Showing 193–216 of 510 articles, newest first.
How is a RAG architecture built? An end-to-end pipeline, chunking, embedding, vector database, hybrid search, reranking, generation, and evaluation in a step-by-step production guide.
What is ISO 42001? The AI management system (AIMS) standard, Annex A controls, the certification process, EU AI Act alignment, and the situation in Türkiye.
What is an AI ethics board, why is it needed, and how do you set one up? Core ethical principles, board composition, decision processes, the ethics charter, and the EU AI Act and ISO 42001 relationship in this guide.
What is LLM logging and why is it risky under KVKK? Personal data in logs, data masking, retention period, access control, and a compliance checklist in this comprehensive guide.
AI with employee data in HR and its limits under KVKK: consent, automated decisions, hiring algorithms, profiling, employee monitoring, and the EU AI Act.
What is AI regulation in Türkiye and what is its current state? KVKK, sectoral rules, the National AI Strategy, a possible AI law, and EU AI Act alignment in this guide.
What data anonymization is, masking, pseudonymization, k-anonymity and differential privacy techniques, re-identification risk, and the KVKK/GDPR context in this comprehensive guide.
On-premises AI or cloud? KVKK, data sovereignty, cross-border data transfer, total cost of ownership, self-hosted LLM, and the hybrid approach in this decision guide.
How does the EU AI Act affect companies in Türkiye? Scope, timeline, risk classification, high-risk systems, GPAI, penalties, and a compliance roadmap in this guide.
How do you build KVKK-compliant AI? Processing basis, data minimization, transparency, DPIA, automated decisions, cross-border transfer, and an item-by-item compliance checklist in this comprehensive pillar guide.
How is corporate AI training pricing set? Price factors, pricing models, cost items, per-person cost, in-house vs external training, and hidden costs in this comprehensive guide.
How to build an internal AI academy? A comprehensive setup guide for role-based curriculum design, roles, competency matrix, continuous learning, and training measurement.
What is AI consulting for SMEs and where should you start? Quick-win use cases, low-budget reality, a first-90-days plan, choosing an external consultant, and KVKK in this guide.
How is the impact of AI training measured? The Kirkpatrick four-level model, a level-by-level KPI set, the training ROI calculation, behavior change, and learning outcomes in this guide.
How should C-level AI training be designed? Strategic not technical content for executives, ROI literacy, risk and governance, EU AI Act/KVKK, role-based curriculum, a sample agenda, and common mistakes in this guide.
AI consulting or in-house team? A comprehensive comparison of external AI consulting versus building an in-house team on cost, risk, speed, and knowledge transfer, plus a hybrid model and decision matrix.
How do you write an AI training technical specification (RFP)? Audience, scope, learning outcomes, evaluation criteria, KVKK, a scoring table, and a copy-ready template in this comprehensive procurement guide.
An HR guide to choosing an AI trainer: trainer qualities, the set of questions to ask, demo/pilot requests, reference checks, an HR evaluation framework, scoring, and red flags.
How is AI consultant selection done? Consultant types, a 12-question evaluation checklist, reference checks, red flags, and proposal evaluation in this comprehensive guide.
Vector database selection 2026: pgvector, Qdrant, Milvus compared. Latency, throughput, scalability, and KVKK-compliant hosting. Start small, benchmark with your own data, grow.
Fine-tuning shapes behavior; RAG supplies knowledge. The right 2026 order: prompt first, then RAG, then LoRA/QLoRA, distillation last. A field decision guide.
Frontier models as of July 2026: benchmarks, price/performance and an enterprise selection guide. Which model for which job? Practical field notes.
In production, 73% of RAG failures come from retrieval. Hybrid search, reranking, and adaptive routing by query complexity for resilient RAG.
With reasoning models, explicit chain-of-thought instructions often hurt. The shift to context engineering, outcome-oriented prompts and evaluation loops.