The team's SynthSmith data pipeline develops a coding model that overcomes scarcity of real-world data to improve AI models ...

1. The "quarantine" pattern is mandatory: In many modern data organizations, engineers favor the "ELT" approach. They dump raw data into a lake and clean it up later. For AI Agents, this is ...

For decades, the data center was a centralized place. As AI shifts to an everyday tool, that model is changing. We are moving ...

AI has been reshaping how operations-heavy companies think about data infrastructure, and it could fundamentally reshape ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

Learn how this new standard connects AI to your data, enhances Web3 decision-making, and enables modular AI systems.

“AI readiness is not fundamentally a model problem. It is a data and metadata issue,” Garg said.

One of the biggest challenges early-stage startup founders face is predicting and managing revenue growth. In most organizations, this looks like top-down forecasting and starts with determining the ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either ...