

This includes Anthropic’s latest version of its language model Claude 2, as well as Stability AI’s Stable Diffusion XL 1.0 which produces improved image and composition detail to generate more realistic creations for films, music and videos.

Bedrock will also now have Cohere’s text generation model, Command, as well as its multilingual text understanding model, Cohere Embed as options.

Amazon Bedrock is used to build and scale generative AI applications with a selection of industry FMs by accessing an API. Bedrock allows customers to find and test different models, customize a model to fit their needs, and then integrate and deploy it to production.

New Amazon EC2 Instances Powered By Nvidia H100 GPUs For Gen AI

Amazon’s popular Elastic Compute Cloud (EC2) launched new instances powered by Nvidia H100 Tensor Core GPUs and AWS’s latest networking and scalability that will deliver up to 20 exaflops of compute performance for building and training large machine learning models.

These new Amazon EC2 P5 instances are now generally available.

AWS touts that it’s the first leading cloud provider to make Nvidia’s H100 GPUs generally available in production. These instances are ideal for training and running inference for large language models (LLMs) and compute-intensive generative AI applications—including question answering, code generation, video and image generation, speech recognition, and more.

With access to H100 GPUs, AWS says customers will be able to create their own LLMs and FMs on AWS faster than ever.

New Agents For Amazon Bedrock For Developers

Amazon Bedrock was also injected with a new capability for creating fully managed agents in just a few clicks.

Agents for Amazon Bedrock is a new capability that makes it easier for developers to create generative-AI based applications that can complete complex tasks for a wide range of use cases and deliver up-to-date answers based on proprietary knowledge sources.

With just a few clicks, AWS says Bedrock’s new agents automatically break down tasks and create an orchestration plan—without any manual coding. The agent securely connects to company data through an API, automatically converting data into a machine-readable format, and augmenting the request with relevant information to generate the most accurate response.

Agents can then automatically call APIs to fulfill a user’s request.

AWS’ New HealthScribe For Healthcare

AWS unveiled a new HIPAA-eligible automatic note generation service for clinical applications dubbed HealthScribe.

HealthScribe uses speech recognition and Amazon Bedrock’s generative AI technology to create transcripts and generate easy-to-review clinical notes, with built-in security and privacy features designed to protect sensitive patient data.

With AWS HealthScribe, healthcare software providers can use a single API to automatically create transcripts, extract key details—such as medications— and create summaries from doctor-patient discussions that can then be entered into an electronic health record (EHR) system.

AWS said HealthScribe enables responsible AI by citing the source of every line of generated text from within the original conversation transcript.

AWS Entity Resolution Becomes GA To Boost Customer Insights

AWS’ analytics services powered by machine learning, Entity Resolution, has become generally available in the market which helps customers better understand how their data is related, matched and linked for better insights.

Entity Resolution helps organizations analyze, match, and link related records stored across applications, channels and data stores. It uses customizable workflows that leverage rule-based and ML techniques to join related consumer, business, and product information.

AWS Entity Resolution offers advanced matching techniques, such as rule-based matching and machine learning models, to help customers accurately link related sets of customer information, product codes, or business data codes.

For example, a user can use AWS Entity Resolution to create a unified view of their customers’ interactions by linking recent events—such as ad clicks, cart abandonment and purchases—into a entity ID, or better track products that use different codes across stores.