GGML and llama.cpp join HF to ensure the long-term progress of Local AI

AI and Bullshit

It is argued that both AI and bullshitters are untrustworthy informants, and for similar reasons, it is natural to describe AI’s informational outputs as bullshit, as it signals their distinctive kind of epistemic deficiencies, which they share with bullshit.

An explainable generative AI framework for detecting low-rate API-based DDoS attacks in cloud environments

Adaptive Repayment Optimisation for SME Lending: A Stochastic Programming Framework with Generative AI Explanation

The Adaptive Repayment Optimisation Engine is introduced, a novel framework that applies constrained stochastic optimisation to the design of loan repayment schedules for small and medium-sized enterprises (SMEs) and contributes to the operations research literature by bridging stochastic programming, explainable AI, and financial regulation in a novel application domain.

Artificial Intelligence for Real-Time Cyber Threat Classification and Emerging Threat Detection: A Structured Review of Methods, Datasets, Challenges, and Research Directions

The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluation protocols.