Breaking the Memory Wall: TurboQuant KV Cache Quantization on Apple Silicon
Author(s): Algomaster Originally published on Towards AI. Implementing Google Research’s TurboQuant algorithm on MLX- for 5× KV cache compression confirmed, quality benchmarks coming in Part 2 Local LLMs on Apple Silicon face one hard constraint: unified memory is finite. A 26B parameter …
Part 19: Data Manipulation in Statistical Profiling
Author(s): Raj kumar Originally published on Towards AI. Statistical profiling sits at the intersection of data validation and analytical insight. In banking operations, descriptive statistics are not academic exercises. They are diagnostic tools that surface anomalies in payment flows, quantify credit portfolio …
Building Your First AI App in Oracle APEX — For Free
Author(s): Sarfaraz Merchant Originally published on Towards AI. In Part 1 of this series Guide to Your OpenRouter API Key, we grabbed our “Universal Key” from OpenRouter. Today, we are going to put that key to work. Prerequisite: Must Have API Key …
Building AI-Ready Backends With Spring Boot in 2026
Author(s): FutureLens Originally published on Towards AI. Building AI-Ready Backends With Spring Boot in 2026 Modern applications are no longer just CRUD systems — they’re expected to integrate intelligent features like recommendations, automation, and natural language interactions. That shift has pushed backend …
Stop Defaulting to Rolling Updates: 6 Kubernetes Deployment Strategies Explained
Author(s): Aditya Jha Originally published on Towards AI. Deploying software isn’t just about pushing new code; it’s about how safely and deliberately you roll it out. Deploying new software is easy. Deploying it safely is an art. Kubernetes gives you powerful primitives, …
Denoising
Author(s): Sefa Bilicier Originally published on Towards AI. Introduction Have you ever taken a photo in low light and noticed those grainy, discolored spots that make the image look unclear? That graininess is called “noise,” and it’s not just a problem for …
Building ML in the Dark: A Survival Guide for the Solo Practitioner
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Boitumelo on Unsplash No GPU cluster. No data team. No ML platform. Here’s what actually ships. Most ML content is written for teams that have things. A labelled dataset. An MLOps platform. …
TAI #199: Gemma 4 Brings a Credible US Open-Weight Contender Back to the Table
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, Google DeepMind released Gemma 4, and I think this is the most consequential US open-weight release in quite a while. China has …
The Claude Code Leak Didn’t Hurt Cursor. It Forced a More Honest Competition.
Author(s): Siddhant Nitin Patil Originally published on Towards AI. On March 31, 2026, 512,000 lines of Claude Code’s source code hit the public internet. Within hours, developer Twitter had catalogued every unreleased feature. KAIROS, the always-on background agent. Dream, the self-healing memory …
ChatGPT’s Secret Codes: 30 Commands That Can Save You Hours
Author(s): Yelpin Sergey Originally published on Towards AI. Picture this: you ask ChatGPT to write copy for a landing page. Technically, the result looks fine. No obvious mistakes. The length is acceptable. The text is readable enough. But it still falls flat. …
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