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A research-driven look at how production LLMs can be prompted (sometimes without jailbreaks) to reproduce large amounts of copyrighted book text, exposing real-world gaps in today’s safety safeguards.

This page explains the key inference-time decoding knobs (temperature, top-k/top-p, penalties, max tokens, and beam search) that control how an LLM trades off determinism, creativity, coherence, repetition, and length.

A concise breakdown of the GPU vs TPU battle, focusing on economics, software ecosystems, specialization trade-offs, networking, and true total cost.

Unlock the full power of LLMs by mastering context engineering—connecting models to memory, tools, and real-world data for truly intelligent AI systems.

Data voids are gaps in online information that malicious actors exploit by flooding them with misleading content, which AI systems then absorb and amplify as authoritative answers.