Shayan Mashatian Shayan Mashatian

Securing LLMs for Privacy Protection: Does the Traditional Compliance Model Work?

Explore the intricacies of securing Large Language Models (LLMs) in today's rapidly evolving AI landscape. Dive deep into the challenges of data privacy, traditional compliance models, and the transformative power of generative AI. Discover why the intersection of AI and privacy is pivotal for the future of digital trust and security.

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Shayan Mashatian Shayan Mashatian

Blueprint for Progress: A Tri-Gear Model to Overcome Health Innovation Hurdles

Facing challenges in healthcare innovation? Dive into our latest article addressing the pressing need for agility in large organizations, especially in the health sector. Explore the tri-gear model that promotes cohesive collaboration between scientific breakthroughs, organizational transformation, and effective user adoption. From the intricacies of regulatory compliance to the gap between invention and user-centric innovation, our comprehensive blueprint offers insights for organizations, researchers, and startups alike. Join the conversation to reshape the future of health innovation.

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Shayan Mashatian Shayan Mashatian

Precise AI: Silverberry’s Approach to a Thrustworthy and Reliable Generative AI

Silverberry AI prioritizes precision and trustworthiness in its AI models, ensuring they are both effective and reliable. By exclusively using curated knowledge sources, Silverberry AI ensures the elimination of misinformation risks. Moreover, the company finely calibrates the AI's creativity levels, striking a balance between innovation and factual accuracy. This meticulous approach allows Silverberry AI to provide tools that excel across various sectors, from healthcare and corporate training to advanced research, making it a beacon of reliability in the vast AI landscape.

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Shayan Mashatian Shayan Mashatian

Detecting machine anomalies with AI. What does it mean for your operation?

From healthcare to manufacturing, AI's potential to enhance efficiency, productivity, and decision-making is unmatched. Take predictive maintenance, for example - AI algorithms can detect anomalies in machine performance, allowing businesses to address issues before costly breakdowns occur. This results in reduced downtime, improved safety, and significant cost savings.

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