Ciro Santilli @cirosantilli 37

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Zurich Instruments by

Ciro Santilli 37 Updated 2025-07-16

www.zhinst.com/europe/en/quantum-computing-systems/qccs

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All the financial advice you’ll ever need fits on a single index card by

Ciro Santilli 37 Updated 2025-07-16

This is a good concept. For the ammount most people save, having a simple and easy to apply investment thesis is the best way to go.

All the financial advice you’ll ever need fits on a single index card

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Finance guru by

Ciro Santilli 37 Updated 2025-07-16

A person who gives financial advice, notably personal finance advice. Some of them are questinable guru-like beings, and many are on YouTube.

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Passive income by

Ciro Santilli 37 Updated 2025-07-16

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python/abc_cheat.py by

Ciro Santilli 37 Updated 2025-07-16

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Python special method by

Ciro Santilli 37 Updated 2025-07-16

docs.python.org/3/reference/datamodel.html#special-method-names

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python/infer.py by

Ciro Santilli 37 Updated 2025-07-16

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python/dataclass_cheat.py by

Ciro Santilli 37 Updated 2025-07-16

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python/dataclass_hash.py by

Ciro Santilli 37 Updated 2025-07-16

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python/typing_cheat/hello.py by

Ciro Santilli 37 Updated 2025-07-16

The hello world!

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python/typing_cheat/infer.py by

Ciro Santilli 37 Updated 2025-07-16

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python/typing_cheat/union.py by

Ciro Santilli 37 Updated 2025-07-16

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Python Protocol by

Ciro Santilli 37 Updated 2025-07-16

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python/pytorch/matmul.py by

Ciro Santilli 37 Updated 2025-07-16

Matrix multiplication example.

Fundamental since deep learning is mostly matrix multiplication.

NumPy does not automatically use the GPU for it: stackoverflow.com/questions/49605231/does-numpy-automatically-detect-and-use-gpu, and PyTorch is one of the most notable compatible implementations, as it uses the same memory structure as NumPy arrays.

Sample runs on P51 to observe the GPU speedup:

$ time ./matmul.py g 10000 1000 10000 100
real    0m22.980s
user    0m22.679s
sys     0m1.129s
$ time ./matmul.py c 10000 1000 10000 100
real    1m9.924s
user    4m16.213s
sys     0m17.293s

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PyTorch model by

Ciro Santilli 37 Updated 2025-08-08

This section lists specific models that have been implemented in PyTorch.

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Ciro Santilli 37 Updated 2025-07-16

Contains several computer vision models, e.g. ResNet, all of them including pre-trained versions on some dataset, which is quite sweet.

Documentation: pytorch.org/vision/stable/index.html

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HHL algorithm by

Ciro Santilli 37 Updated 2025-07-16

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Organization developing quantum dot quantum computer by

Ciro Santilli 37 Updated 2025-07-16

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QMUL research group by

Ciro Santilli 37 Updated 2025-07-16

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ResNet v1 vs v1.5 by

Ciro Santilli 37 Updated 2025-07-16

catalog.ngc.nvidia.com/orgs/nvidia/resources/resnet_50_v1_5_for_pytorch explains:

The difference between v1 and v1.5 is that, in the bottleneck blocks which requires downsampling, v1 has stride = 2 in the first 1x1 convolution, whereas v1.5 has stride = 2 in the 3x3 convolution.
This difference makes ResNet50 v1.5 slightly more accurate (~0.5% top1) than v1, but comes with a small performance drawback (~5% imgs/sec).

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