Announcing the Self-Learning Design Methodology in CES 2023
Being an AI SW/HW design service house, eNeural Technologies, Inc. is striving for delivering the best quality of embedded AI models one has to offer. To do so we developed an in-house toolchain to automate the AI process flow from labeling, modeling, training, augmentation, pruning, and quantization.
![SelfLearning](/_app/immutable/assets/eNeural_img_self-learning.06a2eb51.webp)
This automated process allows us to produce quality and lightweight inference models running on AI SoCs with 8-bit or smaller integer Neural Processing Units (NPU.) This process is now enhanced with a Self-Learning Design Methodology. It first uses a small number of labeled data to train a baseline target inference model. The toolchain then feeds the model with unlabeled data and quickly converges into a highly accurate one. We have applied this methodology to several user applications and obtained more accurate models in 6 times faster time-to-market.
You may find the illustration video on our Youtube channel.