Question

1. which technology did the video say can create convincing fake images and videos (deepfakes)?

bayesian classifiers
generative models such as gans and diffusion - based systems
convolutional neural networks only
liquid neural networks

Explanation:

Generative models like GANs (Generative Adversarial Networks) and diffusion - based systems are designed to generate new data instances. GANs consist of a generator and a discriminator. The generator tries to create fake data (e.g., images, videos) that can fool the discriminator, which is trained to distinguish real from fake data. Diffusion - based systems work by gradually removing noise from a random input to generate a realistic output. In contrast, Bayesian classifiers are mainly for classification tasks (assigning an input to a pre - defined class), convolutional neural networks (CNNs) are often used for feature extraction and classification in image - related tasks (not primarily for generation), and liquid neural networks are a type of neural network architecture with different properties (not focused on generation of convincing fake media).

Answer:

Generative models such as GANs and diffusion - based systems