The
graph shows a decrease in the birth rate.
图表显示出生率的降低。
He has frowned, looked at the
graphs.
他皱了皱眉，又看了看图表。
He decided to show the results in a bar
graph.
他决定用条形图把结果表示出来。
The
graph shows a clear upward trend over the past year.
这张图表清楚地显示了过去一年的增长趋势。
She plotted the data points on a
graph to visualize the relationship between temperature and melting point.
她在图表上绘制数据点，以直观展示温度与熔点之间的关系。
In a network
graph, nodes represent individuals and edges represent connections between them.
在网络图中，节点代表个体，边则表示他们之间的连接。
The bar
graph presents the sales figures for each quarter of the fiscal year.
条形图展示了财政年度每个季度的销售数据。
The
graph is a powerful tool for analyzing complex systems and predicting future outcomes.
图表是分析复杂系统和预测未来结果的强大工具。
After adjusting for outliers, the scatter plot showed a strong correlation between hours studied and exam scores.
在排除异常值后，散点图显示了学习时间与考试分数之间强烈的关联。
The line
graph illustrates the fluctuation in stock prices over time.
折线图展示了股票价格随时间的变化情况。
The organization chart displays the hierarchical structure of the company, with managers at the top and employees at the bottom.
组织结构图展示了公司的层级结构，顶部是经理，底部是员工。
In a decision tree
graph, each branch represents a possible choice and its outcomes are depicted as terminal nodes.
决策树图中，每条分支代表一个可能的选择，其结果以终端节点的形式呈现。
The pie chart provides a visual representation of the distribution of percentages among different categories.
饼图以视觉方式展示了不同类别所占百分比的分布。
The medical platform, namely meeCERTAIN, can assist doctors with diagnosis and offer a medical graph for acute illness and injury.
医疗平台“meeCERTAIN”能够协助医生进行诊断，并为急性疾病和伤害提供医疗图表。
CEO Tim Cook, who said on Jan 2 that a slowdown in China’s economy and US-China trade tensions had caused a drop in iPhone sales in China, told Reuters on Tuesday that those tensions were easing: “If you were to graph up trade tension, it’s clearly less in January than it was in December.
Having launched Nest, the first knowledge graph database in the Chinese market, and enterprise-level AI entrance LiteMind, Mininglamp is developing fast with industry applications and rich practice cases, Lu Yanxia, senior research manager of Enterprise Research, IDC China, said.
Wang oversees the company's AI efforts in machine learning, big data, computer vision, natural language processing, speech technology, knowledge graph, robotics and augmented reality, according to Baidu.
[Photo/China Daily]Earlier in November, JD Finance launched an enterprise-level cloud services platform to use AI technologies, such as face recognition and graph calculation, to enhance work efficiency for financial institutions.
The cloud platform offers intelligent risk control, intelligent investment advisory, intelligent payment and transaction by virtue of face recognition technology, graph calculation and other AI technologies to enhance the work efficiency for financial institutions, said JD Finance.
"His Heineken career graph includes eight years in Europe, and eight years in Africa.
(A smile curve is a graph measuring an industry's value on the y-axis against the value chain on the x-axis. )
It has accumulated experience in speech and computer vision for perception, natural language processing and knowledge graph for cognition, as well as foundational technologies such as deep learning frameworks and platforms, large language models and AI chips, said Wang.
By breaking through the challenges of subgraph partition, separate storage, and node sampling for supermassive graphs, the team has developed an end-to-end supermassive graph neural network learning system.
It has also designed supermassive graph neural network learning algorithms and reasoning acceleration algorithms with software and hardware joint optimization.
It developed an end-to-end distributed optimization system that endows the platform with basic abilities to monitor supermassive dynamic graph neural network models on billions of nodes and edges.
These are, knowledge graph representation learning, including the complexity of internal relation types, the complicacy of internal reasoning paths, and the insufficient use of external rich information.
This will significantly improve the effectiveness of large-scale knowledge graph representation.
Based on the systemized algorithms, they released three open-source tool kits on GitHub, a major international open-source platform, forming a large-scale knowledge graph representation learning system.
The system has obtained more than 10,000 stars and 3,000 branch creations, becoming one of the mainstream systematized tools for knowledge graph representation learning.
High-performance computing, graph analytics key to IT's transformationMore efforts are needed to explore the application of high-performance computing and graph analytics, as the combination of the two cutting-edge technologies is likely to become a key driving force influencing future transformation of the entire IT computing sector, experts said.
It now can be used in more areas such as graph analytics, which can help deliver enhanced value.
High-performance graph computing is the core technology of artificial intelligence and big data, said Zheng Weimin, an academician at the Chinese Academy of Engineering.
Graph analytics is a set of analytic techniques that help explore relationships among organizations, people and transactions.
Market research company Gartner said in a report that by 2023, graph technologies will facilitate rapid contextualization for decision-making in 30 percent of organizations worldwide, and its average annual growth rate is forecast to exceed 100 percent.
Graph analytics can help data and analytics leaders find unknown relationships in data and review data not easily analyzed with traditional analytics.
For example, as the world scrambles to respond to the ongoing COVID-19 pandemic, graph technologies can relate entities across everything from geospatial data on people's phones to facial-recognition systems that can analyze photos to determine who might have come into contact with individuals who later tested positive for the coronavirus, Gartner added.
"More efforts are needed to develop high-performance graph computing technology.
Yang Juan, president of Haizhi Network Technology Beijing Co Ltd, a Beijing-based graph technology company, said graph computing has already been used in sectors such as finance and energy in China.
Experts said graph analytics, for instance, is being used to help identify fraud and money laundering activities and give warnings to financial sector players.
When it comes to e-commerce, graph analytics can also help offer more accurate online real-time product recommendations.
Wu Yongwei, a professor at the department of computer science and technology at Tsinghua University, said although high-performance computing and graph computing technologies have been developed in China for some time, the existing solutions still cannot meet the needs of complex types of operations, and there is not good synchronicity between hardware and software.
To help quicken the development of high-performance graph computing in China, Haizhi has partnered with Tsinghua University to jointly build a workstation in the sector.
"We aim to build a complete set of high-performance graph computing ecosystems and industrial clusters including hardware, software and industry application services to help build China's core industrial base for high-performance graph computing," Yang said.
She added that Haizhi has been dedicated to serving governments, financial institutions and energy companies with graph technologies for some time.
The company said that using text understanding technology combined with a language model and knowledge graph, the smart platform offers full-process medical services covering pre-, during-and post-diagnosis to the public.
Tencent Cloud's new products include technologies to identify fake facial images, a language model self-learning tool, graph computing engine as well as a big data platform to help enterprises fend off risks.
In the graph alongside, the red line represents China's economic growth, and the blue one shows China's money supply.
The first is centered around information technology infrastructure, such as cloud computing platforms, big data platforms, artificial intelligence and knowledge graph.
To better evaluate credit risk, JD Finance applies face recognition technology, biological techniques, graph calculations and other AI technologies.