Search Results: LLMQuantization

fdtn-ai has released Foundation-Sec-8B-Instruct, an 8-billion-parameter language model fine-tuned for cybersecurity applications, now available with multiple quantization variants. The optimized versions enable efficient local deployment—critical for sensitive security workloads—while maintaining performance. This specialized model signals growing industry emphasis on AI tailored for defensive and offensive security operations.

Groundbreaking research reveals that removing just one critical parameter - dubbed 'super weights' - can catastrophically collapse LLM performance, increasing perplexity 1000x. The discovery enables novel quantization techniques and exposes surprising fragility in billion-parameter AI systems.