Recently, I came across a LinkedIn post showing a C++ developer’s reaction to seeingfor the first time how array sorting is done in Python. Unsurprisingly, the simplicity of Python’s approach was shocking.
arr=[64,12,22,55,44]
bubble_sort(arr)
print("Sorted Array:",arr)AI has become prevalent in various domains, including software development. Many developers leverage generative AI to aid them in coding. Let’s explore the newcomer Llama3 and assess its suitability for C++ developers.
Related to Meta here’s a brief description of Llama3:
Our new 8B and 70B parameter Llama 3 models are a major leap over Llama 2 and establish a new state-of-the-art for LLM models at those scales. Thanks to improvements in pretraining and post-training, our pretrained and instruction-fine-tuned models are the best models existing today at the 8B and 70B parameter scale. Improvements in our post-training procedures substantially reduced false refusal rates, improved alignment, and increased diversity in model responses. We also saw greatly improved capabilities like reasoning, code generation, and instruction following making Llama 3 more steerable.
Certain developers may lack interest in AI generative tools due to their perception that the results are not yet mature. This sentiment is particularly pronounced among expert developers who swiftly identify areas for improvement in generated code. Nonetheless, I believe that for the majority of developers, generated code could serve as a valuable starting point for implementation, refactoring, or explanation purposes.
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