“THANOS is a
the volume of massive
image, video, audio
and text data
for machine learning
and deep learning
model's accuracy and
data analysis quality.”
The biggest factor that distinguishes THANOS from any other methods is that it reduces the size of the original dataset. Because it reduces the size from the very first stage in the AI modeling step, it also reduces the time and cost in the later steps as well. Moreover, it’s the biggest advantage that it can also save additional cost by reducing the size of the dataset prior to any other methods introduced previously.
Build and maintain SOTA AI modeling at low cost
While the size of data set reduced, it maintains same level of accuracy
in the initial stage will accelerate the following stages in the AI modeling
lowers the cost of building and maintaining AI models by decreasing the size of the original data set and hence lowering the server costs. the same level of accuracy is maintained despite the reduced data size. This also implies that the customers can now afford to add more training datapoints to improve model accuracy, thanks to the lowered cost. as the data size becomes smaller, the speed of AI modeling will be far more accelerated. Again, the accelerated speed can contribute to faster development and deployment of AI models.