Natural language processing (NLP) has advanced significantly over the past decade, providing immense opportunities for synthetic text generation through large language models, such as word2vec and BERT. However, these models come with ethical and environmental concerns, including the risk of perpetuating societal biases present in training data and the high carbon footprint associated with their development. Gretel, a company exploring NLP innovations, emphasizes the need for responsible usage of these models by considering privacy implications and curating unbiased datasets, although achieving the latter remains a challenging research problem. Despite these challenges, Gretel aims to democratize access to NLP technology by offering users efficient ways to generate high-quality synthetic text while balancing ethical considerations. The company is developing new metrics to evaluate text quality and plans to address these issues further in an upcoming blog series.