Artificial Intelligence
Explore the world of AI, machine learning, and data science.
AI Is a Tool - Your Expertise Makes It Valuable
Artificial intelligence is transforming how we work, create, and solve problems. But AI is only as useful as the person guiding it - it amplifies your existing knowledge and accelerates research, but it does not replace understanding. Whether you are exploring local AI models, building intelligent applications, or simply trying to understand the landscape, these guides will help you make informed decisions.
Wizard Tech Services offers AI & Automation services including local AI installation, model management, and training. Read our AI philosophy to understand our approach to responsible AI adoption.
Machine learning enables systems to learn patterns from data without explicit programming. Explore supervised, unsupervised, and reinforcement learning, plus feature engineering and evaluation metrics like accuracy, precision, and recall.
LLMs like GPT-5, Claude 5, Gemini, and LLaMA power conversational AI; Stable Diffusion, FLUX, and DALL-E generate images from text. Compare cloud APIs vs. local inference, parameter counts, quantization, and fine-tuning for your domain.
AI workloads are GPU-intensive - VRAM is the bottleneck. NVIDIA RTX 5090 (32 GB), H100, and B200 lead; 12+ GB cards comfortably handle 7B-13B models locally. Also covers llama.cpp CPU inference, Apple Silicon (M4 Max/Ultra), and cloud GPU rental.
Data science bridges raw data and actionable insights using statistics and programming. Python with pandas, NumPy, scikit-learn, and Jupyter notebooks is the standard toolkit. Covers cleaning, analysis, and visualization with Matplotlib and Plotly.
PyTorch and TensorFlow dominate deep learning; LangChain and LlamaIndex simplify RAG-based LLM apps; Hugging Face hosts thousands of models. Covers prompt engineering, vector databases, and deploying AI as APIs.
Computer vision enables machines to interpret images and video - object detection, facial recognition, medical imaging, and more. OpenCV handles foundational processing; YOLO and ResNet tackle complex recognition tasks.
Computer Vision
Object detection, image processing, and visual AI frameworks for building vision-powered applications.
Real-time object detection model family - YOLOv8/v9 detect and classify multiple objects in a single pass, enabling applications from security cameras to autonomous vehicles.
Key Features:
- Real-time object detection in single forward pass
- YOLOv8 by Ultralytics is current standard
- Supports detection, segmentation, and pose estimation
- Runs on edge devices and embedded systems
The foundational computer vision library - handles image processing, video capture, feature detection, and camera calibration across Python, C++, and JavaScript.
Key Features:
- Image filtering, transforms, and color space conversion
- Video capture and real-time processing
- Feature detection (SIFT, ORB, Harris corners)
- Cross-platform: Python, C++, JavaScript (OpenCV.js)
Deep CNN architectures for image classification - ResNet introduced skip connections enabling very deep networks, EfficientNet optimizes accuracy per compute.
Key Features:
- ResNet-50/101/152 for transfer learning
- Skip connections solve vanishing gradient problem
- EfficientNet scales width, depth, and resolution
- Pre-trained on ImageNet for fine-tuning
Meta's foundation model for image segmentation - segment any object in any image with a click, box, or text prompt without task-specific training.
Key Features:
- Zero-shot segmentation of any object
- Point, box, or text prompt interfaces
- Foundation model trained on 1B+ masks
- SAM 2 extends to video segmentation
Google's cross-platform ML solutions for face detection, hand tracking, pose estimation, and gesture recognition - optimized for mobile and web deployment.
Key Features:
- Face detection and mesh (468 landmarks)
- Hand tracking and gesture recognition
- Full-body pose estimation (33 landmarks)
- Runs in-browser via JavaScript or on mobile
Beyond text-to-image - Stable Diffusion powers image inpainting, outpainting, depth-to-image, and ControlNet for precise visual generation and editing.
Key Features:
- Inpainting removes or replaces image regions
- ControlNet for pose, edge, and depth conditioning
- Img2img for style transfer and variations
- IP-Adapter for image-guided generation