The latest breakthrough in information theory comes in the form of algorithms offering an effective blend of theory and practical application. These are especially significant in steganography, a field that involves hiding data within digital media. Not often do these two worlds overlap, but these new algorithms satisfy both important theoretical security criteria and offer practical applications for covertly embedding messages in machine-generated content. The algorithms could be used by governments or other entities seeking to transmit information discreetly across digital platforms. In light of increasing restrictions on encrypted channels in some countries, it also offers a tool for people trying to send or receive encrypted messages. Steganography is an ancient art dating back to the 5th century BCE, which makes use of various secretive techniques for message transmission. Modern technology has now allowed the development of a wide range of additional means for concealed communication, such as concealing messages within digital images, voicemail files, or manipulated photos. In the 1980s, mathematicians and computer scientists began creating formal mathematical rules for steganography. These models considered language probabilistically; however, achieving steganographic perfection was considered far-fetched due to the infeasibility of perfect simulation of the human language. Nevertheless, with the rise of machine-generated text created by generative models, the potential for perfectly secure steganography in reality, seems plausible.