Here are ten notable developments in the field of Natural Language Generation (NLG) and Automated Content Creation:

1. GPT-3: OpenAI’s Generative Pre-trained Transformer 3 (GPT-3) model is a groundbreaking NLG system that can generate coherent and contextually relevant human-like text across a wide range of domains and tasks.

2. BigGAN: BigGAN is a state-of-the-art NLG model developed by OpenAI, capable of generating high-quality images based on textual descriptions.

3. Content Shock: Coined by Mark Schaefer, content shock refers to the decreasing effectiveness of content marketing due to the overwhelming amount of information available. As a result, there is a greater demand for automated content creation solutions.

4. Automated News Writing: Automated systems like Wordsmith and Google’s The Washington Post Heliograf are used by various news organizations to generate news articles from data sources, enabling faster and more scalable news production.

5. NLG in Business Intelligence: NLG solutions are employed in business intelligence platforms to automatically analyze complex data sets and generate written summaries, reducing the need for manual analysis and interpretation.

6. Multimodal NLG: Advancements in NLG have allowed for the generation of both textual and visual content simultaneously, enabling systems to produce reports, presentations, and dashboards with integrated charts, graphs, and images.

7. NLG-powered Chatbots: NLG enhances the capabilities of chatbots by enabling them to understand and respond to user queries more naturally and contextually. This improves the overall conversational experience.

8. NLG in E-commerce: Automated content creation is utilized in e-commerce platforms to generate personalized product descriptions, dynamically tailored recommendations, and promotional content based on user preferences and behavior.

9. Natural Language Programming: The concept of Natural Language Programming (NLP) involves using NLG techniques to automatically generate code or program logic based on natural language requirements, simplifying the programming process.

10. Ethical Concerns: With the growing influence of NLG in content generation, ethical considerations, such as the responsible use of AI-generated content, transparency in attribution, preventing the spread of misinformation, and guarding against bias, have become significant areas of focus.

Note that these developments represent the current state of NLG and automated content creation, and ongoing research and innovation will continue to shape the field.