Delving into the realm of Artificial Intelligence (AI) and its applications, one cannot overlook the burgeoning field of AI content writing software. These are sophisticated tools that utilize Machine Learning (ML) algorithms for the automated generation of written content. But what precisely are these AI content writing applications, and how do they operate?

AI content writing software, fundamentally, is a blend of Natural Language Processing (NLP) and Machine Learning technologies. NLP, a branch of AI, enables machines to understand, interpret, and generate human language. It uses computational linguistics to bridge the chasm between human communication and computer understanding.

To comprehend how these AI content writing applications work, we must delve into the realm of Machine Learning and, subsequently, the sub-discipline of Deep Learning. Machine Learning is the scientific study of algorithms and statistical models that systems use to perform tasks without explicit instructions. In the context of content writing, the machine learns from a vast number of text data that it is fed. The more data the system ingests and processes, the more it learns about the structure, syntax, and semantics of a language, thereby producing more coherent and semantically accurate content.

Deep Learning, on the other hand, is a subset of Machine Learning, inspired by the structure and function of the human brain, creating what we call artificial neural networks. These networks are capable of learning from unstructured data, and when applied to text data, they can produce highly sophisticated content.

The mechanism of AI content writing can be better elucidated through an examination of GPT-3—an AI language model developed by OpenAI. GPT-3, or Generative Pretrained Transformer 3, uses a transformer architecture, which relies on attention mechanisms to weigh the influence of different words on each other, thereby generating long and coherent sentences. It's pretrained on a diverse range of internet text and can generate creative, insightful, and contextually relevant text based on the prompt fed to it.

Understandably, some might question the necessity or relevance of AI content writing software. The answer lies in the plethora of benefits these tools offer. They can drastically reduce the time and cost of content creation, provide valuable assistance in generating ideas, and help maintain consistency in a brand’s tone of voice across numerous content pieces. They can also facilitate SEO optimization, thereby boosting a website’s online visibility, and generate personalized content, improving customer engagement.

However, like all technologies, AI content writing software is not devoid of tradeoffs. The most significant drawbacks include a lack of emotional intelligence and context understanding. These tools, as sophisticated as they may be, cannot truly grasp the nuances of human emotions or the subtleties of context that are inherently understood by human writers. They also run the risk of producing content that, while grammatically correct, may come across as non-sensical or irrelevant.

To conclude, AI content writing software signifies a remarkable evolution in technological advancements, promising a future where machines can augment human efforts in content writing. While they are not perfect, continual advancements in Machine Learning and NLP algorithms ensure that these tools will only get better with time. Whether we perceive this as a threat to the creative liberties of human writers or an opportunity for collaboration between humans and machines hinges largely on our perspective. But one thing is certain: AI content writing software is here to stay and will shape the future of content creation.