人工智能最新研究前沿进展_研究进展

人工智能最新研究前沿进展

Trends

发展趋势

Artificial Intelligence (AI) has seen exponential growth. Research paper filings in AI have followed suit and more than 30,000 have been filed on arxiv.org.

人工智能(AI)呈指数增长。 AI的研究论文备案也紧随其后，arxiv.org上已备案了30,000多个。

Pandemic has affected AI research too and can be seen in the drop of submissions in recent months

大流行也影响了AI的研究，最近几个月提交的论文数量有所减少

However healthcare-focused research has seen an upsurge with a spike during the pandemic.

但是，以医疗保健为重点的研究表明，在大流行期间会出现高潮。

Disciplines

纪律

AI research has become very multidisciplinary over the years as can be seen below. In addition to core disciplines of AI & Machine Learning, Computer Vision research has dominated over the years including Image & Video processing. Disciplines of Neural Computing, Robotics, Signal Processing & Language have also seen a good chunk of research.

如下所示，多年来，人工智能研究已变得跨学科。 除了AI和机器学习的核心学科外，多年来，计算机视觉研究也占据主导地位，包括图像和视频处理。 神经计算，机器人技术，信号处理和语言学科也进行了大量研究。

During the pandemic, some of these areas continue to dominate. Here are a top few filing disciplines.

在大流行期间，其中一些地区继续占主导地位。 以下是一些顶级的申请学科。

However, certain biological/ medical disciplines have seen an upsurge in AI-led research during the pandemic. Research around Biomolecules, Tissues & Organs, Molecular Networks, Medical/ Biological Physics, and Genomics has picked up.

但是，在大流行期间，某些生物学/医学学科的AI主导研究激增。 有关生物分子，组织和器官，分子网络，医学/生物物理学和基因组学的研究已经开始。

Concepts

概念

CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), GANs (Generative Adversarial Networks) & other algorithms using GPUs dominate across the years.

多年来，CNN(卷积神经网络)，RNN(递归神经网络)，GAN(生成对抗网络)和其他使用GPU的算法占据主导地位。

Top Few Concepts Across The Years 多年来最热门的概念

During the pandemic, the upshot in medical research has seen a lot of focus on X-Rays, CT scans, EEG, 3D image analysis & RNA focused methods. QA systems to query journals for faster access to answers or patterns have also seen an upsurge. Explainable AI (XAI) has taken precedence, especially in medical diagnosis.

在大流行期间，医学研究的重点是X射线，CT扫描，EEG，3D图像分析和RNA聚焦方法。 用于查询期刊以更快地获得答案或模式的质量检查系统也已经出现了高潮。 可解释的AI(XAI)已被优先考虑，特别是在医学诊断中。

Diseases

疾病

Diseases that AI is applied to has also shifted over the years. Cancer research is the main focus. In recent months Pneumonia related research has seen an increase. Diabetes continues to be a major focus area across the years.

多年来，应用AI的疾病也发生了变化。 癌症研究是主要重点。 近几个月来，与肺炎有关的研究有所增加。 多年来，糖尿病一直是重点关注的领域。

Future

未来

Core disciplines of AI continue to see an upsurge and so do some of the concepts like algorithms using CNNs, RNNs, Reinforcement Learning & other architectures. Computer Vision & Pattern Recognition along with Video, Audio, Speech Signal processing trends. However, a few areas are gaining more traction as we go to the future. AI in Language, Cryptography & Security, Human-Computer Interaction, and Networking & Internet Architecture are areas to watch out.

AI的核心学科继续蓬勃发展，诸如使用CNN，RNN，强化学习和其他架构的算法等概念也在不断涌现。 计算机视觉和模式识别以及视频，音频，语音信号处理趋势。 然而，随着我们走向未来，一些领域越来越受到关注。 语言，密码学和安全性，人机交互以及网络和Internet架构方面的AI是值得关注的领域。

Seems like research in AI is pointing towards a Sensed. Secured. Healthy. Networked. Human Connected. Spoken and Explained world.

似乎人工智能研究正指向有意识的人。 安全的。 健康。 联网。 人与人之间的联系。 口语和解释的世界。

翻译自: https://towardsdatascience.com/ai-research-evolution-107c7434d1f2

人工智能最新研究前沿进展