AWS Machine Learning Blog

JUNE 25, 2024

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. This provides an automated deployment experience on your AWS account. Prerequisites This post is intended for developers with a basic understanding of LLM and prompt engineering.

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Automation Prompt Engineering Prompt Engineer Categorization 119

AWS Machine Learning Blog

DECEMBER 5, 2024

With the launch of the Automated Reasoning checks in Amazon Bedrock Guardrails (preview), AWS becomes the first and only major cloud provider to integrate automated reasoning in our generative AI offerings. Click on the image below to see a demo of Automated Reasoning checks in Amazon Bedrock Guardrails.

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Responsible AI AI Tools AI AI 102

Unite.AI

OCTOBER 7, 2024

Yes, they have the data, the metadata, the workflows and a vast array of services to connect into; and so long as your systems only live within Salesforce, it sounds pretty ideal. While Salesforce and others talk a big game about automation, it’s always grounded in the need to be able to bring a human back into the center when necessary.

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AI AI Prompt Engineering Prompt Engineer 189

AWS Machine Learning Blog

FEBRUARY 12, 2025

You can use metadata filtering to narrow down search results by specifying inclusion and exclusion criteria. Along with protecting against toxicity and harmful content, it can also be used for Automated Reasoning checks , which helps you protect against hallucinations.

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Auto-classification Metadata Generative AI Machine Learning 81

AWS Machine Learning Blog

MARCH 25, 2025

Implement metadata filtering , adding contextual layers to chunk retrieval. For code samples for metadata filtering using Amazon Bedrock Knowledge Bases, refer to the following GitHub repo. Success comes from methodically using techniques like prompt engineering and chunking to improve both the retrieval and generation stages of RAG.

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Prompt Engineering Prompt Engineer Metadata Responsible AI 84

IBM Journey to AI blog

JULY 17, 2023

IBM software products are embedding watsonx capabilities across digital labor, IT automation, security, sustainability, and application modernization to help unlock new levels of business value for clients. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

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Machine Learning Metadata Automation AI 186

Unite.AI

JUNE 11, 2024

Experts can check hard drives, metadata, data packets, network access logs or email exchanges to find, collect, and process information. Automate Processes Automation is one of AI’s greatest capabilities. Unfortunately, they often hallucinate, especially when unintentional prompt engineering is involved.

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NLP Automation AI AI 147

AWS Machine Learning Blog

NOVEMBER 7, 2024

Prompt catalog – Crafting effective prompts is important for guiding large language models (LLMs) to generate the desired outputs. Prompt engineering is typically an iterative process, and teams experiment with different techniques and prompt structures until they reach their target outcomes.

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Generative AI Machine Learning AI AI 106

AWS Machine Learning Blog

MAY 21, 2024

At 20 Minutes, a key goal of our technology team is to develop new tools for our journalists that automate repetitive tasks, improve the quality of reporting, and allow us to reach a wider audience. While these tasks can feel like a chore, they are critical to search engine optimization (SEO) and therefore the audience reach of the article.

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Generative AI Prompt Engineering Prompt Engineer Automation 126

AWS Machine Learning Blog

MAY 7, 2024

This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain. Prompt engineering Prompt engineering enables you to instruct LLMs to generate suggestions, explanations, or completions of text in an interactive way.

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Prompt Engineering Prompt Engineer Large Language Models LLM 115

The MLOps Blog

JUNE 27, 2023

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

OCTOBER 24, 2024

Try metadata filtering in your OpenSearch index. Try using query rewriting to get the right metadata filtering. The retriever isn’t at fault, the problem is with FM generation (evaluated by a human or LLM): Try prompt engineering to mitigate hallucinations. If none of the above help: Consider training a custom embedding.

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Chatbots Metadata Generative AI LLM 82

Unite.AI

JANUARY 23, 2024

Prompting Rather than inputs and outputs, LLMs are controlled via prompts – contextual instructions that frame a task. Prompt engineering is crucial to steering LLMs effectively. Hybrid retrieval combines dense embeddings and sparse keyword metadata for improved recall.

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Large Language Models Prompt Engineering Prompt Engineer LLM 100

AWS Machine Learning Blog

AUGUST 21, 2024

The latest advances in generative artificial intelligence (AI) allow for new automated approaches to effectively analyze large volumes of customer feedback and distill the key themes and highlights. This post explores an innovative application of large language models (LLMs) to automate the process of customer review analysis.

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Generative AI Prompt Engineering Prompt Engineer Automation 122

AWS Machine Learning Blog

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. Strong domain knowledge for tuning, including prompt engineering, is required as well.

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Generative AI Prompt Engineering Prompt Engineer ML 122

AWS Machine Learning Blog

MAY 30, 2024

Additionally, VitechIQ includes metadata from the vector database (for example, document URLs) in the model’s output, providing users with source attribution and enhancing trust in the generated answers. Prompt engineering Prompt engineering is crucial for the knowledge retrieval system.

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Chatbots Prompt Engineering Prompt Engineer Large Language Models 123

AWS Machine Learning Blog

JULY 3, 2024

The use cases can range from medical information extraction and clinical notes summarization to marketing content generation and medical-legal review automation (MLR process). We use prompt engineering to send our summarization instructions to the LLM.

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Generative AI LLM Large Language Models Machine Learning 122

deepsense.ai

JULY 30, 2023

Model training is only a small part of a typical machine learning project (source: own study) Of course, in the context of Large Language Models, we often talk about just fine tuning, few-shot learning or just prompt engineering instead of a full training procedure. Not the best combination, right?

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Large Language Models LLM Machine Learning Automation 98

AWS Machine Learning Blog

OCTOBER 24, 2023

The AmazonTextractPDFLoader is a service loader type of document loader that provides quick way to automate document processing by using Amazon Textract in combination with LangChain. This task is particularly useful for automation of key entity extraction that requires the output to be aligned with desired formats.

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IDP LLM Prompt Engineering Prompt Engineer 131

AWS Machine Learning Blog

JUNE 20, 2024

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. Evaluating RAG systems at scale requires an automated approach to extract metrics that are quantitative indicators of its reliability.

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Auto-classification LLM Prompt Engineering Prompt Engineer 128

AWS Machine Learning Blog

AUGUST 26, 2024

We envision a future where AI seamlessly integrates into our teams’ workflows, automating repetitive tasks, providing intelligent recommendations, and freeing up time for more strategic, high-value interactions. AWS data teams make sure the information used is accurate, up to date, and appropriately utilized.

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Generative AI LLM AI AI 119

ODSC - Open Data Science

OCTOBER 6, 2023

Be sure to check out his talk, “ Prompt Optimization with GPT-4 and Langchain ,” there! The difference between the average person using AI and a Prompt Engineer is testing. Most people run a prompt 2–3 times and find something that works well enough. In an industry where time is money, this feature is invaluable.

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Prompt Engineering Prompt Engineer Python Data Science 52

AWS Machine Learning Blog

MAY 17, 2023

You can use large language models (LLMs), more specifically, for tasks including summarization, metadata extraction, and question answering. Solution overview The Meeting Notes Generator Solution creates an automated serverless pipeline using AWS Lambda for transcribing and summarizing audio and video recordings of meetings.

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Large Language Models Auto-complete ML Generative AI 82

The MLOps Blog

MARCH 12, 2024

Tools range from data platforms to vector databases, embedding providers, fine-tuning platforms, prompt engineering, evaluation tools, orchestration frameworks, observability platforms, and LLM API gateways. with efficient methods and enhancing model performance through prompt engineering and retrieval augmented generation (RAG).

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Prompt Engineering Prompt Engineer Large Language Models LLM 52

Snorkel AI

FEBRUARY 5, 2025

This final prompt gives the LLM more context with which to answer the users question. Prompt engineering: crafting effective prompt templates Poorly designed prompt templates can lead to off-target responses or outputs that lack the desired specificity. Learn more about retrieval-augmented generation in our guide.

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Data Scientist LLM Prompt Engineering Prompt Engineer 52

Heartbeat

OCTOBER 19, 2023

These remarkable AI systems have found applications in a wide array of fields, revolutionizing the way we interact with technology and enabling new possibilities in communication, automation, and problem-solving. Users can gain deep insights into the evolution of their prompts and responses.

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Large Language Models Metadata LLM Deep Learning 52

Snorkel AI

MARCH 2, 2023

In terms of technology: generating code snippets, code translation, and automated documentation. This goes into the model risk management in analyzing the metadata around the model, whether it’s fit for purpose with automated or human-in-the-loop capabilities. Then comes prompt engineering.

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Large Language Models Prompt Engineering Prompt Engineer Neural Network 52

Snorkel AI

MARCH 2, 2023

In terms of technology: generating code snippets, code translation, and automated documentation. This goes into the model risk management in analyzing the metadata around the model, whether it’s fit for purpose with automated or human-in-the-loop capabilities. Then comes prompt engineering.

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Large Language Models Prompt Engineering Prompt Engineer Neural Network 52

Heartbeat

DECEMBER 13, 2023

Automation: Custom tools enable you to automate repetitive tasks or workflows. From expanding functionality with specific use cases to seamless integration and automation, LangChain’s agents are reshaping how we interact with AI systems. Integration: Custom tools can integrate LangChain with other systems or tools.

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LLM Metadata Deep Learning Prompt Engineer 52

Heartbeat

NOVEMBER 22, 2023

The StringComparison evaluators facilitate this so you can answer questions like: Which LLM or prompt produces a preferred output for a given question? The simplest and often most reliable automated way to choose a preferred prediction for a given input is to use the pairwise_string evaluator. kwargs : Additional keyword arguments.

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LLM Explainability Metadata Deep Learning 52

Heartbeat

DECEMBER 15, 2023

Using Selenium, a powerful tool for browser automation, it opens an actual browser window (in headless mode, meaning without a graphical interface) and interacts with the webpage. How SeleniumURLLoader Retrieves Text The SeleniumURLLoader is like an undercover agent in the world of web browsers.

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AI Chatbots LLM Chatbots NLP 52

Flipboard

NOVEMBER 24, 2023

This emergent ability in LLMs has compelled software developers to use LLMs as an automation and UX enhancement tool that transforms natural language to a domain-specific language (DSL): system instructions, API requests, code artifacts, and more. The JSON artifact is directly integrated to the core SnapLogic integration platform.

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ETL Prompt Engineering Prompt Engineer Generative AI 159

AWS Machine Learning Blog

NOVEMBER 29, 2023

With these tools in hand, the next challenge is to integrate LLM evaluation into the Machine Learning and Operation (MLOps) lifecycle to achieve automation and scalability in the process. Those metrics serve as a useful tool for automated evaluation, providing quantitative measures of lexical similarity between generated and reference text.

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LLM Data Scientist Algorithm Generative AI 101

Bugra Akyildiz

JULY 4, 2024

Automate health checks: Develop comprehensive scripts to ensure host health. Metadata, callbacks, and data format conversions. They consider this result exciting given the minimal effort required. The article concludes by explaining that deeper language programs in DSPy, like deeper neural networks, can be more effective.

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LLM Python Data Analysis Automation 52

IBM Journey to AI blog

OCTOBER 30, 2024

IBM watsonx™ can be used to automate the identification of regulatory obligations and map legal and regulatory requirements to a risk governance framework. The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets.

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Prompt Engineering Prompt Engineer ETL Machine Learning 238

AWS Machine Learning Blog

NOVEMBER 25, 2024

This prompted 123RF to search for a more reliable and affordable solution to enhance multilingual content discovery. This post explores how 123RF used Amazon Bedrock, Anthropic’s Claude 3 Haiku, and a vector store to efficiently translate content metadata, significantly reduce costs, and improve their global content discovery capabilities.

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Prompt Engineering Prompt Engineer Metadata Generative AI 93

AWS Machine Learning Blog

DECEMBER 4, 2024

The core challenge lies in developing data pipelines that can handle diverse data sources, the multitude of data entities in each data source, their metadata and access control information, while maintaining accuracy. Amazon Q Business also helps streamline tasks and accelerate problem solving.

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Metadata Generative AI Data Ingestion Software Engineer 93