Term
AI Engineering
Definition
AI Engineering is the process of creating, setting up, and maintaining AI systems by applying well-established engineering methods. It uses technical skills to ensure AI systems work efficiently and effectively.
Where you'll find it
This process typically occurs in the development and operations areas of an AI platform. AI Engineering is not tied to a specific tool within the platform; it spans various tools and functions involved in building and maintaining AI systems.
Common use cases
- Developing new AI applications or services to perform specific tasks.
- Updating and optimizing existing AI systems to improve performance or add new features.
- Troubleshooting and solving issues that arise with AI implementations.
Things to watch out for
- Keeping up with rapidly changing AI technologies and methods can be challenging.
- Ensuring compatibility between different AI components and systems.
- Managing the complexity of AI systems without compromising performance or scalability.
Related terms
- Machine Learning
- Neural Networks
- Data Engineering
- Model Deployment
- System Optimization
Pixelhaze Tip: Dive into user manuals and active community forums to better understand the integration and functional challenges of AI Engineering. Learning from experienced developers can drastically shorten your learning curve.