https://medium.com/@nvidiaomniverse/chatgpt-and-gpt-4-for-3d-content-generation-9cbe5d17ec15#cid=ov01_so-yout_en-us 全球各行业对于三维世界和虚拟环境的需求正在以指数级增长。三维工作流是工业数字化的核心,用于开发实时模拟以测试和验证自主车辆和机器人,操作数字孪生以优化工业制造,并为科学发现铺...
a powerful text-based Artificial Intelligence (AI) tool. Without the need for human intervention, ChatGPT can respond accurately to customer inquiries using language models. Customer service agents are freed up to handle more complex conversations due to the elimination of repetitive tasks like answeri...
你还弄不清xxxForCausalLM和xxxForConditionalGeneration吗? confighiddenmodelself模型 大语言模型目前一发不可收拾,在使用的时候经常会看到transformers库的踪影,其中xxxCausalLM和xxxForConditionalGeneration会经常出现在我们的视野中,接下来我们就来聊聊transformers库中的一些基本任务。
ChatGPT写论文肯定只能作为辅助工具，除了以上辅助功能，当我们有一些大致思路，把这些思路提供给GPT，并提...
GPT 4是去年8月做好的，ChatGPT估计是OpenAI应对Anthropic 要推出的Claude专门做的，那时候GPT 4应该...
[6] N. Lee, W. Ping, P. Xu, M. Patwary, P. Fung, M. Shoeybi, and B. Catanzaro, “Factuality enhanced language models for open-ended text generation,” in Advances in Neural Information Processing Systems, 2022. 6 [7] H. Rashkin, D. Reitter, G. S. Tomar, and D. Das, “Inc...
(GRE) Writing for the two versions of GPT-4 that was released¹. This exam is one of many exams that tests the reasoning and writing abilities of a graduate. It can be said that the text generation from GPT-4 is barely as good as a university graduate, which isn’t bad for a “...
In fact, the top hit in Copyscape featured 45% matching text to the ChatGPT-4 results and even featured duplicate clauses. It can’t account for E-E-A-T.ChatGPT-4 simply can’t account for the experiential and first-hand expertise factors of great content that hooks audiences — which...
GesGPT: Speech Gesture Synthesis With Text Parsing from GPT. Nan Gao, Zeyu Zhao, Zhi Zeng, Shuwu Zhang, Dongdong Weng. [abs], 2023.3 ChatGPT4PCG Competition: Character-like Level Generation for Science Birds. Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro, Ruck Thawonmas, ...
最新ChatGPT GPT-4 自然语言理解NLU与句词分类技术详解 1. NLU基础 NLU是Natural Language Understanding的简称,即自然语言理解。一直以来都与NLG(Generation)任务并称为NLP两大主流任务。一般意义上的NLU常指与理解给定句子意思相关的意图识别、实体抽取、指代关系等任务,在智能对话中应用比较广泛。