This document will introduce you to the example of what Vald can do. Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine, which uses NGT as the core engine of Vald, and Vald manages to integrate with Kubernetes.
You cannot generally search your unstructured data using the inverted index, like images and videos. Applying a model like BERT or VGG can convert your unstructured data into vectors. After converting them into vectors, you can insert them into the Vald cluster and process them in the Vald cluster.
Here are some general use cases of Vald or vector search engines.
Image and video processing
You can use Vald as the image/video processing engine to search the similar images/videos or analyze the image/video for your use case.
Vald is capable of processing a huge number of images at the same time, so its case fits with your use case.
Here are some examples of what you can do with images and videos using Vald.
- Search by image
- Face recognition
- Product recommendation based on images
- Image/Video analysis
- Image/Video deduplication
Audio processing is important for personal assistant implementation.
Vald can act as a brain of the personal assistant function, conversation interpreter, and natural language generation.
Here are some examples of what you can process using Vald.
- Personal assistant
- Speech recognition
- Natural language understanding and generation
Using a text vectorizing model like BERT, you can process your text data in Vald.
Here are some examples of the use case of text processing using Vald.
- Search by text
- Product recommendation based on text
- Grammar checker
- Real-time translator
Vald can process the vector data, you can analyze every data you can vectorize.
Here are some examples of the use case of data analysis.
AI malware detection
To detect the malware using Vald, you need to vectorize the binary file and insert it into Vald first. You can analyze your binary by searching for a similar binary in Vald. If your binary closely resembles the malware binary, you can trigger the alert for users.
By applying the price optimization technique using Vald, you can find the most optimized price for your business. You can apply models like GLMs to achieve it and use Vald as a machine learning engine for your business.
To analyze the social relationship of users, you can suggest to them their related friends, page recommendations, or other use cases. You can apply different models to analyze social data and use Vald as a recommendation engine for your business.
Advanced use cases
Besides the general use case of Vald or vector search engine, Vald supports a user-defined filter that the user can customize the filter to filter the specific result.
For example when the user chose a man’s t-shirt and the recommended product is going to be searched in Vald.
Without the filtering functionality, the women’s t-shirt may be searched in Vald and displayed because women’s t-shirt is similar to the men’s t-shirt and it is very hard to differentiate the image of men’s and women’s t-shirt.
By implementing the custom filter, you can filter only the man’s t-shirt based on your criteria and needs.