Google launches the London AI Campus
Google has launched the AI Campus in Somers Town, Camden, home to a two-year education pilot aimed to help inspire, inform, and educate local sixth form students in the …
Microsoft Cost Management updates—November 2024
As you may know, November is the month for Microsoft’s largest customer and partner event—Microsoft Ignite. This year, we in the Cost management team, announced key product updates at this event to enable your FinOps journey. Below, you’ll find a summary of these enhancements. We invite you to explore and take full advantage of these …
Create a generative AI assistant with Slack and Amazon Bedrock
Seamless integration of customer experience, collaboration tools, and relevant data is the foundation for delivering knowledge-based productivity gains. In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where business users can ask questions of an unstructured dataset. To demonstrate, …
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Unleash your Salesforce data using the Amazon Q Salesforce Online connector
Thousands of companies worldwide use Salesforce to manage their sales, marketing, customer service, and other business operations. The Salesforce cloud-based platform centralizes customer information and interactions across the organization, providing sales reps, marketers, and support agents with a unified 360-degree view of each customer. With Salesforce at the heart of their business, companies accumulate vast …
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Reducing hallucinations in large language models with custom intervention using Amazon Bedrock Agents
Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. This can occur when the model’s training data lacks the necessary information or when the model attempts to generate coherent responses by making logical inferences beyond its actual knowledge. Hallucinations arise …
Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM
With the rise of large language models (LLMs) like Meta Llama 3.1, there is an increasing need for scalable, reliable, and cost-effective solutions to deploy and serve these models. AWS Trainium and AWS Inferentia based instances, combined with Amazon Elastic Kubernetes Service (Amazon EKS), provide a performant and low cost framework to run LLMs efficiently …
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Serving LLMs using vLLM and Amazon EC2 instances with AWS AI chips
The use of large language models (LLMs) and generative AI has exploded over the last year. With the release of powerful publicly available foundation models, tools for training, fine tuning and hosting your own LLM have also become democratized. Using vLLM on AWS Trainium and Inferentia makes it possible to host LLMs for high performance …
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Using LLMs to fortify cyber defenses: Sophos’s insight on strategies for using LLMs with Amazon Bedrock and Amazon SageMaker
This post is co-written with Adarsh Kyadige and Salma Taoufiq from Sophos. As a leader in cutting-edge cybersecurity, Sophos is dedicated to safeguarding over 500,000 organizations and millions of customers across more than 150 countries. By harnessing the power of threat intelligence, machine learning (ML), and artificial intelligence (AI), Sophos delivers a comprehensive range of …
Enhanced observability for AWS Trainium and AWS Inferentia with Datadog
This post is co-written with Curtis Maher and Anjali Thatte from Datadog. This post walks you through Datadog’s new integration with AWS Neuron, which helps you monitor your AWS Trainium and AWS Inferentia instances by providing deep observability into resource utilization, model execution performance, latency, and real-time infrastructure health, enabling you to optimize machine learning …
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Create a virtual stock technical analyst using Amazon Bedrock Agents
Stock technical analysis questions can be as unique as the individual stock analyst themselves. Queries often have multiple technical indicators like Simple Moving Average (SMA), Exponential Moving Average (EMA), Relative Strength Index (RSI), and others. Answering these varied questions would mean writing complex business logic to unpack the query into parts and fetching the necessary …
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