AWS Machine Learning Blog

SEPTEMBER 24, 2024

Goldman Sachs estimated that generative AI could automate 44% of legal tasks in the US. A special report published by Thompson Reuters reported that generative AI awareness is significantly higher among legal professionals, with 91% of respondents saying they have heard of or read about these tools.

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IBM Journey to AI blog

OCTOBER 30, 2024

The enhanced metadata supports the matching categories to internal controls and other relevant policy and governance datasets. These components are built on top of IBM’s leading AI technology, and they can be deployed on any cloud and on prem. Within the IBM watsonx.ai

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AWS Machine Learning Blog

OCTOBER 31, 2024

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. This request contains the user’s message and relevant metadata.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Many commercial generative AI solutions available are expensive and require user-based licenses.

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AWS Machine Learning Blog

SEPTEMBER 28, 2023

In this post, we propose Generative AI Gateway as platform for an enterprise to allow secure access to FMs for rapid innovation. In this post, we define what a Generative AI Gateway is, its benefits, and how to architect one on AWS. What is a Generative AI Gateway?

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AWS Machine Learning Blog

NOVEMBER 14, 2024

This post explores a solution that uses the power of AWS generative AI capabilities like Amazon Bedrock and OpenSearch vector search to perform damage appraisals for insurers, repair shops, and fleet managers. In this solution, Anthropic’s Claude 3 creates the JSON metadata for each image.

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AWS Machine Learning Blog

MAY 21, 2024

For several years, we have been actively using machine learning and artificial intelligence (AI) to improve our digital publishing workflow and to deliver a relevant and personalized experience to our readers. These applications are a focus point for our generative AI efforts.

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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. It also includes guidance on using Google Tools to develop your own Generative AI applications.

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AWS Machine Learning Blog

OCTOBER 27, 2023

Organizations are using AI to improve data-driven decisions, enhance omnichannel experiences, and drive next-generation product development. Enterprises are using generative AI specifically to power their marketing efforts through emails, push notifications, and other outbound communication channels.

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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. As LLMs become integral to AI applications, ethical considerations take center stage.

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AWS Machine Learning Blog

OCTOBER 29, 2024

Organizations can process large datasets more economically because of this significant cost reduction, making it an attractive option for businesses looking to optimize their generative AI processing expenses while maintaining the ability to handle substantial data volumes.

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AWS Machine Learning Blog

MAY 7, 2024

Using generative AI and new multimodal foundation models (FMs) could be very strategic for Veritone and the businesses they serve, because it would significantly improve media indexing and retrieval based on contextual meaning—a critical first step to eventually generating new content.

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AWS Machine Learning Blog

MAY 14, 2024

Recent advances in artificial intelligence have led to the emergence of generative AI that can produce human-like novel content such as images, text, and audio. An important aspect of developing effective generative AI application is Reinforcement Learning from Human Feedback (RLHF).

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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. The second step is Q&A, as shown in the following diagram.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Customers across all industries are experimenting with generative AI to accelerate and improve business outcomes. They contribute to the effectiveness and feasibility of generative AI applications across various domains.

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IBM Journey to AI blog

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Generative AI chatbots have been known to insult customers and make up facts.

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IBM Journey to AI blog

DECEMBER 4, 2023

The AI Ethics Board: a central, cross-disciplinary body that supports a centralized governance, review and decision-making process for IBM ethics policies, practices, communications, research, products and services. The Board recently published its point of view on foundation models addressing the risks that generative AI poses.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications.

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NVIDIA

MAY 1, 2024

Gemma was developed from the same research and technology used to create the company’s Gemini models and is built for responsible AI development. ChatRTX also now supports ChatGLM3, an open, bilingual (English and Chinese) LLM based on the general language model framework. AI powers other elements of the Remix workflow, too.

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AWS Machine Learning Blog

SEPTEMBER 20, 2024

In this post, we demonstrate how to use Amazon Bedrock Agents with a web search API to integrate dynamic web content in your generative AI application. Amazon Q, AWS's generative AI assistant, has been integrated with Smartsheet to provide AI-powered assistance to employees.

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AWS Machine Learning Blog

SEPTEMBER 13, 2024

Set up the policy documents and metadata in the data source for the knowledge base We use Amazon Bedrock Knowledge Bases to manage our documents and metadata. Upload a few insurance policy documents and metadata documents to the S3 bucket to mimic the naming conventions as shown in the following screenshot.

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IBM Journey to AI blog

APRIL 11, 2024

This year the World Economic Forum’s AI Governance Alliance this year published the Presidio AI Framework ( PDF ). It “…provides a structured approach to the safe development, deployment and use of generative AI. ” Academic and scientific perspectives are also essential.

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Towards AI

AUGUST 8, 2024

Manifest relies on runtime metadata, such as a function’s name, docstring, arguments, and type hints. It uses this metadata to compose a prompt and sends it to an LLM. Feedback Loops in Generative AI: How AI May Shoot Itself in the Foot by Anthony Demeusy Generative AI can enhance creativity, but beware of feedback loops!

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AWS Machine Learning Blog

SEPTEMBER 26, 2024

Generative AI is a modern form of machine learning (ML) that has recently shown significant gains in reasoning, content comprehension, and human interaction. But first, let’s revisit some basic concepts around Retrieval Augmented Generation (RAG) applications.

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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. When a user queries the contents of the audio files through a generative AI application or AWS Lambda function, it makes an API call to Knowledge Bases for Amazon Bedrock.

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Flipboard

AUGUST 6, 2023

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. Moreover, it saves metadata about model-generated content, facilitating tracking of AI-generated code within the workflow.

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Marktechpost

AUGUST 7, 2024

As a result, the AI community faces significant barriers to transparency, reproducibility, and trust. The MOF provides a classification system that ranks AI models based on completeness and openness. Image Source The MOF also introduces a classification system with three levels: Class I, Class II, and Class III.

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AWS Machine Learning Blog

JUNE 11, 2024

Wiz has harnessed the power of generative AI to help organizations remove risks in their cloud environment faster. With Wiz’s new integration with Amazon Bedrock , Wiz customers can now generate guided remediation steps backed by foundation models (FMs) running on Amazon Bedrock to reduce their mean time to remediation (MTTR).

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IBM Journey to AI blog

FEBRUARY 22, 2024

The CDAO includes five ethical principles of responsible, equitable, traceable, reliable, and governable as part of its responsible AI toolkit. Based on the US military’s existing ethics framework, these principles are grounded in the military’s values and help uphold its commitment to responsible AI.

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AWS Machine Learning Blog

AUGUST 21, 2024

This post discusses how LLMs can be accessed through Amazon Bedrock to build a generative AI solution that automatically summarizes key information, recognizes the customer sentiment, and generates actionable insights from customer reviews. Also, make sure you don’t include any customer information in the prompt to the FM.

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John Snow Labs

SEPTEMBER 19, 2024

The award, totaling $299,208 for one year, will be used for research and development of LLMs for automated named entity recognition (NER), relation extraction, and ontology metadata enrichment from free-text clinical notes.

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AWS Machine Learning Blog

MAY 22, 2024

With the advancement of Generative AI , we can use vision-language models (VLMs) to predict product attributes directly from images. You can use a managed service, such as Amazon Rekognition , to predict product attributes as explained in Automating product description generation with Amazon Bedrock.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

In the context of generative AI , significant progress has been made in developing multimodal embedding models that can embed various data modalities—such as text, image, video, and audio data—into a shared vector space. Retrieve images stored in S3 bucket response = s3.list_objects_v2(Bucket=BUCKET_NAME) Engine : Select nmslib.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

structured: | Process the pdf invoice and list all metadata and values in json format for the variables with descriptions in tags. She is passionate about using Generative AI in a responsible manner whether that is driving product innovation, boost productivity or enhancing customer experiences.

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AWS Machine Learning Blog

JULY 30, 2024

It allows you to privately customize them with your enterprise data using techniques like Retrieval Augmented Generation (RAG), and build agents that run tasks using your enterprise systems and data sources. He focuses on Generative AI and Serverless technologies, helping customers make the best use of AWS services.

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AWS Machine Learning Blog

JUNE 25, 2024

It provides a broad set of capabilities like model customization through fine-tuning, knowledge base integration for contextual responses, and agents for running complex multi-step tasks across systems. Its enterprise-grade security, privacy controls, and responsible AI features enable secure and trustworthy generative AI innovation at scale.

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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.

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