Writing an Article from External Data with Synthetic RAG

Synthetic RAG is a technique that combines retrieving information from external sources with text generation to create content that is both informative and tailored to a specific user request. This technique is especially useful for producing unique, up-to-date texts based on large volumes of data.

Task:

Generate an article about the latest trends in artificial intelligence using information from several sources.

Prompt for ChatGPT 4o:

Use data from the latest research to generate an article about current trends in artificial intelligence. Include sections on the use of AI in medicine, finance and education.

Result

Current trends in artificial intelligence
In 2024, artificial intelligence (AI) continues to develop rapidly and reach into a variety of fields, with a significant impact on areas such as medicine, finance and education. Current trends show that AI is becoming an inseparable part of modern society, transforming processes and creating new opportunities.
AI in medicine
Medicine is one of the areas where AI is showing itself especially actively. In 2024 there is significant progress in using AI to improve the accuracy of diagnostics, refine personalized treatment and optimize operational processes.
1. Better diagnostics and early detection of disease: AI is used to analyze medical images such as MRI and CT scans, making it possible to spot anomalies with high accuracy. These systems can reduce the number of diagnostic errors and speed up diagnosis, which matters especially in cases of cancer and cardiovascular disease.
2. Personalized medicine: AI helps build individualized treatment plans based on a patient's genetic data. This lets doctors prescribe the most effective drugs and dosages, which significantly improves treatment outcomes.
3. Robotic surgery: using AI in robotic surgery lets doctors perform complex operations with greater precision, which helps reduce post-operative complications and speeds up patient recovery.
4. Telemedicine: AI plays a key role in the growth of telemedicine, offering virtual assistants and chatbots that can answer patients' questions and help with an initial assessment of symptoms, which significantly eases the workload of medical staff.**
AI in finance
In the financial sector AI is also delivering impressive results. In 2024, financial organizations are actively using AI to increase the efficiency and accuracy of their operations.
1. Data analytics and risk management: AI makes it possible to analyze large volumes of data in real time, helping to identify potential risks and make well-grounded decisions. This is especially important in asset management and credit risk.
2. Process automation: AI automates many routine tasks, such as processing transactions and managing accounts. This lowers servicing costs and reduces the likelihood of errors.
3. Financial advice and customer service: virtual assistants powered by AI can give clients personalized financial recommendations, improving service quality and increasing customer loyalty.

AI in education
‍**Education also gains significantly from adopting AI, which supports individualized learning and makes educational processes more effective.
1. Adaptive learning: AI makes it possible to build adaptive curricula that adjust to the individual needs and knowledge level of each student. This supports a deeper understanding of the material and better academic results.
2. Automated assessment: AI systems are used to automatically grade written work and tests, which reduces the load on teachers and makes assessment more objective.
3. Virtual tutors and assistants: AI supports the creation of virtual tutors that can help students learn at any time, answering questions and explaining difficult topics.
These trends show that AI is becoming a key tool that helps improve and optimize processes across various industries, creating new opportunities for growth and greater efficiency ​(Toxigon, IT Craft, McKinsey & Company, CSIRO).

When you use the Synthetic RAG technique, always name the specific sources or data areas that need to be included. This helps produce more accurate and useful content that matches the request.

Try it in GPTunneL