Unite.AI

OCTOBER 25, 2023

Large language models (LLMs) like OpenAI's GPT series have been trained on a diverse range of publicly accessible data, demonstrating remarkable capabilities in text generation, summarization, question answering, and planning. But the drawback for this is its reliance on the skill and expertise of the user in prompt engineering.

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AWS Machine Learning Blog

MARCH 20, 2025

Additionally, large language model (LLM)-based analysis is applied to derive further insights, such as video summaries and classifications. These analytics are implemented with either Amazon Comprehend , or separate prompt engineering with FMs.

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Flipboard

JANUARY 24, 2025

In this post, we show you an example of a generative AI assistant application and demonstrate how to assess its security posture using the OWASP Top 10 for Large Language Model Applications , as well as how to apply mitigations for common threats. This can lead to privacy and confidentiality violations.

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AWS Machine Learning Blog

DECEMBER 5, 2023

Enterprises may want to add custom metadata like document types (W-2 forms or paystubs), various entity types such as names, organization, and address, in addition to the standard metadata like file type, date created, or size to extend the intelligent search while ingesting the documents.

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AWS Machine Learning Blog

MARCH 13, 2025

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.

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deepsense.ai

JULY 30, 2023

To start simply, you could think of LLMOps ( Large Language Model Operations) as a way to make machine learning work better in the real world over a long period of time. As previously mentioned: model training is only part of what machine learning teams deal with. What is LLMOps? Why are these elements so important?

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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.

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AWS Machine Learning Blog

JANUARY 28, 2025

Evaluating large language models (LLMs) is crucial as LLM-based systems become increasingly powerful and relevant in our society. Furthermore, evaluation processes are important not only for LLMs, but are becoming essential for assessing prompt template quality, input data quality, and ultimately, the entire application stack.

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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

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Flipboard

MARCH 31, 2025

Agentic design An AI agent is an autonomous, intelligent system that uses large language models (LLMs) and other AI capabilities to perform complex tasks with minimal human oversight. Amazon Bedrock manages prompt engineering, memory, monitoring, encryption, user permissions, and API invocation.

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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 90

Mlearning.ai

JULY 8, 2023

Prompt Engineering — this is where figuring out what is the right prompt to use for the problem. Develop the LLM application using existing models or train a new model. Storage all prompts and completions in a data lake for future use and also metadata about api, configurations etc.

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Large Language Models LLM Prompt Engineer Prompt Engineering 52

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. TensorFlow on Google Cloud This course covers designing TensorFlow input data pipelines and building ML models with TensorFlow and Keras.

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AWS Machine Learning Blog

MAY 17, 2023

The performance and quality of the models also improved drastically with the number of parameters. These models span tasks like text-to-text, text-to-image, text-to-embedding, and more. You can use large language models (LLMs), more specifically, for tasks including summarization, metadata extraction, and question answering.

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Large Language Models Auto-complete ML Generative AI 89

Marktechpost

MARCH 26, 2025

Large Language Models (LLMs) are becoming integral to modern technology, driving agentic systems that interact dynamically with external environments. Despite their impressive capabilities, LLMs are highly vulnerable to prompt injection attacks. The overhead primarily manifests in token usage, with approximately a 2.82

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Heartbeat

SEPTEMBER 19, 2023

I’m so excited to talk to you about Language Models! They’re these incredible creations called Large Language Models (LLMs) that have the power to understand and generate human-like text. Comet’s LLMOps tool provides an intuitive and responsive view of our prompt history. Image by Author Hey there!

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John Snow Labs

OCTOBER 16, 2023

The recent NLP Summit served as a vibrant platform for experts to delve into the many opportunities and also challenges presented by large language models (LLMs). Implementation Hurdles: For these top performers, 24% see the models and tools as their primary challenge, followed by talent acquisition (20%) and scaling (19%).

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AWS Machine Learning Blog

MAY 7, 2024

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. This post walks through examples of building information extraction use cases by combining LLMs with prompt engineering and frameworks such as LangChain.

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AWS Machine Learning Blog

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks.

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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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IBM Journey to AI blog

JULY 17, 2023

.” Sean Im, CEO, Samsung SDS America “In the field of generative AI and foundation models, watsonx is a platform that will enable us to meet our customers’ requirements in terms of optimization and security, while allowing them to benefit from the dynamism and innovations of the open-source community.”

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AWS Machine Learning Blog

AUGUST 8, 2024

This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock. 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.

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AWS Machine Learning Blog

MAY 30, 2024

Hosting large language models Vitech explored the option of hosting Large Language Models (LLMs) models using Amazon Sagemaker. Vitech needed a fully managed and secure experience to host LLMs and eliminate the undifferentiated heavy lifting associated with hosting 3P models.

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AWS Machine Learning Blog

JULY 3, 2024

Generative AI and transformer-based large language models (LLMs) have been in the top headlines recently. These models demonstrate impressive performance in question answering, text summarization, code, and text generation. We use prompt engineering to send our summarization instructions to the LLM.

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AWS Machine Learning Blog

AUGUST 9, 2024

Retrieval Augmented Generation (RAG) has emerged as a leading method for using the power of large language models (LLMs) to interact with documents in natural language. The text embedding model processes the text chunks and generates embedding vectors for each text chunk.

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AWS Machine Learning Blog

MAY 21, 2024

With the advent of generative AI, and in particular large language models (LLMs), we have now adopted an AI by design strategy, evaluating the application of AI for every new technology product we develop. We use a single-shot prompt with the full article text in context to generate the summary.

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AWS Machine Learning Blog

JUNE 25, 2024

Large language models (LLMs) have transformed the way we engage with and process natural language. These powerful models can understand, generate, and analyze text, unlocking a wide range of possibilities across various domains and industries.

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Automation Prompt Engineering Prompt Engineer Categorization 125

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.

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AWS Machine Learning Blog

JUNE 13, 2023

The latest offering for generative AI from AWS is Amazon Bedrock , which is a fully managed service and the easiest way to build and scale generative AI applications with foundation models. AWS also offers foundation models through Amazon SageMaker JumpStart as Amazon SageMaker endpoints. LangChain requires an LLM to be defined.

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The MLOps Blog

JUNE 27, 2023

W&B (Weights & Biases) W&B is a machine learning platform for your data science teams to track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results, spot regressions, and share findings with colleagues. Can you find experiments and models easily?

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AWS Machine Learning Blog

SEPTEMBER 15, 2023

Large language model (LLM) agents are programs that extend the capabilities of standalone LLMs with 1) access to external tools (APIs, functions, webhooks, plugins, and so on), and 2) the ability to plan and execute tasks in a self-directed fashion. We use prompt engineering only and Flan-UL2 model as-is without fine-tuning.

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LLM Prompt Engineering Prompt Engineer Large Language Models 127

Flipboard

DECEMBER 6, 2023

Experimentation and challenges It was clear from the beginning that to understand a human language question and generate accurate answers, Q4 would need to use large language models (LLMs). Further performance optimization involved fine-tuning the query generation process using efficient prompt engineering techniques.

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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. He specializes in building ML pipelines using Large Language Models, primarily through Amazon Bedrock and other AWS Cloud services.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. However, bringing such solutions and models to the business-as-usual operations is not an easy task. Only prompt engineering is necessary for better results.

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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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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 Engineering Prompt Engineer 52

Mlearning.ai

FEBRUARY 26, 2024

Image source: Seven Failure Points When Engineering a Retrieval Augmented Generation System I’ll discuss various optimization techniques sourced from different research papers. The majority of these techniques will be based on a research paper I particularly enjoyed, titled “ Retrieval-Augmented Generation for Large Language Models: A Survey.”

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