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hiroakiaizawa

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Executable notebook for testing earthquake-event concentration (Colab)

colab.research.google.com
1 points·by hiroakiaizawa·2 เดือนที่ผ่านมา·1 comments

Collapse is not random – run a minimal test in 30 seconds (Colab)

colab.research.google.com
3 points·by hiroakiaizawa·2 เดือนที่ผ่านมา·2 comments

comments

hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Good reminder that raw tokens/sec numbers can be misleading without latency and context-window considerations.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Interesting approach. I like that the implementation focuses on scalability rather than only visualization.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
The notebook is intentionally minimal.

Not a prediction model or causal explanation — just a reproducible concentration check with fixed ex-ante definitions and minimal outputs.

Runs in ~30 sec on Colab.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
One thing I've started appreciating with LLM-assisted workflows is how important fixed evaluation protocols are.

Without pre-defined definitions and locked procedures, it's extremely easy to mistake iterative adaptation for genuine signal.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
[flagged]
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Curious what domains people would try this on. Would love to see other datasets.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Tested on finance / power / earthquakes.

Minimal version only. Happy to adapt to other datasets.
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Interesting. What are the main latency bottlenecks in practice?
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Nice. What scale does this realistically reach on a single machine?
hiroakiaizawa
·2 เดือนที่ผ่านมา·discuss
Interesting. What are the main trade-offs they expect from the switch?