DATA

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Single molecule sequencing advances enable deeper biological interrogation

By

@erictopol

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31 January 2026 15h54

A tour de force single molecule review @ScienceMagazine "the ongoing convergence of two foundational technologies in modern biology: sequencing and single-molecule biophysics……we are now poised to interrogate complex biological phenomena with previously
unattainable depth

→ View original post on X — @godofprompt

RTL’s modular AI breakthroughs in 2026

By

@godofprompt

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31 January 2026 11h17

This isn't just academic. RTL works on: → Image classification (CIFAR-10/100)
→ Speech enhancement (3 acoustic environments)
→ Implicit neural representations (within-image specialization) The era of "one model fits all" is over. Welcome to modular, data-aware AI. Paper:

→ View original post on X — @godofprompt

RTL reveals semantic data structure in deep layers

By

@godofprompt

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31 January 2026 11h17

The semantic alignment is beautiful: Related classes (cat, dog, deer) share more pruning structure in deep layers. Unrelated classes (airplane, truck) stay independent. RTL doesn't just find sparse networks – it discovers the SEMANTIC STRUCTURE of your data.

→ View original post on X — @godofprompt

Samsung’s RTL: Tailored Subnetworks for Data Classes

By

@godofprompt

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31 January 2026 11h16

The problem with current pruning methods: They assume ONE mask works for all data. Like forcing every student to learn math the same way. Samsung's RTL (Routing the Lottery) discovers specialized subnetworks – each tailored to specific classes, clusters, or conditions.

Machine Learning Techniques for Time Series Forecasting and Predictive Analytics

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31 January 2026 6h28

#MachineLearning for #TimeSeries with #Python — Forecast trends, Predict the future, Detect anomalies with state-of-the-art #ML methods: http://
amzn.to/3xf5ZdI by @benji1a ——————
#DataScience #AI #Forecasting #PredictiveAnaytics #AnomalyDetection #IoT #IIoT #DataScientist

Confirmation Bias in Statistics: Seeing Patterns That Aren’t Real

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31 January 2026 6h23

Confirmation Bias in #Statistics = seeing patterns in data that we want to see but they aren't really there.

Football Analytics with Python and R: Learning Data Science Through Sports

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31 January 2026 5h53

(American) Football #Analytics with #Python and R — Learning #DataScience Through the Lens of Sports: http://
amzn.to/46SZzNH
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#DataScientist #SportsAnalytics #AI #ML #MachineLearning #PredictiveAnalytics

Naive Bayes Classification Explained with Python Code and Resources

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31 January 2026 5h41

Naive Bayes Classification, explained with Python code: https://
github.com/taspinar/siml/
blob/master/notebooks/Naive_Bayes.ipynb
…
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Learn more in this book: http://
amzn.to/312hAHF
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#DataScience #MachineLearning #AI #ML #Algorithms #Statistics #DataScientist #Mathematics

Bayesian Data Analysis and Probabilistic Modeling Resources

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31 January 2026 5h38

Bayesian Data Analysis [download 677-page PDF #Statistics eBook] at http://
sites.stat.columbia.edu/gelman/book/
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Do it in #Pythonusing this Practical Guide to Probabilistic Modeling: http://
amzn.to/3w3tq9g —————
#DataScience #DataScientist #MachineLearning #ML #Inference #StatisticalLearning