تقييم موردي الذكاء الاصطناعي ونماذجه

في هذا الدرس

define the criteria for choosing an AI vendor or model and weight them with stakeholders.

الموضوعات المخطط لها

• Core criteria: quality on your own tasks, latency, cost, data terms (residency, retention, training use), security, support and roadmap, and exit.
• Separate vendor questions (terms, support, stability, sub-processors) from model questions (quality, speed, context size, tool use).
• Agree weights with stakeholders before scoring; security and data terms may be pass/fail gates, not weighted points.
• Include operating effort: a self-hosted open-weight model needs GPUs, patching, and skilled people.
• Reuse the vendor-evaluation method from ARC-040; the AI-specific part is how quality is measured.