Artificial Intelligence

To get the most value from AI, we must feed it our most sensitive data. But how do we prevent 'data leakage’ associated with public models? In this review, we explore emerging data privacy alternatives—including Decentralized AI (DeAI), Privacy-Enhancing Technologies (PETs), and Synthetic Data—that allow enterprises to benefit from AI without exposing their secrets.

AI requires massive amounts of high-quality data to be scalable and trusted. Our new blog introduces Data Hydration , a vital set of processes—Validation, Enrichment, and Governance —that transforms raw, incomplete data into the accurate, organized, and compliant fuel AI models need to thrive. Learn how this holistic approach minimizes cost, prevents hallucinations, and delivers high-integrity AI at scale. Join the Data Hydration LinkedIn Group to discuss the future of Truste

AI Data Center Builders Explore Solar, Natural Gas Turbines, Dedicated Small Nuclear Reactors to Meet Huge Power Needs

Everyone’s talking about DeepSeek: Performance, Chinese origin, open-source distribution. It’s also DePIN-friendly for Decentralized AI.

A set of converging trends - including decentralization and tokenization - are supporting the emergence of trustworthy AI.

Trustworthy AI models can leverage decentralization technologies like blockchain to make accurate, reliable, and transparent decisions.

In this blog, we discuss how DePIN can address an infrastructure bottleneck that limits AI – access to vast amounts of trustworthy data.

It’s no secret that the popularity of artificial intelligence (AI) has exploded for both business and consumer applications. Along with...