*Understanding the fundamental building blocks that power modern AI systems* — ## The Building Blocks of Neural Networks One of the most basic blocks that you’re going to have in your toolbox when you build large complicated neural networks is a linear classifier, illustrated here with stacked building blocks showing the layered structure. Much of the intuition and technical bits that we’ll cover today will carry over completely to the neural network systems that we’ll…
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*Exploring how nearest neighbor algorithms work through visual analysis and the transition to k-nearest neighbors for improved classification* — ## What Does Nearest Neighbor Classification Look Like? The slide titled ‘What does this look like?’ displays results of nearest neighbor classification on the CIFAR-10 dataset through a grid of related images. Here what we’re showing is the results of nearest neighbor classification on the CIFAR 10 data set. Grid of image rows showing test images…
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*Exploring why image classification remains challenging for machines despite being intuitive for humans* — ## Introduction: Image Classification as a Core Computer Vision Task Image Classification is a core computer vision task, as shown in the slide title. The task involves taking an input image and assigning it to one of several predefined category labels. When presented with the gray tabby cat image, the system correctly assigns it to the ‘cat’ category. So when we…
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*Understanding the intersection of artificial intelligence and visual perception* — ## Introduction Deep Learning for Computer Vision represents one of the most transformative areas in modern artificial intelligence. This field combines the power of learning algorithms with the complexity of visual data processing, creating systems that can truly “see” and understand the world around them. ## Defining Computer Vision Computer vision is the study of building artificial systems that can process, perceive, and otherwise reason…
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*A deep dive into the revolutionary generative AI technology that’s transforming image synthesis* — ## Introduction The concept of a diffusion model dates back to a 2015 paper by researchers at Stanford and Berkeley titled “Deep Unsupervised Learning Using Nonequilibrium Thermodynamics”. This foundational work introduced a fascinating approach to generative modeling that would eventually revolutionize the field of AI-generated imagery. Original diffusion paper I feel like an interesting tradition of like people with an applied…
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