generative AI

Generative AI for Performance Engineering: Tailoring Llama-3 for Bottleneck Classification and Optimization Recommendations

This paper presents a novel approach to software performance analysis by integrating traditional profiling techniques with a fine-tuned large language model (LLM), based on the Llama-3 model.  Addressing the challenges of manual profiling – such as overwhelming data volumes and the high expertise required to interpret performance metrics – the study introduces a lightweight AI-powered profiler trained on structured JSON-based profiling logs and code samples.  The model is fine-tuned using parameter-efficient methods (LoRA and QLoRA) to classify performance bottlenecks (

Responsibility for Errors of Generative Ai in Legal Practice: Analysis of ‘Hallucination’ Cases and Professional Ethics of Lawyers

The rapid adoption of generative artificial intelligence (AI) in legal practice has created a significant challenge. While AI tools promise unprecedented efficiency, they are prone to "hallucinations" generating plausible but entirely fabricated information. Recent court cases demonstrate a trend of holding lawyers strictly liable for submitting AI-generated falsehoods, creating an unsustainable professional risk.