AWS Machine Learning Blog

Category: AWS Partner Network

Provide live agent assistance for your chatbot users with Amazon Lex and Talkdesk cloud contact center

Amazon Lex provides advanced conversational artificial intelligence (AI) capabilities to enable self-service support for your organization’s contact center. With Amazon Lex, you can implement an omnichannel strategy where customers engage via phone, websites, and messaging platforms. The bots can answer FAQs, provide self-service experiences, or triage customer requests before transferring to a human agent. Amazon Lex integrates […]

Boost your content editing with Contentful and Amazon Bedrock

This post is co-written with Matt Middleton from Contentful. Today, jointly with Contentful, we are announcing the launch of the AI Content Generator powered by Amazon Bedrock. The AI Content Generator powered by Amazon Bedrock is an app available on the Contentful Marketplace that allows users to create, rewrite, summarize, and translate content using cutting-edge […]

Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector database on AWS Marketplace

This post discusses how enterprises can build accurate, transparent, and secure generative AI applications while keeping full control over proprietary data. The proposed solution is a RAG pipeline using an AI-native technology stack, whose components are designed from the ground up with AI at their core, rather than having AI capabilities added as an afterthought. We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace.

Build financial search applications using the Amazon Bedrock Cohere multilingual embedding model

Enterprises have access to massive amounts of data, much of which is difficult to discover because the data is unstructured. Conventional approaches to analyzing unstructured data use keyword or synonym matching. They don’t capture the full context of a document, making them less effective in dealing with unstructured data. In contrast, text embeddings use machine […]

Event Driven MLOps architecture with SageMaker

Modernizing data science lifecycle management with AWS and Wipro

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. […]

Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

This post was written in collaboration with Ankur Goyal and Karthikeyan Chokappa from PwC Australia’s Cloud & Digital business. Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production […]

Bring your own AI using Amazon SageMaker with Salesforce Data Cloud

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. We’re excited to announce Amazon SageMaker and Salesforce Data Cloud integration. With this capability, businesses can access their Salesforce data securely with a zero-copy approach using SageMaker and use SageMaker tools to build, train, and deploy AI models. The inference endpoints are […]

Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center

This blog post is co-written with Bruno Mateus, Jonathan Diedrich and Crispim Tribuna at Talkdesk. Contact centers are using artificial intelligence (AI) and natural language processing (NLP) technologies to build a personalized customer experience and deliver effective self-service support through conversational bots. This is the first of a two-part series dedicated to the integration of […]

Improve ML developer productivity with Weights & Biases: A computer vision example on Amazon SageMaker

July 2023: This post was reviewed for accuracy. This post is co-written with Thomas Capelle at Weights & Biases. As more organizations use deep learning techniques such as computer vision and natural language processing, the machine learning (ML) developer persona needs scalable tooling around experiment tracking, lineage, and collaboration. Experiment tracking includes metadata such as […]

How Mantium achieves low-latency GPT-J inference with DeepSpeed on Amazon SageMaker

Mantium is a global cloud platform provider for building AI applications and managing them at scale. Mantium’s end-to-end development platform enables enterprises and businesses of all sizes to build AI applications and automation faster and easier than what has been traditionally possible. With Mantium, technical and non-technical teams can prototype, develop, test, and deploy AI […]