For much of the AI industry’s tremendous growth over the last few years, companies believed their advantage came from owning better models, with the goal of investing heavily to own superior models.

Inevitable missing values in observational time series often hinder reliable data-driven modeling of complex systems across diverse domains. Recovery is essential yet challenging, particularly in high ...

We introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based causal implicit generative model for simulating single-cell RNA-seq data, in silico perturbation experiments, and ...

Decagon announced a partnership with Databricks on September 30, 2026 that pairs zero-copy data sharing between the two ...

Data’s role as a strategic asset has become increasingly prominent in recent years, chiseled into sharp relief by the numerous organizations using it successfully to respond to rapidly changing market ...

Researchers affiliated with Glow Security, a startup whose backers include venture capital funds Sequoia and Greenoaks, have ...

Data debt is the accumulated cost of every shortcut ever taken in data modeling, integration, quality, lineage and access.

Before Numeric, I was the first finance hire at a venture-backed startup. My first project was getting the company through a first audit. I spent months on it. Drafting policies, creating schedules, ...

Synthetic data is artificially generated or simulated information designed to approximate useful properties of real data for training, testing, evaluation, or privacy goals. This guide explains the ...

The potential benefits of cloud computing are inspiring senior IT and business leaders in many organizations to reconsider enterprise data strategy and contemplate how migrating data and applications ...