Data, Operating Model And Context: AI Needs All Three To Thrive

Companies struggle to fully develop AI in more than a handful of business functions or to accelerate the shift from pilots to ...

Why Reliable Data, Not Bigger Models, Will Define The Next Era Of Enterprise AI

The goal is not perfect data—an often impossible standard—but data sufficiently reliable for the decision it must support.​ ...

Decision models like Jev handle what SQL rules cannot. Here's how data teams use them

Data platforms make decisions all day. An SQL query keeps the rows over a threshold, matches a keyword, and joins two tables ...
CCR-Mag.com

Data-Driven Risk Modeling for Payer Cost and Quality Improvement

Payers face an intersecting set of pressures: controlling costs, improving clinical outcomes, complying with regulations, and demonstrating value to employers ...

Knowledge Grid Study Shows the Same AI Model Goes From Wrong to Right When Data Becomes Knowledge

Knowledge Grid, the company defining the Cognitive Data Layer for AI, today announced a study showing an AI model's verdict ...
The Scientist

RushData: AI-Ready Data for Models and Agents with 1-Day CHO Expression

RushData is an integrated high-throughput platform combining 1-day CHO expression, rapid binding analytics, and early ...
Unite.AI

How Are Large Language Models Pretrained? Data, Objectives, and Compute

Large language model pretraining optimizes a neural network on vast token sequences so it learns reusable linguistic, factual ...
Stanford Daily

Electronic Medical Record (EMR) Data Models

The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an open community data standard, designed to standardize the structure and content of observational data and to enable ...
Unite.AI

What Is Data Poisoning? How Attackers Corrupt AI Models and Datasets

Data poisoning manipulates training, fine-tuning, evaluation, or retrieval data so an AI system learns corrupted behavior or ...