AWS Machine Learning Blog
Category: Python
Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock
In this post, we explore some ways you can use Anthropic’s Claude 3 Sonnet’s vision capabilities to accelerate the process of moving from architecture to the prototype stage of a solution.
Implementing advanced prompt engineering with Amazon Bedrock
In this post, we provide insights and practical examples to help balance and optimize the prompt engineering workflow. We focus on advanced prompt techniques and best practices for the models provided in Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models from leading AI companies such as Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. With these prompting techniques, developers and researchers can harness the full capabilities of Amazon Bedrock, providing clear and concise communication while mitigating potential risks or undesirable outputs.
Use the ApplyGuardrail API with long-context inputs and streaming outputs in Amazon Bedrock
As generative artificial intelligence (AI) applications become more prevalent, maintaining responsible AI principles becomes essential. Without proper safeguards, large language models (LLMs) can potentially generate harmful, biased, or inappropriate content, posing risks to individuals and organizations. Applying guardrails helps mitigate these risks by enforcing policies and guidelines that align with ethical principles and legal requirements.Amazon […]
Use zero-shot large language models on Amazon Bedrock for custom named entity recognition
Name entity recognition (NER) is the process of extracting information of interest, called entities, from structured or unstructured text. Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. Some examples include extracting players and positions in an NFL game summary, products mentioned in an AWS keynote transcript, or […]
Uncover hidden connections in unstructured financial data with Amazon Bedrock and Amazon Neptune
In asset management, portfolio managers need to closely monitor companies in their investment universe to identify risks and opportunities, and guide investment decisions. Tracking direct events like earnings reports or credit downgrades is straightforward—you can set up alerts to notify managers of news containing company names. However, detecting second and third-order impacts arising from events […]
Unlocking language barriers: Translate application logs with Amazon Translate for seamless support
This post addresses the challenge faced by developers and support teams when application logs are presented in languages other than English, making it difficult for them to debug and provide support. The proposed solution uses Amazon Translate to automatically translate non-English logs in CloudWatch, and provides step-by-step guidance on deploying the solution in your environment.
Implement smart document search index with Amazon Textract and Amazon OpenSearch
In this post, we’ll take you on a journey to rapidly build and deploy a document search indexing solution that helps your organization to better harness and extract insights from documents. Whether you’re in Human Resources looking for specific clauses in employee contracts, or a financial analyst sifting through a mountain of invoices to extract payment data, this solution is tailored to empower you to access the information you need with unprecedented speed and accuracy.