Static vs. Dynamic vs. Continuous Batching in LLM Inference
In this article, you will learn how static, dynamic, and continuous batching work in LLM inference, and why the differences between them matter at production...
Create a local CLI Agent from scratch completely for free
The post How to Build CLI Agents with Python & Ollama appeared first on Towards Data Science.
Scaling up and streamlining a multi-agent architecture doesn't necessarily entail escalated costs if you know how to properly implement these four strategies for saving token usage.
The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain?
What actually makes a Forward Deployed Engineer, told through one supply chain project.
The post The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain? appeared first on Towards Data Science.
Large language models understand text well, but they become less effective when information is scattered across documents or mixed with images and other media. Modern AI systems rely on vector databases, which store embeddings and enable similarity search across collections. LanceDB is a vector data...
When the Code Becomes the CEO: Why Your Next Manager Might Be a Decentralized Agentic Loop
In five to ten years, the sharpest manager in your company might not be human, might not sleep, and might exist entirely in shared GPU memory. This is the systems-level view of the algorithmic corporation — why middle management collapses into a protocol, what breaks in the current AI stack, and wha...
How to Debug AI Coding Agents When They Change the Wrong Thing
A practical tutorial for recording model tool requests, real function results, patches, checks, screenshots, and a saved run log.
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How Benders Decomposition Works Part I: Optimality Cuts
A friendly introduction to one of the most powerfull optimization techniques using the uncapacitated facility location problem
The post How Benders Decomposition Works Part I: Optimality Cuts appeared first on Towards Data Science.
How one open-source ecosystem made state-of-the-art AI accessible
The post The Python Ecosystem That Changed AI Development appeared first on Towards Data Science.
Claude Design is a research preview under Anthropic Labs, powered by Claude Opus' vision capability, generating interactive prototypes with working navigation, embedded video, voice input, and 3D elements.
What it actually takes to turn a company's scattered knowledge into something an LLM can reliably use — and why the demo is 5% of the work.
The post How to Build a Context Layer and a Company Brain appeared first on Towards Data Science.
The full conjecture is stated over abstract fields, but the counterexample is a concrete 3D function that we can explain and visualize using familiar geometric ideas and a little algebra.
The post A Simplified View of the Jacobian Conjecture appeared first on Towards Data Science.
How statistical physics explains the transition from deterministic predictions to generative AI.
The post How to Decode the Temperature Parameter in LLMs appeared first on Towards Data Science.
Why Your Best Predictive Model Gives the Wrong Treatment Effect
Why prediction-driven variable selection misses confounders and how Bayesian Adjustment for Confounding attempts to fix it.
The post Why Your Best Predictive Model Gives the Wrong Treatment Effect appeared first on Towards Data Science.
How to Create Custom Skills in Claude: A Step-by-Step Guide
Claude can review data, check code, write reports, and prepare presentations, but teams still end up repeating the same structure, validation rules, company standards, and final-check instructions in every conversation. That repetition wastes time and often leads to inconsistent results. Custom Skil...
Ollama vs. LM Studio vs. llama.cpp: Which Local AI Runtime Should You Use in 2026?
In this article, you will learn how Ollama, LM Studio, and llama.cpp differ across the dimensions that matter most to practitioners, and how to choose...
An Introductory Guide to Practical Constraint Decoding
With this introductory guide to practical constraint decoding, you'll no longer need to beg your model to "output valid JSON without including any markdown."
Don’t Just “Throw Adam at It”: Misunderstanding Adam Will Cost You
You "vibe coded" the import. Understand Adam's optimization dynamics, why it fails spectacularly, and how to fix it.
The post Don’t Just “Throw Adam at It”: Misunderstanding Adam Will Cost You appeared first on Towards Data Science.
Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way
The idea that makes backpropagation possible.
The post Backpropagation Explained for Beginners (Part 2): There Has to Be a Better Way appeared first on Towards Data Science.
“Los Movimientos”: The Routing Problem That Nearly Broke My Spirit
Using mathematical optimization to solve a pickup-and-delivery problem with time windows.
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In a world where human time is expensive, learn how to use it only when really necessary
The post Reducing Human Annotation with ML Active Learning appeared first on Towards Data Science.