Abstract: Provided are techniques for identifying and correcting model focus drift during model training. A model is trained using an original dataset with data, and the is classified into clusters. A representation is assigned to each of the clusters. A first visualization dashboard with visualizations is generated, where each visualization represents a first data distribution of an associated cluster using the representation assigned to that cluster. The model is fine-tuned using a fine-tune dataset. A second visualization dashboard is generated by updating each visualization, where each visualization represents a second data distribution of the associated cluster. It is determined that a cluster of the clusters has focus drift based on changes between the first data distribution and the second data distribution. The focus drift is corrected by: adding the data of the cluster to the fine-tune dataset to form a combined dataset and fine-tuning the model using the combined dataset.

Abstract: A frequency modulation (FM) circuit, built in an electronic device, comprises an antenna circuit for signal receiving, an FM module connected with the antenna circuit for transforming FM signals of incoming signals into respective audio signals, and a controller connected with the FM module for forwarding the audio signals. The antenna circuit further includes an antenna, a low noise amplifier (LNA) and its matching circuit, a support structure, and a feed line. By providing the LNA and its matching circuit, the receiving sensitivity of the antenna circuit can be improved and the whole antenna circuit can be reduced to a size that is easily accommodated inside the electronic device. Also, an antenna circuit for the FM system circuit is provided as well.