AWS Machine Learning Blog

MAY 17, 2023

AWS delivers services that meet customers’ artificial intelligence (AI) and machine learning (ML) needs with services ranging from custom hardware like AWS Trainium and AWS Inferentia to generative AI foundation models (FMs) on Amazon Bedrock. These models span tasks like text-to-text, text-to-image, text-to-embedding, and more.

Large Language Models 68

Large Language Models Auto-complete Generative AI ML 68

AWS Machine Learning Blog

MAY 7, 2024

Large language models (LLMs) have unlocked new possibilities for extracting information from unstructured text data. By handling most of the heavy lifting, services like Amazon SageMaker JumpStart remove the complexity of fine-tuning and deploying these models.

Prompt Engineer 89

Prompt Engineer Prompt Engineering Large Language Models LLM 89

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 91

Chatbots Prompt Engineer Prompt Engineering Large Language Models 91

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 Engineer Prompt Engineering 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

OCTOBER 6, 2023

Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. One such component is a feature store, a tool that stores, shares, and manages features for machine learning (ML) models.

Generative AI 105

Generative AI LLM Natural Language Processing Metadata 105

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

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 LLM Metadata Deep Learning 52

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

IBM Journey to AI blog

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

Machine Learning 157

Machine Learning AI AI Metadata 157

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 93

Metadata Generative AI LLM Prompt Engineer 93

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 69

Generative AI Metadata LLM Large Language Models 69

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. Our approach applies to both open-source and proprietary models equally.

Generative AI 97

Generative AI Prompt Engineer Prompt Engineering AI 97

Heartbeat

FEBRUARY 8, 2024

The recent rise of Large Language Models (LLMs) has been a game changer for the ChatBot industry. These models are trained on extensive data and have been the driving force behind conversational tools like BARD and ChatGPT. The rest are optional like prompt template, metadata, tags, etc.

Conversational AI 52

Conversational AI Chatbots LLM Prompt Engineer 52

Flipboard

NOVEMBER 24, 2023

Many customers are building generative AI apps on Amazon Bedrock and Amazon CodeWhisperer to create code artifacts based on natural language. Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. The SnapLogic pipeline is rendered to the user in a visual friendly manner.

ETL 112

ETL Prompt Engineer Prompt Engineering Generative AI 112

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 95

LLM Prompt Engineer Prompt Engineering Large Language Models 95

Mlearning.ai

JUNE 17, 2023

outputsearch)), Char(10),""), """","") Goal is to use semantic search get the top 3 docs and then pass that with prompt engineering to chatgpt and get the response back and display it in power apps original article —  Samples2023/pinesearchgpt.md

Metadata 52

Metadata Prompt Engineer Prompt Engineering AI 52

Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. Then we’re going to talk about adapting foundation models for the enterprise and how that affects the ML lifecycle, and what we need to potentially add to the lifecycle.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

I am Ali Arsanjani, and I lead partner engineering for Google Cloud, specializing in the area of AI-ML, and I’m very happy to be here today with everyone. Then we’re going to talk about adapting foundation models for the enterprise and how that affects the ML lifecycle, and what we need to potentially add to the lifecycle.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

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 130

Chatbots LLM Prompt Engineer Prompt Engineering 130

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). Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. The second action takes the JSON output and standardizes the date format.

IDP 107

IDP LLM Prompt Engineer Prompt Engineering 107

AWS Machine Learning Blog

NOVEMBER 29, 2023

In the last few years Large Language Models (LLMs) have risen to prominence as outstanding tools capable of understanding, generating and manipulating text with unprecedented proficiency. input prompts comprising input data and query) and define metrics like similarity and toxicity.

LLM 78

LLM Data Scientist Algorithm Generative AI 78

AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them.

Data Scientist 84

Data Scientist Generative AI ML Machine Learning 84