As the field of artificial intelligence continues to evolve, security and stability have improved, and so have the requirements for data quality. If the former algorithm model using the general data set is the rough food, then now the algorithm model needs to be customized nutritional meal. If companies want to further improve the ability to implement the model, they must gradually move away from the original common data set and Internet data, and actively engage in customized data collection to create a core data barrier. At present, the world-wide Alaya data labeling platform has been known for its pursuit of data quality. In a talk titled “AI is the new electricity”, the international authority on artificial intelligence, Enda Wu, highlighted the importance
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As the field of artificial intelligence continues to evolve, security and stability have improved, and so have the requirements for data quality. If the former algorithm model using the general data set is the rough food, then now the algorithm model needs to be customized nutritional meal. If companies want to further improve the ability to implement the model, they must gradually move away from the original common data set and Internet data, and actively engage in customized data collection to create a core data barrier. At present, the world-wide Alaya data labeling platform has been known for its pursuit of data quality.
In a talk titled “AI is the new electricity”, the international authority on artificial intelligence, Enda Wu, highlighted the importance of data “The rise of AI is changing the competitive landscape for companies. The barrier for companies is no longer algorithms, but data, so that the algorithm can use enough data to make the product work…”
So why do people in artificial intelligence continue to seek high quality data?
When faced with a poorly performing model, engineers spend months tinkering with product features and new algorithms, not realizing that the problem exists in their data. High-quality data can lead to greater breakthroughs for humans.
High quality data that is capable of understanding the problem you are trying to solve.
While AI systems are becoming more complex, we need advanced and clever human marker systems to teach and measure their performance. Models that currently know enough about the world to identify and classify misleading information will not increase in complexity by using more low-skilled workers. To identify algorithmic biases, we need high-quality data to identify the right world.
High-quality data can drive target functions consistent with human values
Models are often trained on datasets that are only approximations of their true goals, leading to unexpected divergences. Machine learning is about teaching computers to work the way we want them to, and we achieve our goals by showing positive examples. So in order to build high-quality models, the most important skill a machine learning engineer needs to master should be building high-quality datasets and making sure they match the problem at hand.
If we want AI to solve our own real-world needs, we need to think deeply about the datasets that define our models and give them a certain human touch.
Alaya is always innovating and seeking world-wide growth when it comes to data quality.Alaya is a distributed AI data platform that integrates collection and labeling, that originated from Swarm Intelligence and connects communities, data, and AI through Social Commerce, providing the AI industry with high quality scalable data and full protection of its ownership and privacy. Provide high quality bid collection data for AI industry and has achieved exponential growth through its built-in social recommendation mechanism. The community is used to solve the pain point of lack of data and scarcity of labor for AI practitioners and to bring group intelligence together across time and space and reorganize it efficiently.
In terms of data quality, Alaya has achieved the following three things:
- The theoretical guidance of the discipline of community intelligence, linking global communities, using the community economy to constantly link to everyone in the world, so that the collection of data is no longer constrained by space, and global data collection and labeling can better highlight the quality of data;
- With a built-in hierarchy and a unique intelligent recommendation algorithm, alaya accurately assigns needs to users with the same attribute tags, ensuring that needs are addressed by professional groups and improving data quality. User data will be an important part of the industry’s best quality data;
- Alaya’s unique data quality assessment system ensures the accuracy and consistency of data after it is collected and labeled, and addresses errors and inconsistencies to guarantee customers the highest quality data sets.
Alaya was founded on the idea of providing high quality data to help the industry grow. In the field of artificial intelligence, which is increasingly pursuing data quality, companies like Alaya will be the future of the industry.