The trajectory of the translation services industry has consistently mimicked the advancements within the globalized digital ecosystem. The deluge of digital content and the increasing need for accurate translations have propelled the necessity of sophisticated tools and methodologies. This has led to the evolution of English translating services, a domain that is seeing unprecedented progress in terms of technology and techniques.

Artificial Intelligence (AI) and machine learning (ML) emerged as the bedrock of modern translation services. The utilization of these technologies goes beyond merely translating the text from one language to another. It probes at understanding the nuances and context of the content, which is crucial, especially in English translations.

Language, being an embodiment of cultural, social, and historical elements, cannot be accurately translated without an understanding of these underlying aspects. This understanding is pivotal as the English language, with its vast array of dialects and variations, presents unique challenges for translation services. The incorporation of AI and ML enables these services to assimilate these complexities and provide translations that are contextual and reflective of the respective cultural nuances.

The adoption of Natural Language Processing (NLP) in translation services is a testament to this shift towards more nuanced translations. NLP, a sub-field of AI, aids in understanding, interpreting, and manipulating human language. It includes a gamut of technologies such as Named Entity Recognition, Sentiment Analysis, and Topic Modeling. These technologies, when integrated into translation services, facilitate a more in-depth and sophisticated understanding of the text, hence, improving the quality of translation.

However, the trade-off here lies in the inherent impersonality of AI and ML. While these technologies have greatly enhanced the efficiency and accuracy of translations, they lack the personal touch of human translators. The ability to understand and interpret complex emotions, intricacies, and subtleties of languages might still elude AI and ML.

Despite this, the advancements in AI and ML have prompted a significant shift towards automation in the translation industry. Automation, apart from increasing the speed and cost-effectiveness of translations, also circumvents the risk of human error.

Yet, it is important to acknowledge that automation might not be the panacea for all translation needs. For instance, literary translations, which require a nuanced understanding of metaphors, allegories, and cultural contexts, might not be completely served by automation. In such scenarios, a collaborative model of human translators and AI-powered tools might yield more accurate translations. This indicates, at least in the foreseeable future, human translators will continue to play an indelible role in the industry.

A promising trend in the industry is the advent of real-time translation services. The integration of AI and ML with cloud computing and Internet of Things (IoT) has catalyzed this development. The utility of real-time translations in industries such as tourism, international diplomacy, and global business is immense. This emerging trend is expected to gain momentum in the future, further revolutionizing the industry.

The translation industry is also witnessing the integration of blockchain technology, primarily to ensure the security and integrity of translations. The concept of smart contracts, a blockchain-based contract that automatically executes itself when the conditions in the agreement are met, is being explored to guarantee the quality and timeliness of translations.

In conclusion, the future of English translating services is witnessing a confluence of AI, ML, and other advanced technologies. Although these advancements are bound to redefine the landscape of the industry, the human element will continue to hold its ground. The future, thus, is not about the replacement of human translators, but their collaboration with technology to achieve more accurate, efficient, and nuanced translations.