【人工智能】英文学习材料04（每日一句）

本文主要是介绍【人工智能】英文学习材料04（每日一句），希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

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Bag of Words (词袋模型)

Generative Pre-trained Transformer (GPT) (生成式预训练变换器)

Tensor Processing Unit (TPU) (张量处理单元)

NVIDIA (英伟达)

OpenAI

Model Fine-Tuning (模型微调)

Model Quantization (模型量化)

Model Deployment (模型部署)

Retrieval-Augmented Generation (RAG) (检索增强型生成器)

Vector Similarity (向量相似度)

01 Bag of Words (词袋模型)

The Bag of Words model is a fundamental text processing approach. It involves transforming text into fixed-length vectors by counting the frequency of each word’s occurrence. This model disregards the grammar and the order of words but provides a simple way to analyze text.

fundamental（基本的、根本的）
occurrences (出现次数)
disregarding (忽略)

02 Generative Pre-trained Transformer (GPT) (生成式预训练变换器)

GPT, or Generative Pre-trained Transformer, represents a cutting-edge AI technology developed by OpenAI. It's designed to generate text that mimics human writing styles by predicting the next word in a sequence, based on the words that precede it. GPT models are pre-trained on a vast corpus of text, allowing them to generate coherent and contextually relevant text across a wide range of topics and styles.

represents（代表、表示）
mimics（模仿）
coherent (连贯的): 逻辑上一致，条理清晰的
contextually relevant (语境相关的): 与上下文紧密相关，符合语境的
input (输入): 提供给系统的数据或信息

03 Tensor Processing Unit (TPU) (张量处理单元)

Google's Tensor Processing Unit, or TPU, is an advanced hardware accelerator specifically designed to fast-track neural network machine learning processes. TPUs are engineered to process large volumes of data simultaneously, which significantly speeds up the training and inference phases of machine learning models, making them indispensable for complex AI computations.

advanced（高级的）
hardware（硬件）
accelerator（加速器）
simultaneously（同时）
significantly (显著地): 在很大程度上，明显地
speed up (加速): 使某事进行得更快
optimize (优化): 使变得最有效或最有效率
machine learning computations (机器学习计算): 执行机器学习算法所需的计算过程

04 NVIDIA (英伟达)

NVIDIA is globally recognized for its innovation in the development of graphics processing units (GPUs) for both gaming and professional markets. Beyond gaming, NVIDIA's GPUs have become pivotal in accelerating AI and deep learning tasks, providing the computational power necessary to process complex algorithms and large datasets quickly.

gaming（游戏打游戏）
graphics processing units (GPUs) (图形处理单元)
pivotal (关键的)
accelerating（加速器）

05 OpenAI

OpenAI is an AI research lab that dedicates itself to advancing artificial intelligence in a manner that maximizes benefit to humanity. It is known for developing state-of-the-art AI models, including the GPT series, which have significantly contributed to the field of natural language processing and beyond.

dedicates（致力于）
advancing（推进、进步）
manner（方式）
maximizes（最大化）

06 Model Fine-Tuning (模型微调)

Model Fine-Tuning is the process of taking a pre-trained AI model and making minor adjustments to its parameters to improve its performance on a specific task. This technique allows for leveraging large, pre-trained models on similar but smaller datasets, optimizing them for particular requirements without the need for extensive training from scratch.

minor（较小的）
adjusting (调整)
parameters（参数）
leveraging（撬动）
perform better (表现更好)
optimizing（优化）
extensive（大量的）
scratch（从零开始，从头开始）

07 Model Quantization (模型量化)

Model Quantization involves reducing the precision of the numerical values in a machine learning model. This process helps in making the model lighter and faster by decreasing its memory usage and computational requirements, which is particularly beneficial for deploying models on devices with limited resources.

numerical（数值的）
lighter（更轻量化）
memory usage (内存使用)
computational requirements (计算要求)
deploying (部署)

08 Model Deployment (模型部署)

Model Deployment is the stage in machine learning where a trained model is integrated with an application to perform its intended task in a real-world environment. It involves setting up the model to process live data and provide insights, predictions, or decisions based on that data.

stage（阶段）
integration (集成)
intended（预定的、意图的）
insights（洞察、理解）

09 Retrieval-Augmented Generation (RAG) (检索增强型生成器)

Retrieval-Augmented Generation combines the capabilities of a retrieval system, which fetches relevant documents or data, with a generative model, which uses this information to produce new content. This approach enhances the generative model's ability to provide more accurate and contextually appropriate responses.

capabilities（能力、功能）
retrieval (检索)
fetches（获取）
approach（方法）
contextually（根据上下文，根据语境）
appropriate（合适的）

10 Vector Similarity (向量相似度)

Vector Similarity is a measure used to determine the degree of resemblance between two vectors, often applied in NLP to compare the semantic similarity of words, sentences, or documents. High similarity scores indicate a closer relationship or greater similarity between the vectors.