AI News

MARCH 4, 2024

In an advisory issued by India’s Ministry of Electronics and Information Technology (MeitY) last Friday, it was declared that any AI technology still in development must acquire explicit government permission before being released to the public.

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Large Language Models Big Data Metadata LLM 339

Marktechpost

JULY 25, 2024

Large Language Models (LLMs) have revolutionized AI with their ability to understand and generate human-like text. Learning about LLMs is essential to harness their potential for solving complex language tasks and staying ahead in the evolving AI landscape.

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Large Language Models Prompt Engineer Prompt Engineering Chatbots 111

Towards AI

OCTOBER 10, 2024

The evolution of Large Language Models (LLMs) allowed for the next level of understanding and information extraction that classical NLP algorithms struggle with. This article will focus on LLM capabilities to extract meaningful metadata from product reviews, specifically using OpenAI API. pros** (`List[str]`).

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Metadata LLM Algorithm Large Language Models 119

Unite.AI

MARCH 26, 2025

With so many converging factors, aggregating and assessing this information can be confusing and convoluted, which in some cases can lead to suboptimal decisions on trial sites. Healthtech companies adopting AI are also developing tools that help physicians to quickly and accurately determine eligible trials for patients.

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Artificial Intelligence Artificial Intelligence Metadata Large Language Models 162

Google Research AI blog

AUGUST 18, 2023

Posted by Ziniu Hu, Student Researcher, and Alireza Fathi, Research Scientist, Google Research, Perception Team There has been great progress towards adapting large language models (LLMs) to accommodate multimodal inputs for tasks including image captioning , visual question answering (VQA) , and open vocabulary recognition.

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Large Language Models LLM Computer Vision Metadata 92

Flipboard

NOVEMBER 19, 2024

Solution overview By combining the powerful vector search capabilities of OpenSearch Service with the access control features provided by Amazon Cognito , this solution enables organizations to manage access controls based on custom user attributes and document metadata. For more information, see Getting started with the AWS CDK.

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Generative AI Metadata Robotics LLM 123

Marktechpost

AUGUST 24, 2024

Retrieval Augmented Generation (RAG) represents a cutting-edge advancement in Artificial Intelligence, particularly in NLP and Information Retrieval (IR). This integration allows LLMs to perform more accurately and effectively in knowledge-intensive tasks, especially where proprietary or up-to-date information is crucial.

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Large Language Models Metadata Artificial Intelligence Artificial Intelligence 73

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.

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Generative AI LLM AI AI 158

AWS Machine Learning Blog

JULY 2, 2024

Knowledge bases allow Amazon Bedrock users to unlock the full potential of Retrieval Augmented Generation (RAG) by seamlessly integrating their company data into the language model’s generation process. Metadata filtering gives you more control over the RAG process for better results tailored to your specific use case needs.

Metadata 122

Metadata Generative AI Python Computer Vision 122

Marktechpost

SEPTEMBER 6, 2023

GPT3, LaMDA, PALM, BLOOM, and LLaMA are just a few examples of large language models (LLMs) that have demonstrated their ability to store and apply vast amounts of information. For many reasons, it is difficult for today’s most advanced vision-language models (VLMs) to respond satisfactorily to such inquiries.

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Large Language Models LLM Metadata AI 136

Marktechpost

OCTOBER 27, 2024

Formal theorem proving has emerged as a critical benchmark for assessing the reasoning capabilities of large language models (LLMs), with significant implications for mathematical automation. The earliest breakthrough came with next tactic prediction, where models generate the next proof step based on the current proof state.

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Large Language Models Metadata Inference Engine Automation 100

Unite.AI

JANUARY 29, 2025

Instead of solely focusing on whos building the most advanced models, businesses need to start investing in robust, flexible, and secure infrastructure that enables them to work effectively with any AI model, adapt to technological advancements, and safeguard their data. Did we over-invest in companies like OpenAI and NVIDIA? .”

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LLM Explainability AI AI 165

Flipboard

MARCH 4, 2025

Integration with the AWS Well-Architected Tool pre-populates workload information and initial assessment responses. Metadata filtering is used to improve retrieval accuracy. The WAFR Accelerator application retrieves the review status from the DynamoDB table to keep the user informed.

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Generative AI Prompt Engineer Prompt Engineering AI 163

Flipboard

MARCH 7, 2025

Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks.

Generative AI 149

Generative AI Prompt Engineer Prompt Engineering Software Development 149

AssemblyAI

OCTOBER 16, 2023

LlamaIndex is a flexible data framework for connecting custom data sources to Large Language Models (LLMs). The metadata contains the full JSON response of our API with more meta information: print(docs[0].metadata) With LlamaIndex, you can easily store and index your data and then apply LLMs.  print(docs[0].text)

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Python Metadata Large Language Models OpenAI 200

Marktechpost

MARCH 18, 2025

Retrieval-augmented generation ( RAG ) has emerged as a powerful paradigm for enhancing the capabilities of large language models (LLMs). Often support for metadata filtering alongside vector search Popular vector databases include FAISS (Facebook AI Similarity Search), Pinecone, Weaviate, Milvus, and Chroma.

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Metadata LLM Auto-complete Neural Network 88

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. As the community explores these techniques, tools like LlamaIndex are now gaining attention.

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LLM OpenAI Prompt Engineer Prompt Engineering 304

AWS Machine Learning Blog

DECEMBER 5, 2023

Structured data, defined as data following a fixed pattern such as information stored in columns within databases, and unstructured data, which lacks a specific form or pattern like text, images, or social media posts, both continue to grow as they are produced and consumed by various organizations.

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Metadata Auto-classification Auto-complete Content Enrichment 118

Flipboard

FEBRUARY 10, 2025

Multimodal Capabilities in Detail Configuring Your Development Environment Project Structure Implementing the Multimodal Chatbot Setting Up the Utilities (utils.py) Designing the Chatbot Logic (chatbot.py) Building the Interface (app.py) Summary Citation Information Building a Multimodal Gradio Chatbot with Llama 3.2 ollama/models directory.

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Chatbots Computer Vision Deep Learning Large Language Models 146

AWS Machine Learning Blog

MAY 7, 2024

Veritone’s current media search and retrieval system relies on keyword matching of metadata generated from ML services, including information related to faces, sentiment, and objects. With recent advances in large language models (LLMs), Veritone has updated its platform with these powerful new AI capabilities.

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Metadata Generative AI Machine Learning Large Language Models 124

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. BedrockKBRetrieverTool enables CrewAI agents to retrieve information from Amazon Bedrock Knowledge Bases using natural language queries.

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LLM Automation Generative AI AI Automation 177

AWS Machine Learning Blog

NOVEMBER 26, 2024

Large language models (LLMs) have come a long way from being able to read only text to now being able to read and understand graphs, diagrams, tables, and images. In this post, we discuss how to use LLMs from Amazon Bedrock to not only extract text, but also understand information available in images. 90B Vision model.

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LLM Convolutional Neural Networks Metadata Explainability 97

AWS Machine Learning Blog

MARCH 20, 2025

In a world whereaccording to Gartner over 80% of enterprise data is unstructured, enterprises need a better way to extract meaningful information to fuel innovation. This is particularly valuable for industries handling large document volumes, where rapid access to specific information is crucial.

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Automation IDP Generative AI Prompt Engineer 106

AWS Machine Learning Blog

APRIL 3, 2025

Data synthesis: The assistant can pull relevant information from multiple sources including from our customer relationship management (CRM) system, financial reports, news articles, and previous APs to provide a holistic view of our customers. Its a game-changer for serving my full portfolio of accounts.

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Generative AI Metadata Software Development AI 87

AssemblyAI

AUGUST 31, 2023

LangChain is a framework for developing applications powered by Large Language Models (LLMs). The metadata contains the full JSON response of our API with more meta information: print(docs[0].metadata) LLMs only work with textual data, so to process audio files with LLMs we first need to transcribe them into text.

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Python Metadata Large Language Models LLM 217

Flipboard

FEBRUARY 16, 2023

For more information, refer to Using the AWS CloudFormation console. After you SSH into the head node, you can verify the compute fleet and their status with a Slurm command such as sinfo to view the node information for the system. The model checkpoint and output log per each compute node are also captured in this directory.

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Large Language Models LLM BERT Deep Learning 130

AWS Machine Learning Blog

MARCH 20, 2025

With robust security measures, data privacy safeguards, and a cost-effective pay-as-you-go model, Amazon Bedrock offers a secure, flexible, and cost-efficient service to harness generative AIs potential in enhancing customer service analytics, ultimately leading to improved customer experiences and operational efficiencies.

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Generative AI Metadata AI AI 74

AWS Machine Learning Blog

MARCH 18, 2025

SQL is one of the key languages widely used across businesses, and it requires an understanding of databases and table metadata. This application allows users to ask questions in natural language and then generates a SQL query for the users request. This can be overwhelming for nontechnical users who lack proficiency in SQL.

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LLM Metadata Large Language Models Python 92

Unite.AI

FEBRUARY 26, 2024

The advent of Multimodal Large Language Models (MLLM) has ushered in a new era of mobile device agents, capable of understanding and interacting with the world through text, images, and voice.

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Large Language Models Metadata Natural Language Processing Categorization 214

AWS Machine Learning Blog

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders). langsmith==0.0.43 pgvector==0.2.3 streamlit==1.28.0

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Chatbots Prompt Engineer Prompt Engineering Large Language Models 123

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. Regular interval evaluation also allows organizations to stay informed about the latest advancements, making informed decisions about upgrading or switching models.

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LLM Large Language Models ML Algorithm 95

AWS Machine Learning Blog

NOVEMBER 7, 2024

AI agents , powered by large language models (LLMs), can analyze complex customer inquiries, access multiple data sources, and deliver relevant, detailed responses. These indexes enable efficient searching and retrieval of part data and vehicle information, providing quick and accurate results.

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DevOps Generative AI Python Automation 122

AWS Machine Learning Blog

MARCH 12, 2024

In this post, we discuss how Leidos worked with AWS to develop an approach to privacy-preserving large language model (LLM) inference using AWS Nitro Enclaves. LLMs are designed to understand and generate human-like language, and are used in many industries, including government, healthcare, financial, and intellectual property.

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Large Language Models LLM Chatbots Natural Language Processing 109

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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Prompt Engineer Prompt Engineering Large Language Models LLM 115

AWS Machine Learning Blog

NOVEMBER 30, 2023

Reports holistically summarize each evaluation in a human-readable way, through natural-language explanations, visualizations, and examples, focusing annotators and data scientists on where to optimize their LLMs and help make informed decisions. What is FMEval? We use datasets such as BoolQ , NaturalQuestions , and TriviaQA.

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Large Language Models Algorithm LLM Responsible AI 105

Marktechpost

JANUARY 7, 2025

Models typically treat all input data equivalently, disregarding contextual cues about the source or style. This approach has two primary shortcomings: Missed Contextual Signals : Without considering metadata such as source URLs, LMs overlook important contextual information that could guide their understanding of a texts intent or quality.

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Metadata Natural Language Processing LLM ML 85

Towards AI

FEBRUARY 17, 2025

RAFT vs Fine-Tuning Image created by author As the use of large language models (LLMs) grows within businesses, to automate tasks, analyse data, and engage with customers; adapting these models to specific needs (e.g., Security: Secure sensitive data with access control (role-based) and metadata.

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Data Drift LLM Automation Metadata 95