Reported by Machine Heart Machine Heart Editorial Team Can it hold context of any length? Here is a new model called ∞-former. In the past few years, the Transformer has dominated the entire NLP field and has also crossed into other areas such as computer vision. However, it has its weaknesses, such as not being … Read more
Source: Xixiaoyao Technology Author | Richard Since the advent of GPT-4, large models seem to have become increasingly intelligent, possessing an “encyclopedic” knowledge base. But are they really approaching human intelligence? Not quite. Large models still have significant shortcomings in knowledge integration and long-term memory, which are precisely the strengths of the human brain. The … Read more
Source | Eye on AIOneFlow Compilation and Translation | Jia Chuan, Yang Ting, Xu Jiayu “The hallucination problem of ‘serious nonsense’ is a common issue that large language models (LLMs) like ChatGPT urgently need to address. Although reinforcement learning from human feedback (RLHF) can adjust the model’s output for errors, it is not efficient or … Read more
This article introduces the ICML 2020 paper “Do RNN and LSTM have Long Memory?“. The authors of the paper are from Huawei Noah’s Ark Lab and the University of Hong Kong.. Author | Noah’s Ark Lab Editor | Cong Mo Paper link: https://arxiv.org/abs/2006.03860 1 Introduction To overcome the difficulties of Recurrent Neural Networks (RNNs) in … Read more