It's not just about making AI smarter, but also about making sure people can trust it and understand how it works.

Sapient researchers trained a 1B reasoning model on just 40B tokens — scoring competitively with 2B-7B models at a fraction ...

Securing AI pipelines against data poisoning: a practical guide for technical teams Data poisoning is one of the more practical risks in AI security because it targets the pipeline rather than the ...

Explore the risks of training LLMs on AI-generated data, revealing potential model collapse and the importance of ...

Table 1 Comparison of PPG based NIBG with personalized models. Full size table As the aforementioned personalized models collect data continuously from fasting to post-meal periods, the accompanying ...

Your labeled dataset looks perfect inside the annotation tool. Bounding boxes are clean, labels are consistent, and your team spent three weeks getting everything right. Then you hit export, drop the ...

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 ...

Data modeling is the process of defining datapoints and struc­tures at a detailed or abstract level to communicate information about the data shape, content, and relationships to target audiences.

Three years ago Zoom settled with the FTC over a claim of deceptive marketing around security claims, having been accused of overstating the strength of the encryption it offered. Now the ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...