Pulse 2.0

Unstructured: LLM Data Preprocessing Solutions Provider Raises $40 Million

Unstructured – a leader in ingestion and preprocessing for large language models (LLMs) – announced a $40 million Series B funding round. This funding round was led by Menlo Ventures with ...
HackerNoon

The LLM Operating System: Transformers, Limitations, and the Need for Adaptation

Explore LLM architectures, general-purpose limitations, and why adapting models through Fine-Tuning and RAG is the real ...
Semiconductor Engineering

Largest High-Quality Verilog Dataset for LLM Fine-Tuning (Univ. of Florida)

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation” was published by researchers at the University of Florida.
ascopubs.org

Leveraging Centralized Health System Data Management and Large Language Model–Based Data Preprocessing to Identify Predictors for Radiation Therapy Interruption

We analyzed demographic, behavioral, clinical, and neighborhood-level data for 2,130 patients treated with radiotherapy at the University of Tennessee Medical Center in Knoxville. Treatment ...
techtarget

How to train an LLM on your own data

General-purpose large language models are convenient because businesses can use them without any special setup or customization. However, to get the most out of LLMs in business settings, ...
ascopubs.org

Ensuring Reliability of Curated Electronic Health Record–Derived Data: The Validation of Accuracy for Large Language Model–/Machine Learning–Extracted Information and ...

Early-Stage Breast Cancer in Women Younger Than 50 Years: Comparing American Joint Committee on Cancer Anatomic and Prognostic Stages With Partitioning Around Medoids Clusters in SEER Data Large ...
techtarget

How to prepare data for your RAG pipeline

Retrieval-augmented generation connects generative AI to enterprise data. However, without a proper RAG data pipeline, the RAG system might not find the most accurate data to answer user queries. Data ...