Wu Enda Introduction
Wu Enda (1976-, English name: Andrew Ng), Chinese American, is associate professor of Department of Computer Science and Electronic Engineering at Stanford University and Director of Artificial Intelligence Laboratory. Wu Enda is one of the most authoritative international scholars in the field of artificial intelligence and machine learning. Wu Enda is also the co-founder (with Daphne Koller) of the online education platform Coursera.
Wu Enda and artificial intelligence upgrade manufacturing and processing industry
On December 14th, local time, Wu Enda once again announced its next startup project, Landing.ai, through the media platform in English. Wu Enda said that the project is designed to help traditional industries rely on the transformation and upgrading of artificial intelligence, and will provide training for the traditional enterprises from technology to architecture and training to employees. Currently, Landing.ai has reached strategic cooperation with Foxconn and others.
Wu Enda and Foton Chairman and CEO Terry Gou
After the project was announced, Wu Enda completed the third step of his venture after leaving Baidu. Previously, he had established deeplearning.ai, which integrates optimization resources and specializes in deep learning. It provides students and developers with courses on artificial intelligence. Later, according to the US Securities and Exchange Commission's official website, Wu Enda registered a $150 million artificial intelligence-oriented venture capital fund, AIFund.
“Many companies are exploring how to apply artificial intelligence. The transformation of artificial intelligence is not easy. Many artificial intelligence technologies are still very complex, and few teams can fully understand and effectively use these technologies. Outside the IT industry, artificial intelligence Talent is scarce," wrote Wu Enda.
Therefore, Wu Enda said that he will start from the manufacturing industry and use Landing.ai to help companies meet these challenges. Currently, Landing.ai is developing a series of artificial intelligence transformation projects, including providing new technologies, helping to adjust organizational structure to employee training, and so on.
In the article, Wu Enda also took photos of her own Foxconn Aseptic Plant and a group photo with Chairman and CEO of Foxconn Terry Gou. Since July of this year, Landing.ai has cooperated with Foxconn to develop artificial intelligence technology and talent training based on the core competitiveness of the two companies.
Wu Enda in Aseptic Factory
"As one of the world's leading large multinational technology providers, Foxconn has provided Landing.ai with a global platform for the development and deployment of AI technology and training solutions," said Wu Enda.
In addition to helping the manufacturing industry to transform and upgrade its technology and architecture, Wu Enda believes that training talents in the artificial intelligence era is even more challenging. It is reported that Landing.ai team has invested a lot of time and resources to create reemployment solutions for workers who may be unemployed. They are also negotiating training programs with various partners including local governments.
Born in 1976, Wu Enda, a Chinese-American, is one of the world’s most authoritative scholars in the field of artificial intelligence and machine learning, and is also the founder of Google’s brain plan. Another of Wu Enda’s early work was theSTAIR (StanfordArchitectIntelligenceRobot) project, the Stanford Artificial Intelligence Robot Project. The project eventually developed the widely used open source robotics software platform ROS. In 2013, Wu Enda was selected as one of “Time†magazine's 100 most influential people worldwide and became one of 16 representatives of the scientific and technological community.
In May 2014, Wu Enda joined Baidu as the chief scientist of Baidu, responsible for the leadership of Baidu Research Institute, especially the BaiduBrain program. Under his leadership, Baidu has made considerable progress in the field of artificial intelligence. He was an associate professor at the Department of Computer Science and Electronic Engineering at Stanford University and director of the artificial intelligence laboratory. His areas of research are machine learning and artificial intelligence, with a focus on Deep Learning.
About artificial intelligence
Another early work was theSTAIR (StanfordArchitectIntelligenceRobot) project, the Stanford artificial intelligence robot project. The project finally developed a widely used open source robot technology software platform ROS.
In 2011, Wu Enda established GoogleBrain project at Google. This project uses Google's distributed metering.
The framework calculates and learns large-scale artificial neural networks. An important research result of this project is that the 1 billion parameter neural network learned from deep learning algorithms on 16,000 CPU cores can learn to recognize only by watching videos without annotations without any prior knowledge. High-level concepts such as cats, this is the famous "GoogleCat". The technology of this project has been applied to the Android operating system speech recognition system.
Embracing New Technologies of Artificial Intelligence to Achieve Manufacturing Transformation and Upgrade
Another hot topic related to the manufacturing industry is: At the Guangdong branch of Alibaba Cloud Cloud Assembly last week, Ariyun, a giant in the domestic public cloud sector, extended an olive branch to manufacturing companies - including providing more cost-effective The public cloud computing capabilities will also accelerate progress in the hybrid cloud space and explore more possibilities in the field of artificial intelligence.
The above two news pieces are quite interesting to see together. On the one hand, the external market changes are inflexible, and on the other hand, the possibility of industrial transformation brought about by new technologies. If the former still has one or more kinds of possibilities, then the latter is a constant fact—only embracing new technologies such as cloud computing and artificial intelligence will make data intelligence a new momentum for the development of manufacturing companies. Only then can we truly realize the transformation and upgrading of the manufacturing industry.
Understand the three dimensions of the transformation and development of manufacturing
Whether it is Germany’s “Industry 4.0†or China’s “Made in China 2025â€, these national-level manufacturing development plans have made a three-dimensional distinction between manufacturing industries: 1. Marketing level: better connect the enterprise and the customer through new technology, the technology hears the customer's voice; 2. Production level: Through new technologies, production and manufacturing are more efficient, including supply chain system, production planning, workshop management, etc. 3. Logistics level: Accelerate the circulation of products through new technologies, allowing products to be delivered to customers faster.
In the above three dimensions, the level of market sales and logistics has been growing in the past few years. For example, at the market level, based on the popularity of e-commerce, more and more companies are entering the online sales field. Through the Internet platform, companies can better reach consumers, understand their needs, and further expand sales. This trend can be seen from the strong growth of Tmall's Double 11 events over the years:
At the logistics level, with the help of the radiation effects brought about by the e-commerce business (B2C, B2B), the growth rate and market size of the Chinese logistics market has grown rapidly. The figure below is based on the 2015 China Logistics Industry Investment Promotion Report produced by Deloitte Research:
Alibaba Cloud has already had many active explorations in the field of artificial intelligence this year. At the product level, from the prediction of the “I am a singer†champion by the small AI robot to the evolution of the ET release and the Taobot Chatbot customer service robot, Alibaba Cloud’s artificial intelligence goes further at the Hangzhou’s Yunqi conference in October – participating in the Hangzhou government. In the project, we jointly developed the Hangzhou City Data Brain. On the technical level, the latest figures from Alibaba Cloud's voice team show that the team has made breakthroughs in the deep learning and improvement of the LC-BlSTM model, which has increased the decoding speed of online speech recognition by a factor of three, thus changing the past that can only be used for offline speech recognition. Application dilemma.
Currently, various technology modules including deep recognition, speech recognition, image recognition, and natural language interaction are gradually becoming cloud-based. Cloud computing companies including Alibaba Cloud are opening up their technology and operational practices to more individuals. , large and small enterprises. These artificial intelligence experiences and technological breakthroughs from different fields will bring surprises to the manufacturing industry and are very much anticipated.
The two forecasting data further support the huge market space of “artificial intelligence + manufacturingâ€: a report from Boston Consulting Group titled “Industry 4.0—Future Productivity and Manufacturing Development Prospects†clearly states that cloud computing is The new technologies represented by big data analysis will bring about a 15%-25% increase in the productivity of China's manufacturing industry, and an additional value of 4-6 trillion yuan. Another figure from Xu Xiaolan, deputy chairman and secretary-general of the Chinese Institute of Electronics, shows that in 2015 China's smart manufacturing industry sales revenue has broken through to 1 trillion yuan.
Globally, manufacturing is still the core battleground of national competition. From the "Industry 4.0" in Germany to the "Made in China 2025" in China and the new US government's push for the return of manufacturing, a new round of manufacturing competition has started quietly. However, unlike before, the integration of artificial intelligence, cloud computing, and big data into manufacturing will become an important factor in this competition.
For China's manufacturing industry, new challenges also bring new opportunities for development. In addition to the booming domestic e-commerce market and circulation market, Alibaba Cloud in the cloud computing field has been leading the world for the sixth consecutive quarterly increase, and continues to exert its force in the field of artificial intelligence and overseas markets, all of which constitute the Chinese manufacturing industry. After the huge industrial upgrading, we have reason to expect China to truly enter the “manufacturing power†from the “manufacturing powerâ€.
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