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.

AI 189

AI AI Prompt Engineer Prompt Engineering 189

Unite.AI

NOVEMBER 20, 2024

Artifacts: Track intermediate outputs, memory states, and prompt templates to aid debugging. Prompt Management Prompt engineering plays an important role in forming agent behavior. Key features include: Versioning: Track iterations of prompts for performance comparison.

LLM 182

LLM AI AI DevOps 182

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.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence BERT Computer Vision 131

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.

Metadata 116

Metadata LLM Prompt Engineer Prompt Engineering 116

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

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 Engineer Prompt Engineering Large Language Models LLM 119

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.

Generative AI 126

Generative AI LLM Metadata Natural Language Processing 126

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.

Prompt Engineer 93

Prompt Engineer Prompt Engineering Metadata Generative AI 93

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.

Data Ingestion 123

Data Ingestion Metadata LLM Generative AI 123

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.

Large Language Models 100

Large Language Models Prompt Engineer Prompt Engineering LLM 100

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 AI AI 186

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 126

Metadata Generative AI LLM Prompt Engineer 126

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 122

Automation Prompt Engineer Prompt Engineering Categorization 122

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 AI 147

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 Engineer Prompt Engineering Automation 124

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.

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Chatbots LLM Prompt Engineer Prompt Engineering 168

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 90

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.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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 124

Chatbots Prompt Engineer Prompt Engineering Large Language Models 124

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.

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LLM Metadata Prompt Engineer Prompt Engineering 52

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 84

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Strong domain knowledge for tuning, including prompt engineering, is required as well. Consumers – Users who interact with generative AI services from providers or fine-tuners by text prompting or a visual interface to complete desired actions. Only prompt engineering is necessary for better results.

Generative AI 125

Generative AI Prompt Engineer Prompt Engineering AI 125

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 126

Generative AI Prompt Engineer Prompt Engineering Automation 126

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

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.

Generative AI 122

Generative AI LLM Large Language Models Machine Learning 122

Bugra Akyildiz

MARCH 16, 2024

Of course, all of the things that control vector does can be done through prompt engineering as well as one can consider control vector to be an “addition” to the prompt that is provided by the user. This is where metadata comes in. Metadata is essentially data about data.

Metadata 59

Metadata LLM Machine Learning Python 59

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.

LLM 124

LLM Prompt Engineer Prompt Engineering Large Language Models 124

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.

Responsible AI 107

Responsible AI AI Tools AI AI 107

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 130

IDP LLM Prompt Engineer Prompt Engineering 130

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 Engineer Prompt Engineering 127

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.

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Prompt Engineer Prompt Engineering Python Data Science 52

AWS Machine Learning Blog

JULY 24, 2024

You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning. By logging your datasets with MLflow, you can store metadata, such as dataset descriptions, version numbers, and data statistics, alongside your MLflow runs.

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LLM ML Generative AI Natural Language Processing 126

AWS Machine Learning Blog

AUGUST 26, 2024

Our human review process is comprehensive and integrated throughout the development lifecycle of the Account Summaries solution, involving a diverse group of stakeholders: Field sellers and the Account Summaries product team – These personas collaborate from the early stages on prompt engineering, data selection, and source validation.

Generative AI 122

Generative AI LLM AI AI 122

AWS Machine Learning Blog

SEPTEMBER 6, 2024

Conclusion In this post, we shared how the AWS GenAIIC team used Anthropic’s Claude on Amazon Bedrock to extract and summarize insights from Vidmob’s performance data using zero-shot prompt engineering. The chatbot built by AWS GenAIIC would take in this tag data and retrieve insights.

Generative AI 119

Generative AI LLM Large Language Models AI 119

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.

Generative AI 111

Generative AI AI AI Responsible AI 111

John Snow Labs

OCTOBER 16, 2023

solves this problem by extracting metadata during the data preparation process. File, page, and section metadata enable users to determine the source of a response, while document publication and modification dates allow retrieval systems to bias toward more recent data. Unstructured.IO Unstructured.IO

Large Language Models 52

Large Language Models NLP Metadata Data Scarcity 52

Mlearning.ai

FEBRUARY 26, 2024

Post-Retrieval Next, the RAG model augments the user input (or prompts) by adding the relevant retrieved data in context (query + context). This step uses prompt engineering techniques to communicate effectively with the LLM. Remove unnecessary information such as special characters, unwanted metadata, or text.

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Metadata Large Language Models LLM Neural Network 52