WHY GPT3 AND CHATGPT IS LOSING THE GAME INFORMATIVE INFORMATION

what is gpt 3 GPT-3 examples One of the most notable examples of GPT-3's implementation is the ChatGPT language model. ChatGPT is a variant of the GPT-3 model optimized for human dialogue, meaning it can ask follow-up questions, admit mistakes it has made and challenge incorrect premises. ChatGPT was made free to the public during its research preview to collect user feedback. ChatGPT was designed in part to reduce the possibility of harmful or deceitful responses. Another common example is Dall-E. Dall-E is an AI image generating neural network built on a 12 billion-parameter version of GPT-3. Dall-E was trained on a data set of text-image pairs and can generate images from user-submitted text prompts. ChatGPT and Dall-E were developed by OpenAI. GPT-3 can also be used in the healthcare space. One 2022 study explored GPT-3's ability to aid in the diagnoses of neurodegenerative diseases, like dementia, by detecting common symptoms, such as language impairment in patient speech. GPT-3 can also do the following: create memes, quizzes, recipes, comic strips, blog posts and advertising copy; write music, jokes and social media posts; automate conversational tasks, responding to any text that a person types into the computer with a new piece of text appropriate to the context; translate text into programmatic commands; translate programmatic commands into text; perform sentiment analysis; extract information from contracts; generate a hexadecimal color based on a text description; write boilerplate code; find bugs in existing code; mock up websites; generate simplified summarizations of text; translate between programming languages; and perform malicious prompt engineering and phishing attacks. How does GPT-3 work? GPT-3 is a language prediction model. This means that it has a neural network machine learning model that can take input text and transform it into what it predicts the most useful result will be. This is accomplished by training the system on the vast body of internet text to spot patterns in a process called generative pre-training. GPT-3 was trained on several data sets, each with different weights, including Common Crawl, WebText2 and Wikipedia. GPT-3 is first trained through a supervised testing phase and then a reinforcement phase. When training ChatGPT, a team of trainers ask the language model a question with a correct output in mind. If the model answers incorrectly, the trainers tweak the model to teach it the right answer. The model may also give several answers, which trainers rank from best to worst. GPT-3 has more than 175 billion machine learning parameters and is significantly larger than its predecessors -- previous large language models, such as Bidirectional Encoder Representations from Transformers (BERT) and Turing NLG. Parameters are the parts of a large language model that define its skill on a problem such as generating text. Large language model performance generally scales as more data and parameters are added to the model. #gpt #ai #artificialintelligence #machinelearning #openai #gpsc #datascience #ml #aidungeon #gptw #naturallanguageprocessing #textgeneration #reginatheai #generativeart #art #aiquotes #k #talktotransformer #generative #runwayml #generativedesign #deeplearning #nstlicheintelligenz #gpsdrawing #gpsctaiyari #gpscpreparation #gpscstudy #gpsart #technology #gpsmobil #gpsccurrent #gpswatch #gujarati #science #developer #gpscbooks #all #gptwbrasil #gpscmaterial #gpstracking #gpstracker #gpsbrasilia #coding #gpsfarma #gpslifetime #gpsdecachoeira #gpracingindonesia #gpro #gpravelli #gps #gptrainee #marketing #rkiye #bigdata #aicopywritingtool #aitools #productivity #innovation #writingtool #aicontent

Видео WHY GPT3 AND CHATGPT IS LOSING THE GAME INFORMATIVE INFORMATION автора Общение на Русском: Чат с ИИ