Frequently asked questions

On what types of data is your model trained?

We trained our foundation model on a few hundred million video-text pairs, which is currently one of the largest video datasets in the world. Our dataset is comprised of information scraped from the internet and open-source academic benchmarks.

Where do you store your training dataset?

We have a valuable partnership with Oracle Cloud Infrastructure for both computing and storing data. We conduct all of our training on OCI, and we store a large number of video text pairs on OCI's Object Storage platform.

How do you handle user data privacy?

We transform user-uploaded videos into vector embeddings, which are then securely stored in a separate vector database. Please note that these embeddings cannot be reverse-engineered back into the original raw video. Additionally, we do provide a platform for users to play back their uploaded videos on the Playground, a sandbox environment that allows users to try out the features of the Twelve Labs Video Understanding Platform through an intuitive web page. We are also actively working towards SOC-2 compliance, ensuring that our practices meet the highest security & privacy standards. Please visit the Privacy Policy page for more information on how we collect, retain, and process your data.

How does your model handle temporal dimension within videos?

We utilize a technique known as Positional Encoding, which is employed within the Transformers architecture to convey information regarding the position of a sequence of tokens within the input data. In this case, the tokens refer to the key scenes within the video. This technique facilitates the integration of sequential information into our model while simultaneously preserving the parallel processing capability of self-attention within the Transformer architecture.

What is the maximum size of videos that can be stored in one index?

The Developer plan can accommodate up to 1,000 hours of video (whether in a single index or a combination of all indexes). For larger volumes, our enterprise plan would be best suited. Please contact us for more information at [email protected].

Can your model recognize natural sounds in videos?

Yes, the visual option when configuring our engine contains both visual and audio. This means we do take into account sounds and noise, such as gunshots, honking sounds, trains, thunder, and more. What's interesting is that the model learns the correlation between certain visual objects or situations with sounds that frequently appear together.

Can your model recognize text from other languages?

We are working on supporting multilingual queries.