Evaluating Graph-RAG vs. Standard RAG: A Hallucination Benchmark on Fact-Dense Queries
In this article, you will learn how to benchmark a deterministic 3-Tiered Graph-RAG system against a standard vector RAG pipeline on fact-dense queries, and what...
Have an idea for a lesson illustration, a project chart, or a comic for your next presentation? Nano Banana 2.1 lets you explore these formats with text prompts, making it easier to try different visual styles without switching between tools. In this article, we test Nano Banana 2.1 across four prac...
Introduction to Reinforcement Learning: Multi-Armed Bandit Simulation in Python
When machines learn by themselves
The post Introduction to Reinforcement Learning: Multi-Armed Bandit Simulation in Python appeared first on Towards Data Science.
The Consistency Quadrant: A Visual Guide to LLM Reliability
Mapping structural variance against execution outputs to estimate coding agent reliability without ground truth.
The post The Consistency Quadrant: A Visual Guide to LLM Reliability appeared first on Towards Data Science.
When Do PINNs Beat Classical Numerical Methods? A 1D vs 5D Experiment
I put a physics-informed neural network up against a plain finite-difference solver twice: once in 1D and once in 5D. The winner changed.
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JEV vs LLM as a Judge: The AI Evaluation Comparison
Many teams now use LLM-as-a-Judge to check AI answers, especially when exact-match tests fail for long or open-ended responses. But every judgement adds cost, delay, and possible bias, making this hard to scale. Jev, a small decision model from TypeSafe AI, takes a leaner route: it returns a short ...
A Google Team Measured Half of My Argument, and Left the Other Half Open
Towards Spec-Driven Test Automation: Part 3
The post A Google Team Measured Half of My Argument, and Left the Other Half Open appeared first on Towards Data Science.
How to Make a Cloud Read a Drone's Mind (and Cut Data Usage by 94%)
Two copies of one small AI model keep a remote machine in sync with the cloud, with no constant streaming. A beginner-friendly world model tutorial in PyTorch.
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5 Best Practices for Building Robust Python AI Libraries
This article covers building robust Python AI libraries specifically, Python AI SDK best practices, and what separates a production-ready AI package from one that only survives in its own demo.
Synchronous vs. Asynchronous Agent Execution: Architecture Patterns for Production
In this article, you will learn how synchronous and asynchronous execution patterns differ architecturally, and how to choose between them when deploying LLM-based agents to...
Elegant object matching from several viewpoints
The post Computer Vision: SIFT algorithm (Scale Invariant Feature Transform) appeared first on Towards Data Science.
How to Build a Cheap, Yet Reliable Model Router With Jev
Model routing can finally be a design choice rather than a system enhancement
The post How to Build a Cheap, Yet Reliable Model Router With Jev appeared first on Towards Data Science.
The Reversal Curse: Why a Language Model That Knows “A Is B” Can’t Tell You “B Is A”
A model can recall a fact in the direction it learned it and fail in the other. Here's a toy version of why
The post The Reversal Curse: Why a Language Model That Knows “A Is B” Can’t Tell You “B Is A” appeared first on Towards Data Science.
How to Use a PINN for a Navier-Stokes Inverse Problem
A from-scratch PyTorch build that recovers blood flow, viscosity, and wall shear stress in a narrowed artery from 40 noisy velocity readings
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Autoencoders vs. PCA: I Rigged the Test and PCA Still Won
A theoretical advantage that didn't survive contact with a real benchmark.
The post Autoencoders vs. PCA: I Rigged the Test and PCA Still Won appeared first on Towards Data Science.
What the ReLU Revolution Revealed About Biological Plausibility
The activation function was never a fixed biological commitment but a working hypothesis revised under empirical pressure.
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10 Python One-Liners That Will Make Your Code Cleaner and Faster
Get work done, and have seconds added back to your life since you won't be writing second, third or — *gasp!* — fourth line follow-ups to your impeccable typed line numero uno.
How the way we represent data can change what we think the data is saying
The post How Many Stories Can Your Data Tell? appeared first on Towards Data Science.