Generative AI tools, like ChatGPT, typically have a cut-off date for the information they know due to the way they are trained. These models are trained on vast datasets, which include books, websites, articles, and other written content up until a certain point in time. The "cut-off date" represents the latest point at which the data used for training was collected.
There are several reasons for this:
1. Training Process: Training a large language model requires immense computational resources and time. The process involves feeding the AI massive amounts of text data and then refining its ability to predict and generate text based on that data. Once training begins, the model can't incorporate new information until a new round of training is started, which usually happens periodically rather than continuously.
2. Stability and Testing: After training, the model undergoes testing and fine-tuning to ensure it performs well across various tasks. Locking the model's knowledge to a specific cut-off date helps developers stabilize the AI's behavior and thoroughly test it without worrying about fluctuating information that might cause inconsistencies.
3. Quality Assurance: If the model were constantly updated with new information, it would be difficult to maintain quality control. Developers need to ensure that the data being fed to the AI is accurate and reliable. Periodic updates with clearly defined cut-off dates allow for more rigorous quality assurance.
4. Practicality: Given the scale of data involved, continuously updating the AI's knowledge in real-time would be impractical. It's more efficient to collect, curate, and then update the model's information in large batches, which is why the AI might not have knowledge of events or developments that occurred after its last training update.
This cut-off is why generative AI tools may not be aware of the latest events or newly developed concepts, and it's why they often remind users that their knowledge might be outdated.
Want to learn more about AI? Enroll in AI For Everyone, a beginner-friendly course by Andrew Ng on Coursera*.