Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing
Generative Pre-trained Transformer 4 (GPT-4) is the fourth-generation language model in the GPT series, developed by OpenAI, which promises significant advancements in the field of natural language processing (NLP). In this research article, we have discussed the features of GPT-4, its potential applications, and the challenges that it might face. We have also compared GPT-4 with its predecessor, GPT-3. GPT-4 has a larger model size (more than one trillion), better multilingual capabilities, improved contextual understanding, and reasoning capabilities than GPT-3. Some of the potential applications of GPT-4 include chatbots, personal assistants, language translation, text summarization, and question-answering. However, GPT-4 poses several challenges and limitations such as computational requirements, data requirements, and ethical concerns.
Code (0)
등록된 구현이 없습니다.
Tasks
Language ModelingLanguage ModellingQuestion AnsweringText SummarizationTranslationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Opportunities and challenges of ChatGPT for design knowledge management
Recent advancements in Natural Language Processing have opened up new possibilities for the development of large language models like ChatGPT, which can facilitate knowledge management in the design process by providing …
ManagementCreative Data Generation: A Review Focusing on Text and Poetry
The rapid advancement in machine learning has led to a surge in automatic data generation, making it increasingly challenging to differentiate between naturally or human-generated data and machine-generated data. Despite…
Text GenerationCausal Inference with Large Language Model: A Survey
Causal inference has been a pivotal challenge across diverse domains such as medicine and economics, demanding a complicated integration of human knowledge, mathematical reasoning, and data mining capabilities. Recent ad…
Causal InferenceLanguage ModelingLanguage ModellingLarge Language Model+2Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities
Converting natural language (NL) questions into SQL queries, referred to as Text-to-SQL, has emerged as a pivotal technology for facilitating access to relational databases, especially for users without SQL knowledge. Re…
Text to SQLText-To-SQLBridging Gaps in Natural Language Processing for Yorùbá: A Systematic Review of a Decade of Progress and Prospects
Natural Language Processing (NLP) is becoming a dominant subset of artificial intelligence as the need to help machines understand human language looks indispensable. Several NLP applications are ubiquitous, partly due t…
Systematic Literature Review