NVIDIA

MARCH 19, 2025

NVIDIA RTX Blackwell PRO GPUs large GPU memory can further assist with handling massive datasets and spikes in usage without sacrificing performance. Professionals can benefit from high-quality video playback, accelerate video data ingestion and use advanced AI-powered video editing features. 264 and HEVC decode.

Data Ingestion 91

Data Ingestion AI AI Large Language Models 91

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. To use this setup, you'll need to have an OPENAI_API_KEY.

LLM 299

LLM OpenAI Prompt Engineering Prompt Engineer 299

Snorkel AI

DECEMBER 2, 2024

Large language models (LLMs) fine-tuned on proprietary data have become a competitive differentiator for enterprises. When combined with Snorkel Flow, it becomes a powerful enabler for enterprises seeking to harness the full potential of their proprietary data.

Data Ingestion 52

Data Ingestion Large Language Models LLM Machine Learning 52

IBM Journey to AI blog

SEPTEMBER 20, 2023

By ingesting vast amounts of unlabeled data and using self-supervised techniques for model training, FMs have removed these bottlenecks and opened the avenue for widescale adoption of AI across the enterprise. These massive amounts of data that exist in every business are waiting to be unleashed to drive insights.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

AWS Machine Learning Blog

APRIL 3, 2025

Mid-market Account Manager Amazon Q, Amazon Bedrock, and other AWS services underpin this experience, enabling us to use large language models (LLMs) and knowledge bases (KBs) to generate relevant, data-driven content for APs. Its a game-changer for serving my full portfolio of accounts.

Generative AI 89

Generative AI Metadata Software Development AI 89

Snorkel AI

JANUARY 8, 2025

At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Ingesting raw data from Databricks into Snorkel Flow Efficient data ingestion is the foundation of any machine learning project.

AI Developer 52

AI Developer AI Development Data Ingestion LLM 52

Marktechpost

APRIL 9, 2024

Both offer unique approaches to enhancing the performance and functionality of large language models (LLMs), but they cater to the developer community’s slightly different needs and preferences. Engines: The bridge between data sources and LLMs allows seamless data access and interaction.

Artificial Intelligence 117

Artificial Intelligence Artificial Intelligence Large Language Models LLM 117

AWS Machine Learning Blog

FEBRUARY 7, 2025

Amazon Q retrieves relevant information from its index, which is populated using data from the connected data sources (Amazon S3 and a web crawler). Amazon Q then generates a response using its internal large language model (LLM) and presents it to the user through the Amazon Q web UI.

Data Ingestion 72

Data Ingestion Large Language Models Generative AI Automation 72

Unite.AI

NOVEMBER 2, 2023

The book starts by explaining what it takes to be a digital maverick and how enterprises can leverage digital solutions to transform how data is utilized. A digital maverick is typically characterized by big-picture thinking, technical prowess, and the understanding that systems can be optimized through data ingestion.

Generative AI 157

Generative AI Data Ingestion Large Language Models AI 157

PyImageSearch

FEBRUARY 17, 2025

Recently, pretrained language models have significantly advanced text embedding models, enabling better semantic understanding for tasks (e.g., However, in industrial applications, the main bottleneck in efficient document retrieval often lies in the data ingestion pipeline rather than the embedding model’s performance.

Computer Vision 84

Computer Vision Deep Learning Data Ingestion AI 84

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 first step is data ingestion, as shown in the following diagram. This structure can be used to optimize data ingestion.

Data Ingestion 123

Data Ingestion Metadata LLM Generative AI 123

AWS Machine Learning Blog

APRIL 7, 2025

The original query is augmented with the retrieved documents, providing context for the large language model (LLM). Using the query embedding and the metadata filter, relevant documents are retrieved from the knowledge base. The LLM generates a response based on the augmented query and retrieved context.

Metadata 72

Metadata Data Ingestion Generative AI Natural Language Processing 72

Marktechpost

JUNE 16, 2024

This solution addresses the complexities data engineering teams face by providing a unified platform for data ingestion, transformation, and orchestration. Image Source Key Components of LakeFlow: LakeFlow Connect: This component offers point-and-click data ingestion from numerous databases and enterprise applications.

Data Ingestion 116

Data Ingestion Python Automation Data Scientist 116

AWS Machine Learning Blog

JUNE 18, 2024

This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. A human-in-the-loop mechanism safeguards data ingestion.

Generative AI 122

Generative AI Data Ingestion Python LLM 122

AWS Machine Learning Blog

DECEMBER 11, 2024

By moving our core infrastructure to Amazon Q, we no longer needed to choose a large language model (LLM) and optimize our use of it, manage Amazon Bedrock agents, a vector database and semantic search implementation, or custom pipelines for data ingestion and management.

Generative AI 94

Generative AI Data Ingestion Chatbots Software Engineer 94

Marktechpost

JANUARY 10, 2024

In simple terms, RAG is a natural language processing (NLP) approach that blends retrieval and generation models to enhance the quality of generated content. It addresses challenges faced by Large Language Models (LLMs), including limited knowledge access, lack of transparency, and hallucinations in answers.

Natural Language Processing 107

Natural Language Processing Large Language Models Data Ingestion NLP 107

AWS Machine Learning Blog

FEBRUARY 19, 2024

Chatbots also offer valuable data-driven insights into customer behavior while scaling effortlessly as the user base grows; therefore, they present a cost-effective solution for engaging customers. Chatbots use the advanced natural language capabilities of large language models (LLMs) to respond to customer questions.

Chatbots 116

Chatbots Data Ingestion Machine Learning Generative AI 116

Towards AI

AUGUST 25, 2023

A tech deep-dive to build the ultimate hiring platform using large language models & vector databases Photo by Cytonn Photography on Unsplash “Do you know what’s harder than finding a needle in a haystack? Data Ingestion and Storage Resumes and job descriptions are collected from users and employers, respectively.

Data Ingestion 98

Data Ingestion NLP Large Language Models Software Engineer 98

Marktechpost

DECEMBER 3, 2024

In the evolving landscape of artificial intelligence, language models are becoming increasingly integral to a variety of applications, from customer service to real-time data analysis. One key challenge, however, remains: preparing documents for ingestion into large language models (LLMs).

LLM 102

LLM AI Tools Large Language Models Data Ingestion 102

AWS Machine Learning Blog

JANUARY 29, 2025

Generative AI architecture components Before diving deeper into the common operating model patterns, this section provides a brief overview of a few components and AWS services used in the featured architectures. LLMs may hallucinate, which means a model can provide a confident but factually incorrect response.

Generative AI 82

Generative AI AI AI Large Language Models 82

Towards AI

MARCH 28, 2024

This e-book focuses on adapting large language models (LLMs) to specific use cases by leveraging Prompt Engineering, Fine-Tuning, and Retrieval Augmented Generation (RAG), tailored for readers with an intermediate knowledge of Python.

Large Language Models 97

Large Language Models Prompt Engineer Prompt Engineering LLM 97

Marktechpost

SEPTEMBER 26, 2023

They also plan on incorporating offline LLMs as they can process sensitive or confidential information without the need to transmit data over the internet. This will reduce the risk of data breaches and unauthorized access. Check out the GitHub and Documentation.

Data Ingestion 128

Data Ingestion Natural Language Processing Artificial Intelligence Artificial Intelligence 128

Towards AI

MARCH 10, 2025

Introduction Large Language Models (LLMs) have opened up a new world of possibilities, powering everything from advanced chatbots to autonomous AI agents. However, to unlock their full potential, you often need robust frameworks that handle data ingestion, prompt engineering, memory storage, and tool usage.

LLM 92

LLM Python Data Ingestion Prompt Engineer 92

AWS Machine Learning Blog

OCTOBER 2, 2024

Manage data through standard methods of data ingestion and use Enriching LLMs with new data is imperative for LLMs to provide more contextual answers without the need for extensive fine-tuning or the overhead of building a specific corporate LLM.

Generative AI 117

Generative AI Data Ingestion AI AI 117

AWS Machine Learning Blog

NOVEMBER 22, 2023

Effectively manage your data and its lifecycle Data plays a key role throughout your IDP solution. Starting with the initial data ingestion, data is pushed through various stages of processing, and finally returned as output to end-users. Amazon Textract requires at least 150 DPI.

IDP 108

IDP Data Ingestion Automation Natural Language Processing 108

AWS Machine Learning Blog

NOVEMBER 15, 2023

The teams built a new data ingestion mechanism, allowing the CTR files to be jointly delivered with the audio file to an S3 bucket. In the future, Principal plans to continue expanding postprocessing capabilities with additional data aggregation, analytics, and natural language generation (NLG) models for text summarization.

Data Ingestion 118

Data Ingestion Metadata NLP Data Scientist 118

AWS Machine Learning Blog

MAY 7, 2024

The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub. The service allows for simple audio data ingestion, easy-to-read transcript creation, and accuracy improvement through custom vocabularies. Amazon Transcribe’s new ASR foundation model supports 100+ language variants.

Automation 126

Automation Auto-complete DevOps UX Design 126

Snorkel AI

DECEMBER 2, 2024

Large language models (LLMs) fine-tuned on proprietary data have become a competitive differentiator for enterprises. When combined with Snorkel Flow, it becomes a powerful enabler for enterprises seeking to harness the full potential of their proprietary data.

Data Ingestion 52

Data Ingestion Large Language Models LLM Machine Learning 52

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. For ingestion, data can be updated in an offline mode, whereas inference needs to happen in milliseconds.

Generative AI 131

Generative AI LLM Natural Language Processing Metadata 131

AWS Machine Learning Blog

NOVEMBER 26, 2023

You follow the same process of data ingestion, training, and creating a batch inference job as in the previous use case. Announcing LangChain integration to seamlessly integrate Amazon Personalize with the LangChain framework LangChain is a powerful open-source framework that allows for integration with large language models (LLMs).

Generative AI 121

Generative AI Metadata Software Engineer AI 121

ODSC - Open Data Science

SEPTEMBER 17, 2024

As one of the most rapidly developing fields in AI, the capabilities for and applications of Large Language Models (LLMs) are changing and growing continuously. It can be hard to keep on top of all the advancements. At ODSC West this October 29th-31st, you’ll find a wide range of workshops, tutorials, and talks on LLMs and RAG.

LLM 52

LLM Large Language Models Metadata Data Science 52

Snorkel AI

JANUARY 8, 2025

At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform. Ingesting raw data from Databricks into Snorkel Flow Efficient data ingestion is the foundation of any machine learning project.

AI Developer 52

AI Developer AI Development Data Ingestion LLM 52

ODSC - Open Data Science

OCTOBER 7, 2024

Understanding the MLOps Lifecycle The MLOps lifecycle consists of several critical stages, each with its unique challenges: Data Ingestion: Collecting data from various sources and ensuring it’s available for analysis. Data Preparation: Cleaning and transforming raw data to make it usable for machine learning.

Software Engineer 52

Software Engineer Data Ingestion Machine Learning Data Scientist 52

AWS Machine Learning Blog

APRIL 8, 2024

Unlocking accurate and insightful answers from vast amounts of text is an exciting capability enabled by large language models (LLMs). When building LLM applications, it is often necessary to connect and query external data sources to provide relevant context to the model.

LLM 119

LLM Large Language Models Machine Learning Data Ingestion 119

ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

AWS Machine Learning Blog

JULY 17, 2024

Amazon Q Business is a fully managed, secure, generative-AI powered enterprise chat assistant that enables natural language interactions with your organization’s data. By default, Amazon Q Business will only produce responses using the data you’re indexing. This behavior is aligned with the use cases related to our solution.

IDP 115

IDP Automation Data Ingestion Generative AI 115

John Snow Labs

FEBRUARY 1, 2025

Finally, I will outline ongoing work and future directions, including improving data ingestion, enhancing model transparency, and refining the contextual application of AI within functional medicine.

Data Ingestion 52

Data Ingestion Machine Learning Chatbots Algorithm 52