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Subliminal Learning: How AI Models Inherit Hidden Dangers

Researchers have uncovered an unexpected flaw in one of the most common techniques used to build smaller, cheaper AI models: Distillation. When a “student” model is trained on filtered outputs from a larger “teacher,” it can still inherit the teacher’s quirks and unsafe behaviors, even when those traits never appear in the training data. They’re

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Agent Frameworks vs Runtime vs Harnesses: What They Are and When to Use Which 

AI agents are LLM-powered systems that act autonomously to solve complex tasks. Unlike simple chatbots, agents plan steps, call external tools, and use memory to keep context. For example, an agent can analyse data sources and generate a multi-step plan, whereas a basic LLM app can only answer a single prompt.   Therefore, developers now need

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How Confessions Can Keep Language Models Honest?

When a person admits they made a mistake, something surprising happens. The confession often restores trust rather than breaking it. People feel safer around someone who owns their errors than someone who hides them. Accountability builds confidence.  What if AI models can do the same? Most AI systems give confident answers, even when they are

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