Introduction
Our subnet incentivizes the development of distributed solutions aimed at identifying LLM-generated content.
Given the rapid growth of LLM-generated text, such as ChatGPT's output of 100 billion words daily compared to humans' 100 trillion, we believe that the ability to accurately determine AI-generated text will become increasingly necessary.
Problem
With the recent surge in LLMs appeared many cases where we do actually want to recognize where this text was generated by AI or written by human. Let's explore some scenarios to highlight the potential and significance of LLM detection.
Use Cases
- For ML-engineers: Whether you're sourcing training data, developing a foundational LLM, or fine tuning on your own data, you need to ensure generative text does not make it into your training set. We can help.
- For teachers: While tools like ChatGPT offer numerous benefits for the educational sector, they also present opportunities for students to cheat on assignments and exams. Therefore, it is crucial to differentiate between responses authored by genuine students and those generated by LLMs.
- For bloggers: Recently many bloggers faced with a lot of ai-generated comments in their social networks. These comments are not really meaningful but attract the attention of their audience and promote unrelated products. With our subnet, you can easily identify which comments are ai-generated and automatically ban them.
Additional Applications
- For writers: By utilizing an LLM detection system, writers can assess their text segment by segment to identify sections that appear machine-generated. This enables them to refine these areas to enhance the overall human-like quality of their writing.
- For recruiting: Have you also noticed receiving far more applications with lower candidate quality? AI has enabled people to spam hiring teams with artificially written cover letters and assessments. We help you find the candidates who care about your mission and your quality standards.
- For cyber security: Scammers can leverage LLMs to quickly and easily create realistic and personalized phishing emails. We can help you determine the provenance of any document or email you're reviewing.
As you can see there are a lot of areas where AI detection can be very helpful. We believe that creating llm-detection subnet not only provides a useful tool at a good price for people to use, but also encourages competition to make better and smarter ways to spot AI-generated content.