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.

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LLM Python Data Ingestion Prompt Engineering 92

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. Dianasanimals is looking for students to test several free chatbots.

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Large Language Models Prompt Engineering Prompt Engineer LLM 97

Pragnakalp

JULY 13, 2023

LlamaIndex is an impressive data framework designed to support the development of applications utilizing LLMs (Large Language Models). It offers a wide range of essential tools that simplify tasks such as data ingestion, organization, retrieval, and integration with different application frameworks.

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Chatbots Large Language Models LLM Data Ingestion 52

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).

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Snorkel AI

JANUARY 8, 2025

This integration uniquely bridges the gap between scalable data management and cutting-edge AI development, unlocking new efficiencies in data ingestion, labeling, model development, and deployment for our customers. Validate in Databricks: Ensure that the newly labeled dataset is loaded correctly.

AI Development 52

AI Development AI Developer Data Ingestion LLM 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.

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John Snow Labs

FEBRUARY 1, 2025

However, the complexity and scale of data present significant challenges in processing, accuracy, and can stymie decisionmaking. This presentation will explore the role of FunctionalMind , an AIdriven chatbot and clinical research agent, in addressing these challenges.

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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.

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IDP Automation Data Ingestion Generative AI 120

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.

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LLM Large Language Models Machine Learning Data Ingestion 122

The MLOps Blog

MARCH 12, 2024

TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. What is Large Language Model Operations (LLMOps)? What the future of LLMOps looks like.

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Prompt Engineering Prompt Engineer Large Language Models LLM 52

AWS Machine Learning Blog

AUGUST 8, 2024

Content ingestion into vector db Select the optimal LLM for your use case Selecting the right LLM for any use case is essential. Every use case has different requirements for context length, token size, and the ability to handle various tasks like summarization, task completion, chatbot applications, and so on.

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Metadata LLM Prompt Engineering Prompt Engineer 122

ODSC - Open Data Science

JANUARY 10, 2024

The AI Paradigm Shift: Under the Hood of a Large Language Models Valentina Alto | Azure Specialist — Data and Artificial Intelligence | Microsoft Develop an understanding of Generative AI and Large Language Models, including the architecture behind them, their functioning, and how to leverage their unique conversational capabilities.

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Large Language Models Deep Learning LLM Data Science 52

AWS Machine Learning Blog

MAY 25, 2023

One of the most common applications of generative AI and large language models (LLMs) in an enterprise environment is answering questions based on the enterprise’s knowledge corpus. Amazon Lex provides the framework for building AI based chatbots. Amazon SageMaker Studio for hosting the Streamlit application.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In order to train transformer models on internet-scale data, huge quantities of PBAs were needed. In November 2022, ChatGPT was released, a large language model (LLM) that used the transformer architecture, and is widely credited with starting the current generative AI boom. Firstly, to train a FM from scratch.

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Topbots

FEBRUARY 19, 2024

In the rapidly evolving AI landscape, Large Language Models (LLMs) have emerged as powerful tools, driving innovation across various sectors. From enhancing customer service experiences to providing insightful data analysis, the applications of LLMs are vast and varied.

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ODSC - Open Data Science

JULY 11, 2023

1] The typical application familiar to readers is much more recent, when AI operates as chatbots, enhancing or at least facilitating the user experience on many websites. Whether that happens with many large language models is largely, but not entirely, up to you. [5] Data center career paths (techtarget.com) 10.

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ChatGPT AI AI Chatbots 40

AWS Machine Learning Blog

SEPTEMBER 24, 2024

It allows beginners and expert practitioners to develop and deploy Gen AI applications for various use cases beyond simple chatbots, including agentic, multi-agentic, Generative BI, and batch workflows. Data Ingestion Pipeline Ingesting data from diverse sources is essential for executing Retrieval Augmented Generation (RAG).

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Data Ingestion Machine Learning Large Language Models Generative AI 118

Flipboard

NOVEMBER 26, 2024

Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. Imagine this to be a simpler implementation of calling a customer service agent when the chatbot is unable to answer the customer query.

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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.

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Metadata Generative AI LLM Data Ingestion 104