AWS Machine Learning Blog

AUGUST 8, 2024

Twilio’s use case Twilio wanted to provide an AI assistant to help their data analysts find data in their data lake. 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

Flipboard

AUGUST 6, 2023

The tool connects Jupyter with large language models (LLMs) from various providers, including AI21, Anthropic, AWS, Cohere, and OpenAI, supported by LangChain. Designed with responsible AI and data privacy in mind, Jupyter AI empowers users to choose their preferred LLM, embedding model, and vector database to suit their specific needs.

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence Metadata Large Language Models 123

AWS Machine Learning Blog

SEPTEMBER 13, 2024

The image damage analysis notification agent is responsible for doing a preliminary analysis of the images uploaded for a damage. This agent invokes a Lambda function that internally calls the Anthropic Claude Sonnet large language model (LLM) on Amazon Bedrock to perform preliminary analysis on the images.

Metadata 125

Metadata Automation LLM NLP 125

AWS Machine Learning Blog

MAY 7, 2024

Building enhanced semantic search capabilities that analyze media contextually would lay the groundwork for creating AI-generated content, allowing customers to produce customized media more efficiently. With recent advances in large language models (LLMs), Veritone has updated its platform with these powerful new AI capabilities.

Metadata 119

Metadata Generative AI Machine Learning Large Language Models 119

AWS Machine Learning Blog

NOVEMBER 26, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API. The following screenshot shows the response. You can try out something harder as well.

LLM 97

LLM Convolutional Neural Networks Metadata Explainability 97

Mlearning.ai

JULY 8, 2023

Introduction Create ML Ops for LLM’s Build end to end development and deployment cycle. Add Responsible AI to LLM’s Add Abuse detection to LLM’s. High level process and flow LLM Ops is people, process and technology. LLM Ops flow — Architecture Architecture explained.

Large Language Models 52

Large Language Models LLM Prompt Engineering Prompt Engineer 52

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. are harnessed to channel LLMs output. Auto Eval Common Metric Eval Human Eval Custom Model Eval 3.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Responsible AI 52

AWS Machine Learning Blog

SEPTEMBER 28, 2023

This means companies need loose coupling between app clients (model consumers) and model inference endpoints, which ensures easy switch among large language model (LLM), vision, or multi-modal endpoints if needed. This table will hold the endpoint, metadata, and configuration parameters for the model.

Generative AI 116

Generative AI Metadata Large Language Models AI 116

Unite.AI

JANUARY 23, 2024

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries.

Large Language Models 100

Large Language Models Prompt Engineering Prompt Engineer LLM 100

ODSC - Open Data Science

SEPTEMBER 17, 2024

Fine Tuning Strategies for Language Models and Large Language Models Kevin Noel | AI Lead at Uzabase Speeda | Uzabase Japan-US Language Models (LM) and Large Language Models (LLM) have proven to have applications across many industries. This talk provides a comprehensive framework for securing LLM applications.

LLM 52

LLM Large Language Models Metadata Data Science 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Metadata 83

Metadata Data Ingestion Generative AI Computer Vision 83

The MLOps Blog

JUNE 27, 2023

When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. Can you compare images?

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

MAY 21, 2024

This blog post outlines various use cases where we’re using generative AI to address digital publishing challenges. However, when the article is complete, supporting information and metadata must be defined, such as an article summary, categories, tags, and related articles.

Generative AI 120

Generative AI Prompt Engineer Prompt Engineering Automation 120

Towards AI

AUGUST 8, 2024

Take advantage of the current deal offered by Amazon (depending on location) to get our recent book, “Building LLMs for Production,” with 30% off right now! Featured Community post from the Discord Arwmoffat just released Manifest, a tool that lets you write a Python function and have an LLM execute it.

Neural Network 79

Neural Network Metadata Explainability LLM 79

AWS Machine Learning Blog

OCTOBER 2, 2024

It’s a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like Anthropic, Cohere, Meta, Mistral AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Generative AI 113

Generative AI Data Ingestion AI AI 113

AWS Machine Learning Blog

JUNE 25, 2024

With Amazon Bedrock, developers can experiment, evaluate, and deploy generative AI applications without worrying about infrastructure management. Its enterprise-grade security, privacy controls, and responsible AI features enable secure and trustworthy generative AI innovation at scale. The Step Functions workflow starts.

Automation 118

Automation Prompt Engineering Prompt Engineer Categorization 118

AWS Machine Learning Blog

AUGUST 5, 2024

Finding relevant content usually requires searching through text-based metadata such as timestamps, which need to be manually added to these files. Next, Knowledge Bases for Amazon Bedrock augments the user’s original query with these results to a prompt, which is sent to the large language model (LLM).

Metadata 105

Metadata Python Generative AI LLM 105

AWS Machine Learning Blog

MAY 14, 2024

A second real-time human workflow is initiated as decided by the LLM. We use a simple notification workflow in this post, but you can use any real-time human workflow to take over the AI-human conversation. We also use the same LLM to respond to this internal sentiment prompt check for simplicity.

Generative AI 109

Generative AI LLM Chatbots Machine Learning 109

AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker Clarify now provides AWS customers with foundation model (FM) evaluations, a set of capabilities designed to evaluate and compare model quality and responsibility metrics for any LLM, in minutes. You can use FMEval to evaluate AWS-hosted LLMs such as Amazon Bedrock, Jumpstart and other SageMaker models.

Large Language Models 107

Large Language Models Algorithm LLM Responsible AI 107

AWS Machine Learning Blog

NOVEMBER 7, 2024

In this second part, we expand the solution and show to further accelerate innovation by centralizing common Generative AI components. We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. This logic sits in a hybrid search component.

Generative AI 108

Generative AI AI AI Responsible AI 108

AWS Machine Learning Blog

SEPTEMBER 26, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Chatbots 102

Chatbots Generative AI Metadata LLM 102

AWS Machine Learning Blog

OCTOBER 31, 2024

This request contains the user’s message and relevant metadata. The Lambda function interacts with Amazon Bedrock through its runtime APIs, using either the RetrieveAndGenerate API that connects to a knowledge base, or the Converse API to chat directly with an LLM available on Amazon Bedrock.

Generative AI 119

Generative AI AI AI Python 119

AWS Machine Learning Blog

MAY 22, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Generative AI 124

Generative AI Machine Learning Natural Language Processing Large Language Models 124

AWS Machine Learning Blog

JUNE 20, 2024

It allows LLMs to reference authoritative knowledge bases or internal repositories before generating responses, producing output tailored to specific domains or contexts while providing relevance, accuracy, and efficiency. Generation is the process of generating the final response from the LLM.

Auto-classification 123

Auto-classification LLM Prompt Engineering Prompt Engineer 123

AWS Machine Learning Blog

NOVEMBER 25, 2024

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. Metadata such as the content type, domain, and any relevant tags. The corresponding translation chunk.

Prompt Engineering 89

Prompt Engineering Prompt Engineer Metadata Generative AI 89

AWS Machine Learning Blog

MAY 21, 2024

The solution uses Amazon Bedrock , a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies, providing a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Natural Language Processing 117

Natural Language Processing Metadata ML NLP 117

AWS Machine Learning Blog

SEPTEMBER 20, 2024

required=True, ) }, ), ] ), After the Amazon Bedrock agent determines the API operation that it needs to invoke in an action group, it sends information alongside relevant metadata as an input event to the Lambda function.

Generative AI 100

Generative AI Python Chatbots AI 100

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Below follows a transcript of his talk, lightly edited for readability.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

Snorkel AI

MARCH 2, 2023

Ali Arsanjani, director of cloud partner engineering at Google Cloud , presented a talk entitled “Challenges and Ethics of DLM and LLM Adoption in the Enterprise” at Snorkel AI’s recent Foundation Model Virtual Summit. Below follows a transcript of his talk, lightly edited for readability.

Large Language Models 52

Large Language Models Prompt Engineer Prompt Engineering Neural Network 52

AWS Machine Learning Blog

NOVEMBER 29, 2023

However, harnessing this potential while ensuring the responsible and effective use of these models hinges on the critical process of LLM evaluation. An evaluation is a task used to measure the quality and responsibility of output of an LLM or generative AI service. Who needs to perform LLM evaluation?

LLM 102

LLM Data Scientist Algorithm Generative AI 102

Flipboard

DECEMBER 3, 2024

Agent architecture The following diagram illustrates the serverless agent architecture with standard authorization and real-time interaction, and an LLM agent layer using Amazon Bedrock Agents for multi-knowledge base and backend orchestration using API or Python executors. Domain-scoped agents enable code reuse across multiple agents.

Generative AI 149

Generative AI Metadata Machine Learning Natural Language Processing 149

Unite.AI

AUGUST 8, 2024

While single models are suitable in some scenarios, acting as co-pilots, agentic architectures open the door for LLMs to become active components of business process automation. As such, enterprises should consider leveraging LLM-based multi-agent (LLM-MA) systems to streamline complex business processes and improve ROI.

AI Modeling 157

AI Modeling LLM Automation Responsible AI 157

AWS Machine Learning Blog

DECEMBER 19, 2024

In this blog post, we provide an introduction to preparing your own dataset for LLM training. Whether your goal is to fine-tune a pre-trained modIn this blog post, we provide an introduction to preparing your own dataset for LLM training. The next step is to filter low quality or desirable documents.

LLM 73

LLM Machine Learning Natural Language Processing ML 73

AWS Machine Learning Blog

OCTOBER 11, 2024

This post dives deep into Amazon Bedrock Knowledge Bases , which helps with the storage and retrieval of data in vector databases for RAG-based workflows, with the objective to improve large language model (LLM) responses for inference involving an organization’s datasets. The LLM response is passed back to the agent.

Metadata 96

Metadata Generative AI LLM Data Ingestion 96

AWS Machine Learning Blog

OCTOBER 21, 2024

If you’re starting with no existing schema, the simplest way to provide tool metadata for your agent is to use simple JSON function definitions. You can directly generate the IaC required for creating your agents with function definitions and Lambda connections using generative AI.

Generative AI 85

Generative AI Metadata Software Development AI 85