IBM Journey to AI blog

JANUARY 9, 2024

In the generative AI or traditional AI development cycle, data ingestion serves as the entry point. Here, raw data that is tailored to a company’s requirements can be gathered, preprocessed, masked and transformed into a format suitable for LLMs or other models. Increased variance: Variance measures consistency.

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Data Ingestion Data Integration Data Quality LLM 222

Snorkel AI

DECEMBER 2, 2024

The integration between the Snorkel Flow AI data development platform and AWS’s robust AI infrastructure empowers enterprises to streamline LLM evaluation and fine-tuning, transforming raw data into actionable insights and competitive advantages. Here’s what that looks like in practice.

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Data Ingestion Large Language Models LLM Machine Learning 52

Marktechpost

DECEMBER 3, 2024

As generative AI continues to grow, the need for an efficient, automated solution to transform various data types into an LLM-ready format has become even more apparent. Meet MegaParse : an open-source tool for parsing various types of documents for LLM ingestion. Check out the GitHub Page.

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LLM AI Tools Large Language Models Data Ingestion 102

Marktechpost

APRIL 1, 2024

Existing research emphasizes the significance of distributed processing and data quality control for enhancing LLMs. Utilizing frameworks like Slurm and Spark enables efficient big data management, while data quality improvements through deduplication, decontamination, and sentence length adjustments refine training datasets.

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Large Language Models ETL Data Ingestion Data Quality 110

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 101

Generative AI Data Ingestion Chatbots Software Engineer 101

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.

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LLM Large Language Models Metadata Data Science 52

Towards AI

DECEMBER 19, 2024

It emphasizes the role of LLamaindex in building RAG systems, managing data ingestion, indexing, and querying. Finally, it offers best practices for fine-tuning, emphasizing data quality, parameter optimization, and leveraging transfer learning techniques. This article examines data leakage in LLMs.

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Data Ingestion Explainability AI Research AI Researcher 105