I Built a Deep Learning Framework from Scratch in C++ and CUDA (And Beat PyTorch's Speed Multiple Run)
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If you work in AI today, you are almost certainly using PyTorch or TensorFlow. They are incredible tools, but they are also massive black boxes. As an AI developer, I realized that relying solely on these frameworks meant I didn't truly understand the underlying hardware realities, memory mechanics, or how the math actually maps to GPU acceleration. So, I decided to strip away the abstractions. Over the last few months, I built Aakaar —a deep learning framework developed completely from scratch…
1Key Takeaways
- If you work in AI today, you are almost certainly using PyTorch or TensorFlow.
- They are incredible tools, but they are also massive black boxes.
- As an AI developer, I realized that relying solely on these frameworks meant I didn't truly understand the underlying hardware realities, memory mechanics, or how the math actually maps to GPU acceleration.
- So, I decided to strip away the abstractions.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that if you work in AI today, you are almost certainly using PyTorch or TensorFlow.
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