QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...

Machine learning is often key to success for today’s institutions that rely heavily on data. But often, data science teams can have a difficult time convincing their organizations of the breadth and ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

We are now getting closer to the adoption of AI for business as a direct contributor more than before, with generative AI emerging as a transformative force. Generative AI, which is technically a ...

Gengo, a leader in expert, high-scale crowdsourced translation services, is taking aim at the growing need for high-quality multilingual data to train tomorrow’s advanced AI (artificial intelligence) ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...