The rise of AI-powered text-to-image generation has resulted in a flood of low-quality images, causing skepticism and misdirection. However, a new phenomenon of AI-powered text-to-CAD generation has emerged, with major players like Autodesk, Google, OpenAI, and NVIDIA leading the way.
The article explores common data clustering techniques, with a focus on spectral clustering. Using k-means to compute cluster labels from eigenvectors is found to be the best approach, despite variations and complexities.