### [Download](https://drive.google.com/file/d/1t6irPsTSC9Yk9V9lW44IZ-ZGvJodty-h/view?usp=sharing), [Results](https://drive.google.com/file/d/1zvZUio10eiFxOAsC85SzlDXSQl9z66aK/view?usp=sharing), [Discussion](https://youtu.be/6nZzji0dlws). 

## C++ Generative AI Inference: Production Ready Speed and Control:

C++ is utilized across many software libraries for speed, and is widely used in operating systems, financial applications, and scientific simulations. Production ready generative artificial intelligence applications continue to implement C++ to ensure application performance, reliability, and flexibility. Open source LLaMA.cpp, GPT4All, Libtorch, and TensorFlow C++ permit a broad range of fast machine learning implementations. TensorRT (nVIDIA) and OpenVINO (Intel) heavily rely on C++ software designed for hardware specific to the manufacturer.

C++ was developed by Bjarne Stroustrup, and was released in 1985 <br>

C++ object-oriented programming (OOP): encapsulation, inheritance, and polymorphism for modularity <br>

C++ is widely used in Operating systems, Financial applications, and Scientific simulations <br>

C++ code is compiled into machine code, making it a fast and efficient language <br>

C++ is known for its: performance, reliability, flexibility, and complexity <br>

Generative AI Inference with C++ allows for fast and controllable answers to user questions  <br>

Python is more for training/fine-tuning models, which can be converted to C++ for speed  <br>

Many IDEs across Operating Systems utilize C++: XCode, CLion, VS Code, and more  <br>

PyTorch dedicates a significant portion of C++ code in its own Platform  <br> 

#cpp <br>

June 13th 2024 <br>

Kevin Kawchak