Generative AI
An artificial intelligence technology that learns from large-scale data to understand patterns and structures, and based on this, generates original new content such as text, images, audio, and code.
Detailed explanation
Why it matters in tool selection
Generative AI is moving beyond simple chatbots to become the standard for workplace productivity. When selecting tools, the success of business integration is determined not just by simple 'generative capability', but also by fine-tuning availability for specific domains, hallucination mitigation technologies, and secure integration (security) with internal enterprise data.
What to check when choosing tools
- Multimodal support: Can it simultaneously analyze images, documents (PDFs), etc., in addition to text?
- Data security: Is there an option to prevent entered data from being reused for model training?
- Context window: Is the amount of information that can be entered and processed at one time sufficient?
- Response speed and cost: Does it have an inference speed and API cost structure suitable for real-time services?
Key use cases
Key examples include automated marketing copy generation and image banner production, source code writing assistance and bug fixing, large-scale document summarization and knowledge base construction, and personalized learning content creation.
Confusing terms
Discriminative AI
Focuses on classifying what data is (e.g., distinguishing between dogs and cats) or predicting numerical values.
Traditional AI
Finds optimal answers based on set rules or algorithms, but cannot create new original work.