4 posts
What is explainable AI? Explainable AI (XAI) is the set of methods that make a model's decision — which inputs and reasons it rests on — understandable to a human. This guide: a clear definition, the black-box problem, how XAI works, SHAP and LIME, model transparency, KVKK/GDPR, sector examples, and FAQs.
A complete compliance playbook for Turkish banks: BDDK's AI Safe Testing and Validation Environment (AI Sandbox) launched February 2026 with ~30 banks and 100 CIOs, KKB's shared testing infrastructure, the EU AI Act's high-risk classification of credit scoring, and real-world use cases in credit scoring, fraud detection, AML and call center — with documented case studies.
Detailed head-to-head of xAI Grok 3 and OpenAI GPT-5: X (Twitter) real-time data access, DeepSearch + Think reasoning, image/video generation (Aurora, Imagine), Turkish fluency, pricing (X Premium $8/mo vs ChatGPT Plus $20/mo), KVKK posture, censorship profile, and use cases. 8 scenario-based selection guide.
A comprehensive Turkish guide spanning the philosophical foundations of AI ethics and safety to production controls. Covers responsible AI principles (FAT — Fairness, Accountability, Transparency, Privacy, Safety), bias sources and mitigation, hallucination control, alignment techniques (Constitutional AI, RLHF, RLAIF), prompt injection and jailbreak defenses, deepfake detection, red teaming, EU AI Act + ISO 42001 integration, a responsible-AI maturity model, and 3 anonymized Turkish enterprise case studies.