Imagine a world where computers can learn and adapt like humans. They can make decisions, recognize patterns, and continuously improve the efficiency of tasks. All of this is powered by artificial intelligence, which is revolutionizing various industries, improving efficiency, and driving innovation and development.
But here’s the thing: AI isn’t magic. It requires a lot of data to learn, and raw data itself isn’t very valuable. Data must be organized, categorized, and interpreted before it can be meaningful to machines. This process is called AI data annotation.
AI data annotation is similar to teaching machines how to see, hear, and understand things. For example, if you want a self-driving car to stop when it encounters a pedestrian or a red light, during the AI training process, you need to annotate these objects in the pictures and videos used for training. This requires manually identifying and labeling pedestrians and red lights in images and videos. By providing this annotated data for AI model training, the car can learn to recognize and respond to pedestrians and red lights in reality.
Figure 1. This figure is an example of data annotation, with pedestrians marked in blue and vehicles marked in orange, which is used to train AI models for object recognition.
Market analysis
AI data annotation is critical to creating new products and services in various industries, including medical, retail, automotive, and banking. As demand increases, industry revenue has increased significantly and is expected to continue to grow in the future. As more companies adopt AI and develop new learning methods, the need for data annotation continues to rise.
The global data annotation solutions and services market is expected to grow from USD 11.6 billion in 2022 to USD 46.9 billion in 2030, with an estimated compound annual growth rate (CAGR) of 19.5%.
(Data source: https://www.kbvresearch.com/data-labeling-solution-and-services-market/)
Figure 2. Data annotation market size
How OORT Datahub revolutionizes the data annotation industry
Figure 3. How OORT Datahub works
Notes:
a. OORT Storage: Enterprise-level decentralized storage solution.
b. Olympus Blockchain: OORT’s Layer-1 blockchain, used to record and verify the data collection and annotation process.
The traditional data annotation industry is highly dependent on manual labor and lacks transparency, resulting in extremely low remuneration for workers. Leveraging blockchain and cryptocurrencies can significantly improve these issues. Through blockchain technology and cryptocurrency, AI data annotation has become safer and more convenient on a global scale. OORT Datahub pioneered this new approach, which it calls decentralized data annotation. Figure 4 provides a detailed comparison between OORT Datahub and the traditional data annotation industry.
Figure 4. Comparison between OORT Datahub and traditional data annotation products
Global Engagement
Decentralized data annotation allows people around the world to participate and earn cryptocurrency for their work. This approach breaks the limitations of traditional platforms, such as Toloka, which only recruits data collectors and annotators in specific countries and has difficulty making cross-border payments to these people. Similar to individuals making borderless transactions through Bitcoin, OORT Datahub contributors can easily earn extra income anywhere in the world.
Open and transparent
Blockchain enhances the transparency of the AI data annotation process. Every step from task completion to payment is recorded and verified on the blockchain. This transparency effectively reduces errors and disputes in data labeling and increases trust between AI projects and users involved in data annotation. In OORT Datahub, OORT uses its high-performance Layer-1 blockchain, Olympus Protocol, to ensure transparency in the data preprocessing process.
Data Security
All AI data on DataHub will be stored in OORT Storage. OORT Storage is OORT's enterprise-level decentralized storage solution. Both raw data and annotated data will be encrypted and stored in different locations in pieces to ensure that they will not be tampered with or accessed without authorization. In contrast, data managed by centralized cloud platforms are more vulnerable to hacker attacks due to vulnerabilities.
Instant Payment
Using cryptocurrency payments speeds up the payment process, making cross-border payments faster and less expensive. Smart contracts ensure efficient allocation of tasks, and once a task is completed, payments to contributors are made within minutes. In contrast, traditional methods are slow and complicated, often taking weeks or months. More importantly, OORT Datahub introduces a new reward mechanism where Datahub participants will receive NFTs as additional rewards. These NFTs give holders the right to share in future data sales revenue, providing users with higher income potential.
Community Collaboration Tool Development
OORT DataHub encourages community members to jointly develop small tools for AI data collection and annotation. With the participation of developers, data experts and AI projects, these small tools will be more efficient and practical.
QC
The quality of collected and labeled data has always been a pain point in the data labeling industry. Low-quality data will seriously affect the training effect of AI. The feature of OORT DataHub lies in its Proof of Honesty (PoH) consensus algorithm, which is a semi-automated quality control mechanism with human participation. The algorithm can quickly verify the accuracy of submitted data labels, unlike traditional companies that rely on manual verification, which is prone to omissions and human errors.
In short, OORT DataHub improves efficiency by simplifying and accelerating the data collection and annotation process. With the help of blockchain technology and decentralized storage services, it also enhances the security and privacy of data preprocessing, thereby encouraging the participation and contribution of global users.
