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OORT lands on Shenzhen Data Exchange to expand its influence in the Asian artificial intelligence market
#oort #depin #ai
By listing on the Shenzhen Data Exchange, OORT will offer its products to the booming market of AI companies.
As a decentralized AI cloud platform, OORT is pleased to announce that it will be stationed in the Shenzhen Data Exchange, China's leading head data trading platform. This will enable OORT to provide its products and services, including its flagship products OORT DataHub and OORT AI, to a large number of AI companies across Asia.
Shenzhen Data Exchange: A Center for Data Innovation
Shenzhen Data Exchange is a subsidiary of Shenzhen Exchange Group. Its goal is to build a national data exchange. It is to establish a national trading platform for cross-domain and cross-border circulation of data elements, and to explore demonstration paths and trading models for the market-oriented allocation of data elements that are suitable for the development of China's digital economy.
By listing on the Shenzhen Data Exchange, OORT will offer its products to the booming market of AI companies.
As a decentralized AI cloud platform, OORT is pleased to announce that it will be stationed in the Shenzhen Data Exchange, China's leading head data trading platform. This will enable OORT to provide its products and services, including its flagship products OORT DataHub and OORT AI, to a large number of AI companies across Asia.
Shenzhen Data Exchange: A Center for Data Innovation
Shenzhen Data Exchange is a subsidiary of Shenzhen Exchange Group. Its goal is to build a national data exchange. It is to establish a national trading platform for cross-domain and cross-border circulation of data elements, and to explore demonstration paths and trading models for the market-oriented allocation of data elements that are suitable for the development of China's digital economy.
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Shenyang signed contracts with 11 data annotation industry companies
#oort #depin
On October 22, the first “Data Annotation Industry Conference and Supply and Demand Matchmaking Conference” was held in Beijing under the guidance of the Digital Technology and Infrastructure Construction Department of the National Data Administration and hosted by the Artificial Intelligence Special Class of the National Data Administration. The Shenyang Municipal Data Bureau released a data annotation industry map at the National Data Administration Data Annotation Supply and Demand Matchmaking Conference, and successfully signed cooperation framework agreements with 11 well-known companies in the fields of data annotation and artificial intelligence.
On the morning of the same day, the National Data Bureau released the "Artificial Intelligence Data Labeling Industry Atlas" compiled by the Shenyang Municipal Data Bureau in conjunction with the China Academy of Information and Communications Technology, China Telecom, China Electronics, and China Aerospace Science and Industry Network Information Development Co., Ltd. The atlas includes more than 500 upstream and downstream companies from all over the country that are deeply engaged in the data labeling industry chain, covering more than 16 industry fields. The "Artificial Intelligence Data Labeling Industry Atlas" consists of three parts: resource providers, data labeling core service providers, and supporting support providers.
On October 22, the first “Data Annotation Industry Conference and Supply and Demand Matchmaking Conference” was held in Beijing under the guidance of the Digital Technology and Infrastructure Construction Department of the National Data Administration and hosted by the Artificial Intelligence Special Class of the National Data Administration. The Shenyang Municipal Data Bureau released a data annotation industry map at the National Data Administration Data Annotation Supply and Demand Matchmaking Conference, and successfully signed cooperation framework agreements with 11 well-known companies in the fields of data annotation and artificial intelligence.
On the morning of the same day, the National Data Bureau released the "Artificial Intelligence Data Labeling Industry Atlas" compiled by the Shenyang Municipal Data Bureau in conjunction with the China Academy of Information and Communications Technology, China Telecom, China Electronics, and China Aerospace Science and Industry Network Information Development Co., Ltd. The atlas includes more than 500 upstream and downstream companies from all over the country that are deeply engaged in the data labeling industry chain, covering more than 16 industry fields. The "Artificial Intelligence Data Labeling Industry Atlas" consists of three parts: resource providers, data labeling core service providers, and supporting support providers.
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What is data annotation in AI training?
1. What is Data Annotation?
First, let’s talk about what data annotation is. There are many types of data annotation, such as classification, drawing boxes, annotations, tags, etc. We will discuss them in detail below.
To understand data labeling, you must first understand that AI is actually a partial replacement of human cognitive functions. Think back to how we learn. For example, if we learn to recognize an apple, someone needs to bring an apple to you and tell you that this is an apple. Then, when you encounter an apple later, you know that this thing is called an "apple."
Analogous to machine learning, if we want to teach it to recognize an apple, and you give it a picture of an apple directly, it has no idea what it is. We first need to have a picture of an apple with the word "apple" labeled on it, and then the machine learns a lot of features from the pictures. At this time, if you give the machine any picture of an apple, it will be able to recognize it.
First, let’s talk about what data annotation is. There are many types of data annotation, such as classification, drawing boxes, annotations, tags, etc. We will discuss them in detail below.
To understand data labeling, you must first understand that AI is actually a partial replacement of human cognitive functions. Think back to how we learn. For example, if we learn to recognize an apple, someone needs to bring an apple to you and tell you that this is an apple. Then, when you encounter an apple later, you know that this thing is called an "apple."
Analogous to machine learning, if we want to teach it to recognize an apple, and you give it a picture of an apple directly, it has no idea what it is. We first need to have a picture of an apple with the word "apple" labeled on it, and then the machine learns a lot of features from the pictures. At this time, if you give the machine any picture of an apple, it will be able to recognize it.
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oort: Decentralized Data Labeling
#oort #数据标注 #ai #百倍币计划
Why choose OORT DataHub? How is it different from traditional data labeling?
OORT is a decentralized data cloud platform designed to integrate global computing and storage resources, maximizing privacy and cost efficiency, providing a set of enterprise-grade decentralized solutions for generative AI and data-driven businesses.
Currently, one of the largest decentralized cloud infrastructures in the world has been established, with network nodes covering over 100 countries and generating millions of dollars in revenue. OORT's core technology has been published in top academic journals globally and has obtained a US patent. Its globally renowned clients and partners include many industry giants such as Lenovo Imaging, Dell, Tencent Cloud, and BNB Chain. OORT has a highly experienced and execution-oriented team, along with a top consulting committee composed of global experts. As a result, OORT has established and solidified its leading global position in the DePin field of artificial intelligence.
Why choose OORT DataHub? How is it different from traditional data labeling?
OORT is a decentralized data cloud platform designed to integrate global computing and storage resources, maximizing privacy and cost efficiency, providing a set of enterprise-grade decentralized solutions for generative AI and data-driven businesses.
Currently, one of the largest decentralized cloud infrastructures in the world has been established, with network nodes covering over 100 countries and generating millions of dollars in revenue. OORT's core technology has been published in top academic journals globally and has obtained a US patent. Its globally renowned clients and partners include many industry giants such as Lenovo Imaging, Dell, Tencent Cloud, and BNB Chain. OORT has a highly experienced and execution-oriented team, along with a top consulting committee composed of global experts. As a result, OORT has established and solidified its leading global position in the DePin field of artificial intelligence.
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What is 'Data Annotation'?
#OORT# #HundredfoldCoin# #AI# #datahub#
What is 'Data Annotation' and Its Role
Data annotation is an important step in the field of artificial intelligence (AI) deep learning. It involves pre-labeling 'images and other data' that need to be recognized and distinguished by artificial intelligence (computers), allowing them to continuously identify the features of these 'images and other data' and establish corresponding relationships with the 'labels,' ultimately enabling artificial intelligence (computers) to autonomously recognize these 'images and other data.'
What is 'Data Annotation' and Its Role
Data annotation is an important step in the field of artificial intelligence (AI) deep learning. It involves pre-labeling 'images and other data' that need to be recognized and distinguished by artificial intelligence (computers), allowing them to continuously identify the features of these 'images and other data' and establish corresponding relationships with the 'labels,' ultimately enabling artificial intelligence (computers) to autonomously recognize these 'images and other data.'
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GMTBurnVote
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#GMTBurnVote The #GMTBurnVote is a pivotal initiative by GMT DAO, inviting GMT token holders to decide the fate of up to 600 million GMT tokens, valued at approximately $100 million. This community-driven event underscores GMT DAO's commitment to transparency and decentralized governance.
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Supply Reduction: Burning 600 million GMT would significantly decrease the total supply, potentially increasing the value of remaining tokens.
Enhanced Value: A reduced supply could boost market confidence and demand.
Community Empowerment: This initiative exemplifies GMT DAO's dedication to decentralization and community involvement.
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Lock Tokens: Secure your GMT tokens until January 20, 2025, to cast your vote on the Polygon network.
Vote: Decide on the proposed token burn.
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By participating in the #GMTBurnVote, you play a crucial role in shaping the future of GMT, contributing to a more decentralized and community-focused ecosystem.
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