Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Synthetic data generation has emerged as a crucial technique for addressing various ...
In the evolving landscape of artificial intelligence (AI), the assumption that more data lead to better models has driven unchecked reliance on synthetic data to augment training datasets. Although ...
The new API is designed to speed up the agent development and testing process so agents can be deployed in production faster. As enterprise demand for building multi-agent systems continues to grow, ...
Databricks Inc. today introduced an application programming interface that customers can use to generate synthetic data for their machine learning projects. The API is available in Mosaic AI Agent ...
PhD, MBA, CTO at John Snow Labs. Making AI & NLP solve real-world problems in healthcare, life science and related fields. Artificial intelligence (AI) and machine learning applications are widely ...
The Federal Chief Data Officers Council is looking for information on synthetic data generation as it works to establish best practices, according to a solicitation posted Thursday. The request for ...
Ojai, CA October 30, 2025 –(PR.com)– GenRocket, the market leader in Design-Driven Synthetic Data Generation, today announced the launch of its Unstructured Data Accelerator (UDA) — an innovation that ...
Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...
Synthetic data generation (SDG) was proposed in the early nineties as a form of imputation. 1 Since then, multiple statistical and machine learning (ML) methods have been developed to generate ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback