Foundations
ML Fundamentals
Neural networks, backpropagation, gradient descent — the maths behind AI
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Dev.to · Casey Li
📐 ML Fundamentals
⚡ AI Lesson
5h ago
Free Models as Test Doubles: A Dev/Prod Split That Saves Real Money
The most expensive place to call a paid model API is your own laptop during debugging. Every retry,...

Dev.to · L D (一π狐言)
📐 ML Fundamentals
⚡ AI Lesson
1d ago
I Built a Free CLI + MCP Server for GEO Audits - Here is What 1,200 Sites Taught Me
I spent two months building a free GEO (Generative Engine Optimization) audit tool with a CLI and an...

Dev.to · Papers Mache
📐 ML Fundamentals
📄 Paper
⚡ AI Lesson
1d ago
Adaptive compute techniques yield significant inference speedups across models
FlashMorph slashes the cost of designing hybrid attention models, needing only 20 M tokens and...

Dev.to · Michael Amachree
📐 ML Fundamentals
⚡ AI Lesson
2d ago
The cheapest model on my plan loses every benchmark. It still beats models charging 14x more.
I ran the $0.14 model against the $0.44 model expecting a close fight. It lost 4-0. Then I looked at what it does to everything priced in between.

Dev.to · Sachin Kr. Rajput
📐 ML Fundamentals
⚡ AI Lesson
2d ago
Blending and Voting: Four Noses, One Bottle, and the Blender Who Graded His Own Homework
The One-Line Summary: Voting has no learned parameters, so it cannot overfit and it cannot lie to...

Dev.to · Prabhakar Chaudhary
📐 ML Fundamentals
⚡ AI Lesson
2d ago
GC-OPD: Reconciling Teacher Likelihood with Verified Task Success
The mismatch inside standard on-policy distillation On-policy distillation trains a...

Dev.to · Lino Avila
📐 ML Fundamentals
⚡ AI Lesson
2d ago
JX N-Body Engine 0.1.0: Arbitrary-Precision Python and Numerical Validation
A Newtonian N-body engine built around a sixth-order Yoshida integrator, an independent Decimal...

Dev.to · Kutluk Atalay
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Beyond the Vector: Why Graph Neural Networks are the Strategic Choice for Enterprise Generative AI on GCP
In the current epoch of Artificial Intelligence, the industry remains singularly preoccupied with the...

Dev.to · Jordan Huang
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Don't Trust the First Token: A Streaming Latency Autopsy on Free Model Servers
Streaming changes everything. Or so I thought. Then I measured it. The first token is a...

Dev.to · Efrain Garay
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Go 1.27's SIMD ties with NumPy until the data fits in cache
I measured Go 1.27's experimental simd package against NumPy. They tie out of cache and lose inside it, and the reason is not the language.

Dev.to · Efrain Garay
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Go 1.27's SIMD ties with NumPy until the data fits in cache
I measured Go 1.27's experimental simd package against NumPy. They tie out of cache and lose inside it, and the reason is not the language.

Dev.to · Roman Koropets
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Computing WHO growth percentiles on-device
Every baby tracker shows growth percentiles. "Your daughter is in the 72nd percentile for weight." It...

Dev.to · sagar jain
📐 ML Fundamentals
⚡ AI Lesson
3d ago
Model Routing in Production: Cheap First, Escalate on Doubt
Route most requests to the cheapest model that passes your evals, and send a request to the expensive model only when a cheap, checkable signal says the...

Dev.to · ömer faruk aydın
📐 ML Fundamentals
⚡ AI Lesson
3d ago
How I built a crypto signal generator that beat fixed-weight strategies by 37% Sharpe
Combining 13 technical indicators in an XGBoost model with Bayesian-optimized hyperparameters - a complete Python pipeline.

Dev.to · Alok Kumar
📐 ML Fundamentals
⚡ AI Lesson
4d ago
Part 1 — What Actually Happens When Code Runs
When we write: const result = add(10, 20); Enter fullscreen mode Exit fullscreen...

Dev.to · Nerav Doshi
📐 ML Fundamentals
⚡ AI Lesson
4d ago
Compared Quantization Levels: Q4 vs Q8 vs FP16 on llama3.2:1b
Context: A model's weights — the numbers it uses to reason — are normally stored at high precision,...

Dev.to · Christian Pichichero
📐 ML Fundamentals
⚡ AI Lesson
4d ago
Point-in-Time Fundamentals for Numerai Signals: Killing Lookahead in Your Feature Join
If you build features for Numerai Signals from fundamentals, the single most common way to silently...

Dev.to · Josef Doornink
📐 ML Fundamentals
⚡ AI Lesson
4d ago
Choosing the Right GPU for Your Model — A Sizing Method, Not a Guess
Choosing the Right GPU for Your Model — A Sizing Method, Not a Guess OK,...

Dev.to · Tom Jones
📐 ML Fundamentals
⚡ AI Lesson
5d ago
Who your model works with matters more than which model you picked
The short version, for anyone who does not benchmark models for a living Every few weeks a...

Dev.to · Shashi Bhushan Savarn
📐 ML Fundamentals
⚡ AI Lesson
5d ago
Predicting CPU Spikes
Predictive System Health Checks: What I Learned Testing ARIMA, SARIMA, and Prophet on Infrastructure...

Dev.to · Timevolt
📐 ML Fundamentals
⚡ AI Lesson
5d ago
From Zero to Hero: Preparing for FAANG Interviews in 3 Months – A Journey Inspired by *The Lord of the Rings*
The Quest Begins (The "Why") Honestly, I used to stare at a blank editor and feel like...

Dev.to · Serguey Asael Shinder
📐 ML Fundamentals
⚡ AI Lesson
5d ago
Make the Model Show Its Work
Don't just ask for the answer. Ask how it got there. A model will hand you a conclusion with total...

Dev.to · Samuel Umoh
📐 ML Fundamentals
⚡ AI Lesson
5d ago
Building Fault-Tolerant, Event-Driven Kafka Pipelines in Go: Reliable Reprocessing & Dead Letter Queues
A practical guide to building reliable event-driven systems in Go using Apache Kafka. Learn how to...

Dev.to · Quinn Li
📐 ML Fundamentals
⚡ AI Lesson
6d ago
A Free Server Is Enough to Test a New Model Before You Trust It
You do not need a large budget to find out whether a freshly announced model fits your system. A...

Dev.to · Ashkan Ahmadi
📐 ML Fundamentals
⚡ AI Lesson
6d ago
How We Hardened a Multilingual TypeScript Text Filter Against Real Bypasses and False Positives
Text filtering looks deceptively simple when the first version works on isolated examples. Give a...

Dev.to · Quinn Sun
📐 ML Fundamentals
⚡ AI Lesson
6d ago
Replay Your Last Ten Bugfixes Before You Trust a New Coding Model
Consider a small team that sees two model releases in the same week. One is DeepSeek-V4-Pro-0813,...

Dev.to · Dinesh Kumar Ramasamy
📐 ML Fundamentals
⚡ AI Lesson
6d ago
From API to GPU, Week 5: Tensors, the Data Structure Behind Every Model
Phase 2 of 8: Enough ML to understand inference. Week 5 of 32. Phase 1 was about running models....

Dev.to · Finley Zhou
📐 ML Fundamentals
⚡ AI Lesson
1w ago
A Free Model Endpoint Replied Twice, Then Went Silent. The Fix Was a C++ Replay Envelope, Not Retries
Late on a Tuesday, a C++ tooling team noticed their warning classifier was duplicating...

Dev.to · Alexander Kopylkov
📐 ML Fundamentals
⚡ AI Lesson
1w ago
Why Making AI Answer Faster Is Worth $1.5 Billion
Keeping an AI model fast enough to use is turning out to be the expensive part of building...
Simon Willison's Blog
📐 ML Fundamentals
⚡ AI Lesson
2w ago
GitHub Models is now retired
GitHub Models is now retired I missed this news until today, when the GitHub Actions run for my simonw/research repository failed with this error message: GitHu

Dev.to · sagar jain
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Build, Buy, or Call an API: How We Actually Decide
Clients ask me why we don't just build our own model. It's a fair question, and most of the time the honest answer is that building our own would be the slowest

Dev.to · Aviral Srivastava
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Serving Models with TensorFlow Serving
Unleash Your AI: Serving Models Like a Pro with TensorFlow Serving So, you've poured your...

Dev.to · oleg kholin
📐 ML Fundamentals
⚡ AI Lesson
2w ago
A Stroke Instead of a Picture: The Evolution of Recognition Paradigms as Exemplified by Speech and Handwritten Input
The problem of speech recognition in contemporary artificial intelligence systems can be described as...

Dev.to · dayu2333-jinyul
📐 ML Fundamentals
⚡ AI Lesson
2w ago
I Could Not Mentally Calculate Bitwise XOR in a Coding Interview — So I Built a Visual Calculator
After bombing a bitwise operations question, I built a free visual calculator that shows AND, OR, XOR, NOT, NAND, NOR, XNOR with binary alignment.

Dev.to · Li Zhuojun
📐 ML Fundamentals
⚡ AI Lesson
2w ago
I measured his app with his own code. He measured my claim with his own corpus.
This is part five of a series about pointing an append-only audit log at things that count tokens....

Dev.to · Michael Yousrie
📐 ML Fundamentals
⚡ AI Lesson
2w ago
A Pest test that asserts nothing: toContain takes needles, not a message
I added a test last week that was doing absolutely nothing, and it passed every time I ran it. The...

Dev.to · Probal Dhali
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Your AI Model Is 99% Accurate — So Why Is It Still Failing? 🤖
Machine Learning has a number that everyone loves to see: accuracy. You train your model, run the...

Dev.to · Jaypee
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Why MCP Servers Need Verification Before Production | MCP Workbench
Why MCP Servers Need Verification Before Production The Model Context Protocol (MCP) is...

Dev.to · Juan Carlos Isaza
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Cuando tu clasificador parpadea: histéresis para señales que oscilan
Una señal que cerca del umbral hace OK, CAÍDO, OK, CAÍDO dispara alertas o failovers en cada tembleque. La solución es vieja y elegante: no cambiar de estado ha

Dev.to · Yuri Peixinho
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Programação Funcional
Introdução A Programação Funcional tem raízes no cálculo lambda, formalizado pelo...
Dev.to · lu1tr0n
📐 ML Fundamentals
⚡ AI Lesson
2w ago
WeatherNext: DeepMind gana 24 horas de anticipación en huracanes
WeatherNext, el modelo de Google DeepMind publicado en Nature, predice trayectoria e intensidad de ciclones con un día extra de anticipación y ya ayud

Dev.to · Wesam Khallaf — Author of PyTorch From Ground Up
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Your CNN's Advantage Is One Assumption — and I Measured What Happens When It Breaks
A small convolutional network beats a plain flatten-and-feed-it-forward network by 7.0 points on...

Dev.to · Sandip Subedi
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Building a survey-based ML pipeline to find out what's really holding SEE and +2 graduates back
Building a survey-based ML pipeline to find out what's really holding SEE and +2 graduates back The...

Dev.to · Priyadharshiny J
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Building Smart Health API: A Production-Style REST API with CNN-Based Risk Prediction
By Priyadharshiny J — GitHub: priyadharshiny13 Overview Smart Health API is a backend...

Dev.to · clan chen
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Why I use reconstruction puzzles to keep interview algorithms fresh
The hardest part of algorithm interview prep was not learning binary search or two pointers for the...

Dev.to · allenhori
📐 ML Fundamentals
⚡ AI Lesson
2w ago
zhao-cli: a free, deterministic breaking-change gate for dbt
I kept hitting the same problem on almost every dbt project I worked on: a PR changes a column...

Dev.to · TuanPK Builds
📐 ML Fundamentals
⚡ AI Lesson
2w ago
Model AI Seat Cost Against a Defined Workflow Outcome
The plan price tells you what the vendor charges, not what the workflow costs. A small test...

Dev.to · Na'aman Hirschfeld (Goldziher)
📐 ML Fundamentals
⚡ AI Lesson
2w ago
300+ languages doesn't mean what you think: three tiers of code understanding
Every tool in this space leads with a language count. basemind's README says 300+. Serena says...
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