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What are some common data preprocessing techniques used before training a generative AI model?
Common data preprocessing techniques used with a generative AI model before training include data cleaning, where missing values and inconsistencies are addressed, and data normalization, which scales features to a standard range to ensure uniformity. For example, data augmentation can be performedRead more
Common data preprocessing techniques used with a generative AI model before training include data cleaning, where missing values and inconsistencies are addressed, and data normalization, which scales features to a standard range to ensure uniformity. For example, data augmentation can be performed to increase the size of the dataset as well as to diversify it by making various transformations to images. Crucial tasks for any text dataset are tokenization and encoding. In addition, the use of dimensionality reduction methods like PCA (Principal Component Analysis) simplifies data by maintaining the most important characteristics, hence increasing efficiency and performance when a model is trained.
See lessHow does cache memory improve the performance of a computer system, and what are the different levels of cache?
Cache memory improves the performance of computer systems by holding data that is frequently accessed by the user and the instructions of programs closer to the CPU. It reduces the time in which the data are retrieved as compared to the main memory, meaning lower latency and a faster execution of prRead more
Cache memory improves the performance of computer systems by holding data that is frequently accessed by the user and the instructions of programs closer to the CPU. It reduces the time in which the data are retrieved as compared to the main memory, meaning lower latency and a faster execution of programs. The cache memory hierarchy is normally available at three levels: L1, L2, and L3. Cache memory capitalizes on temporal and spatial locality to keep average memory access time low, hence enhancing overall efficiency.
The computer memory cache is organized into levels in such a way as to increase performance by minimizing the time taken to access data. The smallest and fastest level is the Level 1 (L1) cache located on the chip of the CPU, storing necessary data for ready access. The Level 2 (L2) cache is again located on or near the CPU but is larger and a bit slower, though it still provides secondary storage for frequently used data. The Level 3 (L3) cache is larger but shared among several cores, thereby providing a more general data reservoir, albeit one that is slower to access compared to L1 and L2. A few systems even provide for a Level 4 (L4) cache, the largest and slowest of them all; sometimes it may be on a separate chip or integrated into main memory itself, where it acts as an extra cushion against CPU/RAM wait states.
See lessHow does cache memory improve the performance of a computer system, and what are the different levels of cache?
See less