Automated News Summarization and Translation Service. This service automatically selects the three “most interesting” news articles from The Seattle Times, creates a summary for each with an accompanying photo, translates the summaries into Russian, and publishes them to a web page as a continuous news stream.

Sample screenshot

Motivation

I developed this service primarily for my parents, enabling them to read concise summaries of Seattle news in Russian. This project bridges their language gap and keeps them connected to local events in my area.

Who Could This Be Useful For?

This type of service could be beneficial for various groups:

1. Immigrants: People with limited language skills who want to stay connected with local news in their native language.
2. Language Learners: Students learning Russian (or English) can compare original English news with translations to improve their skills.
3. Cross-cultural Families: Families with members speaking different languages can share local news and stay connected.
4. Researchers and Analysts: Those studying media trends or conducting cross-cultural studies could use this tool to analyze how news is presented across languages.
5. News Aggregators: Smaller news outlets looking to provide international coverage could adapt this service to offer translated summaries of foreign news.
6. Travel and Relocation Services: Companies helping people move internationally could offer this as a service to help newcomers stay informed about their new home.

Development Details

• Time to create the service: 2-3 weeks
• Coding:
  • ChatGPT: 80%
  • Claude: 15%
  • Manual coding: 5%
• News update frequency: Daily
• Operating cost: Approximately 20 cents per month

AI used

• ChatGPT: For news selection, summarization, and translation validation (second pass)
• Microsoft Bing Translator: For the initial translation (first pass)

Workflow

1. Retrieve news articles and URLs, filtering out previously processed items
2. Use ChatGPT to select the most interesting news from the title list
3. Feed full text of selected news to ChatGPT for summarization
4. Translate summaries using Microsoft Bing Translator
5. Employ ChatGPT to validate and refine translations
6. Perform post-processing and publish results to the Web site via FTP
7. Do a full data backup

Key Learnings

1. Initially, ChatGPT outperformed other LLMs (e.g., locally-run Llama 2 and Claude) in terms of cost-effectiveness for news selection and summarization
2. Microsoft Bing Translator proved a good quality of translation, also offering ~1M words/month at no cost. However, translation errors required making corrections – daily. Recently, Claude significantly improved quality of summarization and translation, so, the output doesn’t require manual error correction anymore.
3. Based on the feedback from my parents and other people, I added a flow that is commenting each news summary, explaining details that people oversees may not be familiar with. This turns out to be a challenging task, but at the end, it dramatically improved user experience and engagement.
4. I implemented local data caching for most workflow steps to optimize speed of troubleshooting and cost of re-running the workflow.
5. I make adding new languages configurable and run experiments with translating US news into Chinese and Hindy, and Ukrainian news – into English..
6. I tried using ChatGPT to make the output HTML page mobile-friendly, however, the result wasn’t that great. Claude produced a good template and the code though, and I am using it ever since.
7. I implemented prompt query template workflows (this item will be expanded)

Considerations for Future Improvements

1. News search functionality.
2. Tags.

Bottom Line

While the initial setup required time and effort, the majority of the coding was accomplished by AI. This project demonstrates the power of AI in creating practical, cost-effective solutions for everyday problems, bridging language barriers, and connecting people across cultures.