![]() Visitor: who is luciano abriata? Assistant: Luciano Abriata is a biotechnologist, doctor in chemistry, artist and content creator. You see in bold my questions the rest is the chatbot’s answers and I write some lines with comments in-between: This is not very efficient because it is limited in the amount of information you can pass, and also because it consumes many tokens each time you send the prompt. I achieve this in a way called “few-shot learning” by the OpenAI people it essentially consists in preceding the questions of the prompt (to be sent to the GPT-3 API) with a block of text that contains the relevant information. Let me show you first this short conversation with the custom-trained GPT-3 chatbot. The former will make up stuff, or in the best case just not provide any answers, while the second will be more accurate in its answers, at least when you ask it about information that I provided it. Besides, the responses depend on the context so for example you can talk about a person by name and then refer to him or her with the corresponding articles.Īs an example, let’s compare the outputs of a regular GPT-3 chatbot when asked about me to those of a GPT-3 chatbot informed with a short bio about me and some of my projects. Rather, you can retrieve the information in a natural way. The best thing is that you don’t need to ask the questions in a very structured way, as you’d need for a regular question-answer-matched chatbot to understand you. When the questions refer to the topic you informed the chatbot with, then it will reply based on that content. Users can naturally chat with the bot through a web page, asking whatever they want. In this article we will see how to build a simple chatbot that knows about a specific topic that you provide as prompt. GPT-3 is very easy to work with, for example in Python or as shown here in JavaScript and PHP.We will in fact see here one of two possible ways to train your GPT-3 models ad hoc for your goals. This allows you to program chatbots that behave in ways you can tune, or even more interesting, that “know” about a particular topic you teach them. Despite not having a grasp on the executables (because it all runs online), GPT-3 is very customizable.We will see here how to achieve this with simple PHP and JavaScript. The above includes the possibility of writing web code that will call the GPT-3 API, so you can include the power of this tool in your web pages.I can use it just by including calls to the GPT-3 API in my source code. It runs online, so I don’t need to download anything to the computer or server where I want to use it.But among all language processing models, I find GPT-3 especially enticing because of these features: ![]() Trained with billions of parameters and huge loads of text corpora, GPT-3 is one of the largest models available out there. Depending on the input and exact flavor of GPT-3 used, the output text will conform to a task such as replying to a question asked in the input, or completing the input with additional data, or translating the input from one language to another, or summarizing the input, or inferring sentiments, or even crazier things such as writing a piece of computer code from an indication given in the input. Given an input text, GPT-3 outputs new text. Developed by OpenAI, GPT-3 is a machine learning model specialized in language processing.
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