AI Geek Programmer Blog
Machine learning, computer vision, deep learning and artificial intelligence engineering.

Cloud AI requires specialized distributed architecture
- AI Geek Programmer
- 5 October 2026
Cloud AI requires specialized distributed architecture. A large model is rarely a good fit for one ordinary server.
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Deep learning uses neural networks to find patterns in data
- AI Geek Programmer
- 5 October 2026
What is deep learning, really? It is a way to teach a computer to find patterns in data by stacking many layers of simple calculations.
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Azure AI Services offer scalable cloud-based intelligence.
- AI Geek Programmer
- 4 October 2026
Azure AI Services offer scalable cloud-based intelligence. They give software access to ready-made AI through web APIs and SDKs.
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CNNs excel at image recognition by detecting spatial patterns
- AI Geek Programmer
- 4 October 2026
CNNs excel at image recognition because they detect spatial patterns. They do not treat an image as one long list of pixels.
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AI systems require robust security architecture for protection
- AI Geek Programmer
- 3 October 2026
AI systems require robust security architecture for protection.
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AI, ML, Deep Learning, and Gen AI Defined
- AI Geek Programmer
- 3 October 2026
What is the cleanest way to tell AI, machine learning, deep learning, and generative AI apart?
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AI image generators use diffusion models to create photos
- AI Geek Programmer
- 2 October 2026
AI image generators use diffusion models to create photos. The model starts with random noise, then removes that noise in small steps.
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CNNs identify patterns in images using specialized layers
- AI Geek Programmer
- 2 October 2026
CNNs identify patterns in images using specialized layers. That is the simple answer, and it is the right place to start.
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- machine learning
- artificial intelligence
- deep learning
- shape recognition
- python
- keras
- convolutional neural networks
- numpy
- cifar10
- convnets
- tensorflow
- ai
- overfitting
- anaconda
- mnist
- pytorch
- data augmentation
- development environment
- dropout
- GPU
- nlp
- scikit-learn
- transformer architecture
- batch normalization
- blockchain
- digits dataset
- google colab
- huggingface
- internal covariate shift
- k-nn