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

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

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Metadata 52

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.

Large Language Models 52

Large Language Models LLM Prompt Engineering Prompt Engineer 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.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence BERT Computer Vision 131

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!

Large Language Models 52

Large Language Models Metadata LLM Data Scientist 52

Unite.AI

NOVEMBER 20, 2024

The growth of autonomous agents by foundation models (FMs) like Large Language Models (LLMs) has reform how we solve complex, multi-step problems. These agents perform tasks ranging from customer support to software engineering, navigating intricate workflows that combine reasoning, tool use, and memory.

LLM 176

LLM AI AI DevOps 176

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%).

Large Language Models 52

Large Language Models NLP Metadata Data Scarcity 52

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.

Large Language Models 78

Large Language Models Auto-complete ML Generative AI 78

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.

Prompt Engineering 115

Prompt Engineering Prompt Engineer Large Language Models LLM 115

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.”

Machine Learning 186

Machine Learning Metadata Automation AI 186

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.

Generative AI 122

Generative AI LLM Metadata Natural Language Processing 122

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.

Metadata 113

Metadata LLM Prompt Engineering Prompt Engineer 113

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.

Chatbots 120

Chatbots Prompt Engineering Prompt Engineer Large Language Models 120

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 Engineering 89

Prompt Engineering Prompt Engineer Metadata Generative AI 89

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.

Generative AI 119

Generative AI LLM Large Language Models Machine Learning 119

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.

Data Ingestion 119

Data Ingestion Metadata LLM Generative AI 119

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.

Automation 118

Automation Prompt Engineering Prompt Engineer Categorization 118

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.

Generative AI 120

Generative AI Prompt Engineer Prompt Engineering Automation 120

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 123

Metadata Generative AI LLM Prompt Engineering 123

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?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

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.

Chatbots 168

Chatbots LLM Prompt Engineering Prompt Engineer 168

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.

LLM 120

LLM Prompt Engineer Prompt Engineering Large Language Models 120

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.

Generative AI 80

Generative AI Metadata LLM Large Language Models 80

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 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.

Generative AI 115

Generative AI LLM Large Language Models AI 115

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.

Generative AI 122

Generative AI Prompt Engineering Prompt Engineer AI 122

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.

Generative AI 123

Generative AI Prompt Engineer Prompt Engineering Automation 123

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.”

Metadata 52

Metadata Large Language Models LLM Neural Network 52

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

JULY 24, 2024

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You can customize the model using prompt engineering, Retrieval Augmented Generation (RAG), or fine-tuning.

LLM 122

LLM ML Generative AI Machine Learning 122

Heartbeat

OCTOBER 19, 2023

An Introduction to Large Language Models (LLMs) Image credit: shaip.com In the rapidly evolving landscape of artificial intelligence and natural language processing, large language models (LLMs) have emerged as powerful tools capable of understanding, generating, and manipulating human language with unprecedented proficiency.

Large Language Models 52

Large Language Models Metadata LLM Chatbots 52

The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. What is Large Language Model Operations (LLMOps)? What the future of LLMOps looks like.

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models LLM 52

AWS Machine Learning Blog

OCTOBER 24, 2023

In this post, we discuss how to extend a new or existing IDP architecture with large language models (LLMs). 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.

IDP 127

IDP LLM Prompt Engineering Prompt Engineer 127

AWS Machine Learning Blog

JUNE 20, 2024

Retrieval Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by incorporating external knowledge sources. In this case, the model choice needs to be revisited or further prompt engineering needs to be done.

Auto-classification 123

Auto-classification LLM Prompt Engineering Prompt Engineer 123

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 118

Generative AI LLM AI AI 118

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 108

Generative AI AI AI Responsible AI 108

ODSC - Open Data Science

JULY 12, 2024

Topics you will learn: Introduction to Deep Learning with PyTorch and TensorFlow | Self-Supervised Learning in Vision | Multimodal Models | Deep Generative Models | Adversarial Attacks | Applications of Multimodal Models | Latent Diffusion Models LLMs and RAG One of our most popular tracks is getting an upgrade!

Robotics 40

Robotics Deep Learning NLP Large Language Models 40