What is WebGPT?
This model further developed the GPT-3 to answer open-ended questions more accurately using a text-based web browser.
WebGPT's prototype imitates the way people search for answers to questions online - sends search queries, follows links, and shifts up and down on web pages.
WebGPT collects information by giving a series of commands: "Search: ...", "Find on page: ..." or "quote:…". In this way, the model collects transitions from web pages and uses these transitions to create a response. Model is fine-tuned from the GPT-3 with the general methods we have used before.
WebGPT is trained to answer questions from a data set called ELI5.
ELI5 is a data set of open -ended questions from the subreddit. Three different models were trained and the best performance model produces 56 %preferred responses according to the responses written by human demonstrators.
Another important feature of WebGPT is that a device has access to the Graphic Processing Unit (GPU) using the WebGPU API. GPUs are particularly good in performing parallel calculations of the type required by machine learning models, which makes them a strong resource for WebGPT. WebGPT can make local calculations on the user's device using the WebGPU API. The results are rotated directly in the browser, which provides a quick and efficient application.
WebGPT has deep effects for web development to bring such powerful machine learning models to the browser. For example, if the calculations can be performed on the client side, there is a minimal delay potential with real -time data processing.
Another important feature of WebGPT is that users can perform complex language model calculations directly from their browsers. This reduces the need to calculate the server side using the processing power of users' devices. This allows WebGPT to run faster and more efficiently on users on their devices.
These features of WebGPT help users to search and process information more effectively on the web. However, since this technology is still under development, there are some difficulties and limitations. For example, the accuracy and reliability of the model depends on the quality and diversity of the training data set. In addition, due to the complexity and calculation requirements of the model, some users may not have enough processing power to run such a model.
As a result, WebGPT is an important step in the fields of language modeling and web research. This technology makes users search and processing information on the web, while at the same time allows users to use their devices more efficiently. However, since this technology is still under development, some technical challenges need to be overcome in order for users to effectively use such a model.
