Archive: 2026/04 - Page 3

Privacy and Security Risks of Distilled LLMs: A Guide for Secure Deployment
Privacy and Security Risks of Distilled LLMs: A Guide for Secure Deployment

Tamara Weed, Apr, 5 2026

Explore the hidden privacy and security risks of distilled LLMs. Learn why model compression doesn't stop PII leaks and how to use Intel TDX to secure your AI deployment.

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Enterprise Technology

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distilled large language models model compression knowledge extraction attacks Intel TDX PII leakage
Federated Learning for LLMs: How to Train AI Without Centralizing Data
Federated Learning for LLMs: How to Train AI Without Centralizing Data

Tamara Weed, Apr, 4 2026

Learn how Federated Learning enables training Large Language Models (LLMs) across decentralized data sources to ensure privacy and bypass data centralization.

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Enterprise Technology

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Federated Learning Large Language Models data privacy OpenFedLLM decentralized training
Emergent Capabilities in Generative AI: What Works and What Remains Unclear
Emergent Capabilities in Generative AI: What Works and What Remains Unclear

Tamara Weed, Apr, 1 2026

Exploring emergent capabilities in Generative AI: definition, examples like chain-of-thought, the 'mirage' debate, and safety implications for 2026.

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Science & Research

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emergent capabilities generative AI large language models AI safety chain-of-thought

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