What's new in IntelligenceLab VC++ 8.0.0.0
Mar 1, 2021
- Redesigned Visual C++ support
- Added Byte and Char visual live bindings
- Significantly improved loading execution, and editing speed
- Significantly improved JSON support
- Improved IGDIPlus rendering performance
- Modified to use interface class function methods instead of constructors
- Redesigned pin path collection to significantly improve the speed
- Redesigned to set pin and properties owner fields on creation
- Improved pin information caching
- CreateLock replaced by Create with Lock parameter
- Improved FMX Design Time support
- Improved FMX support
New in IntelligenceLab VC++ 5.0.3 (Oct 12, 2012)
- Added support for Delphi / C++ Builder / RAD Studio XE3
- Added support for Visual Studio 2012
- Improved FireMonkey support
- Fixed memory leak for .NET generic filters
New in IntelligenceLab VC++ 5.0.2 (Oct 12, 2012)
- Added FireMonkey support.
- Added 64 bit support for VCL, FireMonkey, and .NET
- All .NET assemblies are now managed assemblies.
- The .NET assemblies are reduced by half combining low level and high level assemblies, and simplifying deployment.
- All .NET assemblies now contain the necessary 32 and 64 bit BPLs and DLLs internally simplifying the deployment.
- The .NET Visual C++ redistributables are no longer needed.
New in IntelligenceLab VC++ 5.0.1 (Oct 20, 2011)
- The managed assemblies are now rewritten in C# for better .NET 4.0 compatibility.
- Added support for .NET 4.0 and .NET 3.5 “Client Profile”.
- Significantly improved .NET type converters.
- Significantly optimized component loading performance in .NET.
- Major improvements in the .NET property editors.
- Small improvements in the Unicode support for VC++.
- Improved VisualStudio 2010 .NET support.
- .NET assemblies have been renamed to better match the Microsoft guidelines.
- Added .NET 4.0 assemblies.
New in IntelligenceLab VC++ 5.0 (Oct 20, 2011)
- Added Delphi XE and XE2 support.
- Added TILRadialBasisFunctionNetwork component.
- Training can be saved and restored.
- Neural network training progress can be monitored.
- Significantly improved multithreading model adapted for multicore systems, with advanced relaxed interlocking, and with optional per-component dedicated threads.
- Added new demos.