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HOCIntelligentTechnologyGroup
Faculty, BIG DATA (information), Large language model(LLM), Generative Pre-trained Transforme model(GPT), Research Lab's "FBLGR Quality" is a leading company,AI Science and Technology Innovation for Global Sustainable Development.
Security,DX, ICT, AI, Agriculture, Medical, Human Resource Development, Future Prediction, SDGs, etc.





Geoffrey Hinton

Research ScienceTeam
Motivation-driven, based on passion, hard work, endless learning
Boldly go where no one has gone before and do what no one has ever done before




HOC Intelligent Technology With a registered capital of 50 million, HOC Intelligent Technology is based on the research and academic circles of prestigious universities such as Harvard University, Oxford University, Cambridge University, etc. It has a leading R&D team of top doctoral professors and strong technology accumulation, with more than 400 people, big data The solution takes the industry's "intelligent and digital" transformation as an opportunity to delve into the three vertical fields of "finance, transportation, and operators" to provide professional intelligent data services. It is headquartered in Nanjing and has offices in Shanghai, Beijing, Shenzhen, Hangzhou and other places. Project Delivery Center, HOC Intelligent Technology Nanjing Company is led by Dr. Guolong Cambridge Dr. Yu Honghong and a PhD team from Oxford University, Cambridge University, Harvard University, MIT, etc., ERP consulting, cloud technology, big data, blockchain, AI machine learning , experts in practical capabilities in RPA, OCR-AI, especially deep learning and other artificial intelligence fields, and a professional team with 40 years of work experience. Haniuqiao Intelligent Technology is a national-level A-level team in China. It is also a team of scientists that has received national science and technology support funds. It is a national key scientific research office in China. It is an academician of the Chinese Academy of Sciences and a professor of Tsinghua University. Integrating with technology trends, leading analytical technologies are used in government/local government, education/medical/health care, finance, manufacturing, logistics, communications/broadcasting, construction/real estate, electricity/gas/water, network, pharmaceuticals , agriculture, retail, manufacturing, transportation, sports, aerospace, advertising, IOT, ICT and other industries. Academician of the Chinese Academy of Sciences, member of IEEE, won the first prize in a patent product competition in ERP blockchain cloud technology, big data, artificial intelligence related fields (not limited to speech processing, including all fields of artificial intelligence), and competed with Alibaba, Tencent, Huawei, etc. Several contracts were signed. AI × 5G Face recognition has become the mainstream payment method, what you see is what you buy, short video AI animation × 5G, Metaverse, intelligent driving, finance, 5G telemedicine 5G AI Medical, intelligent driving, intelligent business, intelligent medical care, 5G robots, 5G materials, semiconductor sports Technology in fields such as entertainment is our mainstream. We are world-leading in key technologies such as separation and purification, innovative drugs, biotechnology, chip design, quantum dot display, multi-touch, nanospheres and low-carbon nanomaterials. Intelligent driving, intelligent manufacturing, Robots, smart medical care. Face and human body analysis technology, SLAM and 3D vision, general and professional image recognition, robot control and sensing, massive video understanding and mining, image and video processing enhanced medical image analysis, artificial intelligence computing platform, AI supercomputing platform, self-developed Training framework, AI high-performance storage, high-performance heterogeneous computing
Main business in the United States, United Kingdom and Japan - system and mobile application development.
Nanjing (China) - Professional services for scientific and technological research in China System development of information science, biological science and material science.
• Shenzhen (China) – develops environmental and energy systems for Chinese companies.
• Shanghai (China) – Autonomous driving in China, system development for medical companies.
• Hangzhou (China) – System development for Chinese manufacturing company DX.
• Wuxi (China) - Offshore development, SI and BPO for Chinese companies.
China
Nanjing
Shanghai
Beijing
Hangzhou
Wuxi
〒210089
Room 801-845, Chuangzhi Building, No. 17, Xinghuo Road, Jiangbei New District, Nanjing, China
*As part of measures to prevent the spread of the novel coronavirus, we will temporarily stop accepting telephone consultations.
email:1500467240@qq.com

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Story





Based on the original technology system and the deep learning platform as the core "brain", it lays out cutting-edge research in multiple fields and directions to quickly open up the application of AI in various vertical scenarios.
Our research always adheres to originality, continuous breakthroughs and innovations, and has established in-depth cooperative relationships with dozens of first-class universities and research institutes at home and abroad. It has profound academic accumulation in the field of artificial intelligence and a sound talent training mechanism. The Harvard Graduate School of Design, considered one of the best design schools in the world, cooperates with Harvard University, Cambridge University, Oxford University, MIT, Tokyo University, Kyoto University, Osaka University, Tsinghua University, Chinese Academy of Sciences and other famous universities
Qualifications and Honors
National high-tech enterprise •Double-soft enterprise in Nanjing •Key private high-tech enterprise in Jiangsu Province •CMMI3 •ISO9001 •ISO27001
The R&D center has Nanjing headquarters, Hangzhou headquarters, Shanghai headquarters, Taizhou branch, Lishui branch, Suzhou branch, etc., in Japan, the United Kingdom, the United States, and South Korea. . .
core advantages
HOC Intelligent Technology is
With Silicon Valley's excellent machine learning modeling algorithms, we continue to explore and pursue the application of machine learning and deep learning in the technology field. The current technical reserves in machine learning (referring to the code of the core algorithm independently developed by our model team) include:
Random forest, neural network, support vector machine, single model of decision tree class and bagging algorithm of the above single model
cross validation algorithm for machine learning
Implementation of stacking methods for various basic algorithms
gradient boosting machine algorithm for decision trees
Semi-supervised learning based on SVM, etc.
It mainly carries out basic research and applied research, application demonstration and industrialization in the fields of software technology, artificial intelligence and other fields. It is committed to breaking through core key technologies, accelerating the transfer and transformation of results, building a new think tank in the software industry, and creating a high ground for talents in the software industry. The joint R&D partners are the technical and talent advantages of the Institute of Software of the Chinese Academy of Sciences and the University of Cambridge Company in the software field. The company has grown rapidly since its establishment and now has deployed intelligent system software, a general software platform for service robots, an intelligent unmanned system training and evaluation platform, Five specific scientific research directions including cloud computing and big data, Internet of Things urban brain, etc. High-tech comprehensive research and top natural science research in 8 fields of agriculture, energy, electronic computing, laser, space science, high-energy physics and general engineering have participated in many a large project. Rockets and artificial satellites feature optoelectronic technology and integrate optics, mechanics, electricity, computers, and materials. It is a research enterprise developed in cooperation with multiple departments. The Chinese Academy of Sciences participates in the joint venture between the affiliated Institute of Optical Precision Instruments and Physics and the Shenzhou Manned Spacecraft. Research.
Cambridge University jointly researches development in pharmaceutical field
China Shenzhen Innovation and Entrepreneurship Competition International Competition Sino-Kazakhstan HOC Intelligent Technology Nanjing Co., Ltd. won the final award
The participating project is the world's largest blockchain artificial intelligence big data cloud platform, focusing on building a "R&D" global
tional Institute of Information and Communications Technology NICT




















Partner certification qualifications























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Team members




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Cooperation between China and Africa in jointly building the “Belt and Road”,Second-hand clothes are sold to Africa.In the African second-hand clothing market, China has become the largest exporter in Africa for the first time
Every year, everyone buys new clothes, and in 2018, 54.06 billion pieces of clothing were sold nationwide.
But few people pay attention to old clothes, new clothes buy and buy, so how to deal with old clothes?
01 Never too many clothes
In rural areas, the general lifespan of clothes is 3-4 years, especially for many middle-aged and elderly people, and they are reluctant to throw them away when they are old.
In towns, the general lifespan of clothes is 1-2 years, and for young people the use time is even shorter. But many old clothes were either discarded or piled up in the closet.
According to idle fish data, the idle old clothes produced by ordinary Chinese families weigh 60 pounds a year.
In today's era of women's clothing consumption, women buy clothes at least twice a month, and trendy clothing only stays for one season. 80% of these clothes are forgotten after the season, but the number of clothes purchased is still increasing at a rate of 15% per year.
Men have a lower impulse to buy clothes, purchasing on average once a month. But they don't give away their old clothes, and they rarely throw away their old clothes.
02 Lost to half of the Daqing oilfield in one year
The data shows that the average person in China buys about 10 pieces of new clothes per year, of which 3-5 are discarded. Between 26 million and 28 million tons of clothes are discarded every year, with a utilization rate of less than 1%, which is a huge waste.
Some people know that an important raw material for clothing fiber is crude oil, which is equivalent to discarding 24 million tons of petroleum crude oil every year, more than half of the Daqing oilfield production.
So at present, the treatment of old clothes is mainly the following 4 ways:
A. Public welfare donations
There will be many non-profit organizations or institutions online that will collect used clothes and regularly send them to poor mountainous areas in central and western China, or donate them to local people in need through charities.
In addition, in many first- and second-tier cities, there are some used clothes recycling bins. Some of these recycling bins are jointly organized by the government and enterprises, and some of the clothes will be sorted and used for charitable donations.
However, due to information asymmetry, there are now many public welfare organizations or poor schools, and old clothes are almost impossible to put down.
The first batch has not yet been processed, and the second batch has come again. Some departments received donations in 2009 and still have a backlog of hundreds of thousands of used clothes.
And the cost of used clothes donation is actually very high, from recycling, sorting, disinfection, cleaning, packaging, distribution and other links, the donation cost of an old clothes is about 12-15 yuan.
B. Sell or give away
More than 500,000 pieces of used clothes are sold every month, of which post-95 young people are the main force, accounting for 34%.
Post-95 young people are not only willing to buy old clothes, but also accept old clothes donations, and 30% of the used clothes donations in Idle Fish are included in the post-95s.
Of course, women are more willing to deal with second-hand clothing sales, 4 times more than men
C. Reprocessing
Whether it is an individual vendor or an organization, eventually the vast majority of used clothes are recycled and sorted by recycling plants.
Used clothes that cannot be sold twice, but that are not used for burning.
After sorting, it will be sold to downstream suppliers for recycling, and made into greenhouse insulation cotton, environmentally friendly gloves, environmentally friendly bags, sound insulation cotton, building materials, etc.
D. Resale
Either way, it is not the most impressive in terms of economic benefits.
For businesses specializing in the recycling of used clothes, it is only by sorting out about 90% of new clothes and selling them for secondary sales to make money.
At present, the living conditions of most families in the country have been significantly improved, and most of them will not buy old clothes to wear.
Because in China, it is very convenient to buy clothes, very cheap, there are many styles, and a very small number of used clothes flow into the local market.
So where are these huge quantities of old clothes being sold twice?
The answer is: Africa! Yes, it's Africa, and it's very profitable!
Africa"The World's Largest E-Waste Graveyard" Agbogbloshie, Ghana
From a medium- to long-term perspective, we will adopt cutting-edge technologies and proactively promote concrete measures that contribute to social structural transformation toward a decarbonized and recycling-oriented society that is expected to grow sustainably in the future.
300 million mobile phones discarded in Africa annually "Leaked from Japan" As for the recycling of e-waste, "there is a connection between Africa and Europe, and an international chain of resource circulation has been established. It can be expanded to other resources as well. I think the environmental value behind the business is great
In addition to promoting cross-border e-commerce (EC) as part of China's "digital innovation project" jointly implemented with Africa, live commerce events are also being held at the same time to introduce excellent African-made products such as coffee and crafts.
Talent overview/ Overview
The Scientific Research Laboratory strives to build an open and innovative talent ecosystem. At present, the overall size of the talent team has exceeded 4,000, including more than 2,600 full-time employees and nearly 300 academic leaders. Over 99% of researchers have a doctorate or above. A talent team that is “specialized in the field, high-end, and well-organized”. The laboratory adheres to the talent cultivation concept of hierarchical classification and practical cultivation, relies on the "Science Research Academy" base to coordinate the construction of a talent cultivation system, and focuses on creating training projects such as the "Pilot Plan". The laboratory adheres to the core orientation of talent evaluation based on innovation quality and practical contribution, connects various channels for talent development, stimulates talent creativity in an all-round way, and provides strong talent support for building national strategic scientific and technological strength.
Academician Team / Academician Team
It is composed of well-known experts at home and abroad to provide academic consultation and guidance. They are responsible for providing advisory opinions and suggestions to the council on academic issues such as innovative research directions, key development areas, major research tasks and goals, guiding and grasping the direction of scientific research in the laboratory, and conducting Assessment of academic work.
Successfully partnered hospitals
Jiangsu Provincial People's Hospital Jiangsu Provincial Hospital of Traditional Chinese Medicine Nanjing Gulou Hospital Nanjing Hospital of Traditional Chinese Medicine Nanjing First Hospital Affiliated Zhongda Hospital of Southeast University Nanjing Children's Hospital Second Affiliated Hospital of Nanjing Medical University Nanjing Brain Hospital Jiangsu Provincial Cancer Hospital Zhejiang Provincial People's Hospital Obstetrics and Gynecology Hospital Affiliated to Zhejiang University School of Medicine Zhejiang Provincial Hospital of Traditional Chinese Medicine ) The First Affiliated Hospital of Zhejiang Medical University, etc.

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system introduction
Existing AI-based clinical decision support systems (CDSS) are knowledge-based and mainly serve diagnosis. On the other hand, AlphaGo defeated world champion Lee Sedol, making everyone realize that deep reinforcement learning can use process data to discover new Go knowledge or patterns, thereby surpassing humans.
Clinical decision support systems can also greatly improve their intelligence level through deep reinforcement learning, especially in the direction of disease treatment. Harvard & MIT Medical School in the United States and others published a paper in Nature Medicine on the technical application guidelines of reinforcement learning in medical health. To provide guidelines for employing reinforcement learning for patient treatment decisions, they hope this will accelerate the rate at which observational cohorts can inform medical practice in a safe, risk-aware manner.
Our artificial intelligence team has started research and development work in this area, including data construction, algorithm development, software system development, etc. Our product is named Lingbo Weibu. Lingbo Weibu is taken from the "Book of Changes" and has a precise meaning.
In terms of data construction, we obtained access qualifications to the critical care database MIT, then localized it and developed data alignment software and a dimensionality reduction tool based on causality testing. In terms of algorithm development, for sepsis treatment strategies, we use the Deep Deterministic Policy Gradient (DDPG) algorithm, which surpasses the MIT team's DQN algorithm and allows patients to achieve a higher survival rate. At the same time, the model training time is faster and the stability is better. In terms of software system development, it integrates data and algorithms to obtain data from HIS and LIS in real time, and regularly outputs each patient's disease status and treatment suggestions through a visual interface for doctors' reference.
In addition to sepsis treatment strategies, we have also worked with several tertiary hospitals to develop treatment strategies for respiratory failure, renal failure, tumors and other diseases.
The joint postdoctoral research institutes now include Fudan University, Shanghai Jiao Tong University, Zhejiang University, East China Normal University, Nanjing University, Chinese Academy of Sciences and other academic research institutions.
——Clinical decision support system based on deep reinforcement learning

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