What's the Difference Between AI, Machine Learning, and Deep Learning?
AI, Machine Learning (ML), and Deep Learning (DL) are often used interchangeably, but they’re not the same. Understanding how they differ is key to unlocking the full potential of intelligent solutions in retail and beyond.
| Key Aspect | AI | Machine Learning | Deep Learning |
|---|---|---|---|
| Scope | All intelligent systems | Data-driven learning | Neural networks (many layers) |
| Data Dependency | Not always | Essential | Critical (large datasets) |
| Feature Engineering | Manual or automated | Manual | Automated (hierarchical) |
| Model Complexity | Varies | Shallow to moderate | Deep (multi-layered) |
| Hardware Needs | Low–moderate | Moderate | High (GPUs/TPUs) |
| Example Algorithms | Rules, logic, search | Decision trees, SVM, k-means | CNN, RNN, transformers |
| Use Case Example | Chess, expert systems | Spam detection, credit scoring | Image recognition, translation |
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From smart surveillance to predictive analytics, SAI Group’s visual AI is built for a safer, smarter, and more profitable retail future - connect with us today!
About SAI
As a leader in computer vision technology, SAI Group delivers cutting-edge, multi-modal AI solutions into retail environments. Using a unique platform approach, its technology uses existing camera systems to target losses, increase store safety, and underpin operational efficiencies.
All solutions are built from the ground up to ensure the highest levels of security and data protection, respecting the privacy expectations of the public and operating to stringent ethical standards while delivering substantial value to our clients. Globally, SAI monitors millions of transactions per day, protecting the revenues from tens of millions of product sales and hundreds of millions of customer interactions. Its models also accurately identify anti-social behaviour, aggression and violence, helping to de-escalate situations with real-time interfaces to security officers and operations centres.
