AWS Machine Learning Blog

MARCH 20, 2025

Customers can use Amazon Bedrock Data Automation to support popular media analysis use cases such as: Digital asset management: in the M&E industry, digital asset management (DAM) refers to the organized storage, retrieval, and management of digital content such as videos, images, audio files, and metadata.

Automation 115

Automation IDP Generative AI Prompt Engineering 115

Unite.AI

OCTOBER 25, 2023

But the drawback for this is its reliance on the skill and expertise of the user in prompt engineering. On the other hand, a Node is a snippet or “chunk” from a Document, enriched with metadata and relationships to other nodes, ensuring a robust foundation for precise data retrieval later on.

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LLM OpenAI Prompt Engineering Prompt Engineer 304

Heartbeat

AUGUST 25, 2023

Introduction Prompt Engineering is arguably the most critical aspect in harnessing the power of Large Language Models (LLMs) like ChatGPT. However; current prompt engineering workflows are incredibly tedious and cumbersome. Logging prompts and their outputs to .csv First install the package via pip.

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Prompt Engineer Prompt Engineering Large Language Models Metadata 52

The MLOps Blog

DECEMBER 26, 2024

makes it easy for RAG developers to track evaluation metrics and metadata, enabling them to analyze and compare different system configurations. Further, LangChain offers features for prompt engineering, like templates and example selectors. The framework also contains a collection of tools that can be called by LLM agents.

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LLM Metadata OpenAI Chatbots 96

Flipboard

JANUARY 24, 2025

Sensitive information disclosure is a risk with LLMs because malicious prompt engineering can cause LLMs to accidentally reveal unintended details in their responses. You can build a segmented access solution on top of a knowledge base using metadata and filtering feature. This can lead to privacy and confidentiality violations.

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AWS Machine Learning Blog

FEBRUARY 12, 2025

You can use metadata filtering to narrow down search results by specifying inclusion and exclusion criteria. For more information on application security, refer to Safeguard a generative AI travel agent with prompt engineering and Amazon Bedrock Guardrails.

Auto-classification 97

Auto-classification Metadata Generative AI Machine Learning 97

Marktechpost

JULY 25, 2024

Introduction to Large Language Models Difficulty Level: Beginner This course covers large language models (LLMs), their use cases, and how to enhance their performance with prompt tuning. Students will learn to write precise prompts, edit system messages, and incorporate prompt-response history to create AI assistant and chatbot behavior.

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Large Language Models Prompt Engineer Prompt Engineering Chatbots 111

ODSC - Open Data Science

AUGUST 24, 2023

Evolving Trends in Prompt Engineering for Large Language Models (LLMs) with Built-in Responsible AI Practices Editor’s note: Jayachandran Ramachandran and Rohit Sroch are speakers for ODSC APAC this August 22–23. This trainable custom model can then be progressively improved through a feedback loop as shown above.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Responsible AI 52

AWS Machine Learning Blog

DECEMBER 5, 2024

Used alongside other techniques such as prompt engineering, RAG, and contextual grounding checks, Automated Reasoning checks add a more rigorous and verifiable approach to enhancing the accuracy of LLM-generated outputs.

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Responsible AI AI Tools AI AI 111

AWS Machine Learning Blog

AUGUST 8, 2024

They used the metadata layer (schema information) over their data lake consisting of views (tables) and models (relationships) from their data reporting tool, Looker , as the source of truth. Refine your existing application using strategic methods such as prompt engineering , optimizing inference parameters and other LookML content.

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Metadata LLM Prompt Engineering Prompt Engineer 129

AWS Machine Learning Blog

JANUARY 28, 2025

By documenting the specific model versions, fine-tuning parameters, and prompt engineering techniques employed, teams can better understand the factors contributing to their AI systems performance. This record-keeping allows developers and researchers to maintain consistency, reproduce results, and iterate on their work effectively.

LLM 115

LLM Large Language Models ML Algorithm 115

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. Salesforce may or may not have invented prompt engineering, a claim Benioff also made in the keynote evoking perhaps the “Austin Powers” Dr.

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AI AI Prompt Engineering Prompt Engineer 189

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 116

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 126

AWS Machine Learning Blog

OCTOBER 6, 2023

Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks. Generative AI developers can use frameworks like LangChain , which offers modules for integrating with LLMs and orchestration tools for task management and prompt engineering.

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Generative AI LLM Natural Language Processing Metadata 141

Unite.AI

SEPTEMBER 25, 2023

MusicLM Performance, Image source: here Stability Audio Stability AI last week introduced “ Stable Audio ” a latent diffusion model architecture conditioned on text metadata alongside audio file duration and start time.

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Generative AI Deep Learning Algorithm AI 296

Marktechpost

MAY 30, 2024

Inspect Rich Documents with Gemini Multimodality and Multimodal RAG This course covers using multimodal prompts to extract information from text and visual data and generate video descriptions with Gemini. Prompt Design in Vertex AI This course covers prompt engineering, image analysis, and multimodal generative techniques in Vertex AI.

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Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

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 62

AWS Machine Learning Blog

AUGUST 9, 2024

The embedding representations of text chunks along with related metadata are indexed in OpenSearch Service. In addition to the embedding vector, the text chunk and document metadata such as document, document section name, or document release date are also added to the index as text fields.

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Data Ingestion Metadata LLM Generative AI 133

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 94

AWS Machine Learning Blog

JUNE 25, 2024

Operational efficiency Uses prompt engineering, reducing the need for extensive fine-tuning when new categories are introduced. Prerequisites This post is intended for developers with a basic understanding of LLM and prompt engineering. A prompt is natural language text describing the task that an AI should perform.

Automation 129

Automation Prompt Engineering Prompt Engineer Categorization 129

AWS Machine Learning Blog

MAY 30, 2024

The workflow for NLQ consists of the following steps: A Lambda function writes schema JSON and table metadata CSV to an S3 bucket. The wrapper function reads the table metadata from the S3 bucket. The wrapper function creates a dynamic prompt template and gets relevant tables using Amazon Bedrock and LangChain.

Metadata 132

Metadata Generative AI LLM Prompt Engineering 132

AWS Machine Learning Blog

MAY 21, 2024

However, when the article is complete, supporting information and metadata must be defined, such as an article summary, categories, tags, and related articles. 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 140

IBM Journey to AI blog

JULY 17, 2023

offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting. These Slate models are fine-tuned via Jupyter notebooks and APIs. To bridge the tuning gap, watsonx.ai

Machine Learning 186

Machine Learning Metadata Automation AI 186

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

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. Unfortunately, they often hallucinate, especially when unintentional prompt engineering is involved. If algorithms were always accurate, the black box problem wouldn’t be an issue.

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NLP Automation AI Algorithm 147

AWS Machine Learning Blog

JUNE 13, 2023

An AWS Glue crawler is scheduled to run at frequent intervals to extract metadata from databases and create table definitions in the AWS Glue Data Catalog. LangChain, a tool to work with LLMs and prompts, is used in Studio notebooks. However, these databases must have their metadata registered with the AWS Glue Data Catalog.

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Generative AI Metadata LLM Large Language Models 99

Flipboard

DECEMBER 6, 2023

Given the right context, metadata, and instructions, a well-selected general purpose LLM can produce good-quality SQL as long as it has access to the right domain-specific context. Further performance optimization involved fine-tuning the query generation process using efficient prompt engineering techniques.

Chatbots 168

Chatbots LLM Prompt Engineering Prompt Engineer 168

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.

Chatbots 133

Chatbots Prompt Engineering Prompt Engineer Large Language Models 133

The MLOps Blog

JUNE 27, 2023

The platform also offers features for hyperparameter optimization, automating model training workflows, model management, prompt engineering, and no-code ML app development. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

JULY 3, 2024

We use prompt engineering to send our summarization instructions to the LLM. Importantly, when performed, summarization should preserve as much article’s metadata as possible, such as the title, authors, date, etc. We can guide the LLM further with few-shot examples illustrating, for instance, the citation styles.

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Generative AI LLM Large Language Models Machine Learning 134

Heartbeat

JANUARY 19, 2024

As prompt engineering is fundamentally different from training machine learning models, Comet has released a new SDK tailored for this use case comet-llm. In this article you will learn how to log the YOLOPandas prompts with comet-llm, keep track of the number of tokens used in USD($), and log your metadata.

LLM 52

LLM Metadata Prompt Engineering Prompt Engineer 52

AWS Machine Learning Blog

SEPTEMBER 15, 2023

Often, these LLMs require some metadata about available tools (descriptions, yaml, or JSON schema for their input parameters) in order to output tool invocations. We use prompt engineering only and Flan-UL2 model as-is without fine-tuning. You have access to the following tools.

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LLM Prompt Engineering Prompt Engineer Large Language Models 132

AWS Machine Learning Blog

AUGUST 21, 2024

We provide a list of reviews as context and create a prompt to generate an output with a concise summary, overall sentiment, confidence score of the sentiment, and action items from the input reviews. Our example prompt requests the FM to generate the response in JSON format.

Generative AI 129

Generative AI Prompt Engineering Prompt Engineer Automation 129

Mlearning.ai

JULY 8, 2023

Prompt Engineering — this is where figuring out what is the right prompt to use for the problem. Model selection can be based on use case, performance, cost, latency, etc Test and validate the prompt engineering and see the output with application is as expected. original article —  Samples2023/LLM/llmops.md

Large Language Models 52

Large Language Models LLM Prompt Engineer Prompt Engineering 52

AWS Machine Learning Blog

OCTOBER 24, 2023

For example, we can follow prompt engineering best practices to fine-tune an LLM to format dates into MM/DD/YYYY format, which may be compatible with a database DATE column. The following code block shows an example of how this is done using an LLM and prompt engineering.

IDP 139

IDP LLM Prompt Engineering Prompt Engineer 139

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. In this case, the model choice needs to be revisited or further prompt engineering needs to be done.

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Auto-classification LLM Prompt Engineering Prompt Engineer 139