Goals are for losers. Winners use systems. - Scott Adams @ScottAdamsSays
The @EntryLevelNet blog has a wonderful article that expands upon the above excerpt.
https://t.co/HaluxtdOUF
First GitHub push of 2026! 🚀
Custom refit strategy in GridSearchCV: balances precision, recall & prediction speed.
Because real-world "best" models need efficiency too!
https://t.co/BCQZRgykzS
More coming this year 💪
#MachineLearning#Python#scikitlearn
Selecting features using all data before splitting into folds for training/testing is a big source of train-test leakage. To demonstrate, I generated random data and labels, select down to 25 features, and train a model. Much better than random performance due to the leakage.
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This might be the most disturbing AI paper of 2025 ☠️
Scientists just proved that large language models can literally rot their own brains the same way humans get brain rot from scrolling junk content online.
They fed models months of viral Twitter data short, high-engagement posts and watched their cognition collapse:
- Reasoning fell by 23%
- Long-context memory dropped 30%
- Personality tests showed spikes in narcissism & psychopathy
And get this even after retraining on clean, high-quality data, the damage didn’t fully heal.
The representational “rot” persisted.
It’s not just bad data → bad output.
It’s bad data → permanent cognitive drift.
The AI equivalent of doomscrolling is real. And it’s already happening.
Full study: llm-brain-rot. github. io
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