Below are some high-level guidelines and considerations for product managers looking to leverage MCP in their roadmap.

Confidentiality, to a lesser extent, and integrity, to the greatest extent, are the most important considerations with AI ...

Securing this environment requires moving beyond static roles, perimeter defenses and after-the-fact monitoring. Organizations need data-centric security that embeds protection at the source, adapts ...

For example, in Meta's flagship open-source model, Llama 3.1 405B, which the company introduced last week, the researchers made extensive use of synthetic data to "fine-tune" the model and to ...

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 ...

Learn how to use the Excel PowerPivot functionality for data modeling in data analysis in your spreadsheets. Once mastered this function ...

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

NVIDIA covered how research is enabling scalable synthetic data generation and robot model training workflows using world ...

Data poisoning corrupts AI systems by teaching them with bad data. There’s no silver bullet to protect against it, but ...

Data regulators around the world are investigating issues with how OpenAI gathered the data it uses to train its large language models, the accuracy of answers it provides about people, and other ...