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One Open Source Project a Day (No. 48): karpathy/autoresearch —— Launching the Era of Self-Evolving AI Laboratories

Introduction "This may be the story of how it all began." —— Andrej Karpathy This is the No.48 article in the "One Open Source Project a Day" series. …

aiopensourcedeeplearningllm
Dev.to Apr 26, 2026, 01:32 UTC
EN

A CNN Grid Encoding for Snake AI That DOUBLES! the Best Published Score

A traditional Snake game grid has only 4 states each grid point can be in: empty, head, body, or apple. And for some reason every published Snake AI p…

aimachinelearningdeeplearningcnn
Dev.to Apr 25, 2026, 04:39 UTC
EN

Seeing Fast and Slow: Learning the Flow of Time in Videos

Seeing Fast and Slow: Learning the Flow of Time in Videos Time is everywhere in video — yet most computer vision models treat it as an afterthought. W…

machinelearningcomputervisionvideogenerationdeeplearning
Dev.to Apr 25, 2026, 00:53 UTC
EN

I Built a Pneumonia Detection AI on My MacBook — Here's Exactly How It Works

I just finished building a deep learning system that identifies pneumonia from chest X-rays with 96% accuracy and an AUC-ROC of 0.99. I ran the entire…

aideeplearningmachinelearningshowdev
Dev.to Apr 24, 2026, 11:37 UTC
EN

My Notes on Karpathy's Makemore part 1: Building a Bigram Language Model from Scratch

These are my notes on the first part of Andrej Karpathy's Makemore series. I intend to add notes on the remaining videos soon. If you spot any errors …

machinelearningdeeplearning
Dev.to Apr 19, 2026, 13:25 UTC
EN

The 270-Second Rule: How to Cut Claude Code API Costs by 90% with Smart

Anthropic's prompt cache has a 5-minute TTL. Orchestrator loops running faster than 270 seconds pay ~10% of full input token costs. Key Takeaways Anth…

aimachinelearningresearchdeeplearning
Dev.to Apr 17, 2026, 08:15 UTC
EN

A Vertically Integrated AI Stack: From Numerics to Silicon and Where Cognitive Architectures Like A11 Actually Matter

AI systems are no longer just software. Modern large‑scale models depend on a full vertical stack that spans: numerical formats, quantization strategi…

aimachinelearningdeeplearningsystemdesign
Dev.to Apr 17, 2026, 05:24 UTC
EN

Claude Code's Edge: Why Sonnet 4.5 Beats GPT-4o for Multi-File Projects

Claude Code's underlying model excels at understanding existing codebases and maintaining instruction fidelity in long sessions, making it the better …

aimachinelearningresearchdeeplearning
Dev.to Apr 17, 2026, 04:33 UTC
EN

Spiking Neural Network Hits 1B Parameters, Hints at New Behavior

A spiking neural network allegedly reached 1.088 billion parameters and trained from random initialization to a reported loss of 4.4 before the builde…

spikingneuralnetworkslargelanguagemodelsmachinelearningdeeplearning
Dev.to Apr 14, 2026, 21:36 UTC
EN

YOLO Evolution: Comparing YOLOv5, v11, v12, and v26 on the Cars Detection Dataset

Fig 1. YOLOv12 performing real-time vehicle detection on the Cars Detection Dataset. 1. Introduction: The Need for Speed and Precision Object Detectio…

computervisiondeeplearningobjectdetectionimagedata
Dev.to Apr 12, 2026, 07:56 UTC
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Image Classification Explained — Why k-NN Breaks and Linear Classifiers Matter

Image classification sounds easy until you remember that a computer never sees “objects.” It only sees pixel arrays. This post explains why that makes…

aimachinelearningcomputervisiondeeplearning
Dev.to Apr 11, 2026, 18:13 UTC
EN

CNNs Explained: How Image Classification Actually Works in Deep Learning

Understanding CNNs means understanding how models turn raw pixels into structured representations. This guide explains convolution, pooling, and archi…

deeplearningmachinelearningaicomputervision
Dev.to Apr 11, 2026, 18:10 UTC
EN

Multilayer Perceptron (MLP): A Practical Way to Understand Neural Networks

Multilayer Perceptrons (MLPs) are the foundation of deep learning. This guide explains MLP intuition, real-world usage, and when you should (and shoul…

aideeplearningmachinelearningprogramming
Dev.to Apr 11, 2026, 17:37 UTC
EN

Theoretical Foundations of Deep Learning (Why Neural Networks Actually Work)

Deep learning and neural networks work because of entropy, KL divergence, probability distributions, and optimization. This guide explains the theoret…

deeplearningmachinelearningaiprogramming
Dev.to Apr 11, 2026, 16:30 UTC
EN

Benchmark Shadows Study: Data Alignment Limits LLM Generalization

A controlled study finds that data distribution, not just volume, dictates LLM capability. Benchmark-aligned training inflates scores but creates narr…

aimachinelearningresearchdeeplearning
Dev.to Apr 11, 2026, 09:24 UTC
EN

AI News Update: April 10, 2026 - A Week of Breakthroughs and Concerns

AI News Update: April 10, 2026 - A Week of Breakthroughs and Concerns Published: April 10, 2026 | Reading time: ~5 min This week has been a whirlwind …

aimachinelearningdeeplearningprogramming
Dev.to Apr 10, 2026, 19:05 UTC

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