Disclaimer: This review is based on publicly available release notes, technical documentation, and user reports. The specific build number referenced by the user is assumed to be a variant of the official R2023b x64 release.

Furthermore, R2023b introduces a new, faster automatic differentiation engine. This engine computes gradients and Jacobian matrices more efficiently, which is a game-changer for deep learning training and numerical optimization. Additionally, MATLAB Coder now supports SIMD (Single Instruction, Multiple Data) intrinsics in generated MEX code, providing performance improvements for users deploying algorithms as C/C++ code.

For users of legacy code or those with heavy Python integrations, the known performance regressions and deprecation warnings suggest that a thorough testing period is necessary before migrating production systems. However, considering the vast array of performance gains—from faster MEX code via SIMD to UI responsiveness in the Data Cleaner and Tiled Chart Layouts— represents a mature, stable, and highly optimized version of the software that pushes the boundaries of what is possible in a desktop engineering environment.

Automatic routing reduces visual clutter in massive block diagrams, keeping canvas layouts organized.

For years, Mac users running powerful M-series chips had to rely on Rosetta translation to run x64 MATLAB builds. R2023b changes everything by introducing native Apple Silicon support Better Performance: