LAI #122: Word Embeddings Started in 1948, Not With Word2Vec
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we’re covering what happens when AI labs sit across the table from governments, why most AI-generated writing still sounds the same (and how to fix it), …
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 …
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 …
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. …
LAI #121: The single-agent sweet spot nobody wants to admit
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Your next AI system is probably too complicated, and you haven’t even built it yet. This week, we co-published a piece with Paul Iusztin that gives you a …
I Read Every Line of Anthropic’s Leaked Source Code So You Don’t Have To. Here’s What They Were Hiding.
Author(s): DrSwarnenduAI Originally published on Towards AI. 512,000 lines of TypeScript. A secret AI pet. An always-on daemon that dreams. A mode that hides from you that it’s AI. All of it now public, because someone forgot one line in a config …
A Plateau Plan to Become AI-Native
Author(s): Bram Nauts Originally published on Towards AI. AI will not transform because it’s deployed – it will transform because the way of operating is redesigned. The tricky part? Transformations rarely fail at the start, they fail in the middle – when …
AgentOps: Your AI Agent Is Already Failing in Production. You Just Can’t See It
Author(s): Divy Yadav Originally published on Towards AI. The practical guide to monitoring, debugging, and governing AI agents before they become a liability You shipped an AI agent. It worked in staging. Photo by authorFollowing the introduction, the article delves into the …
Why System Behaviour Must Be Designed, Not Improvised
Author(s): Muhammad Ejaz Ameer Originally published on Towards AI. By Muhammad Ejaz Ameer, Product & Decision Architecture Lead There is a moment in the life of almost every digital product when the team realises something uncomfortable: the system does not actually know …
The Loop: How an AI Swarm Surfaced a Governance Limitation, Then Tested the Fix
Author(s): Selfradiance Originally published on Towards AI. AgentGate is a runtime accountability layer for AI agents: before an agent can execute a high-impact action, it must lock a bond as collateral. Good outcomes release the bond. Bad outcomes slash it. The mechanism …
Meta Just Built an AI That Rewrites the Rules of How It Gets Smarter. Then It Rewrote Those Rules Too.
Author(s): DrSwarnenduAI Originally published on Towards AI. The complete breakdown of HyperAgents — what metacognitive self-modification actually means, why the old way always hits a ceiling, and the result that made the AI safety community sit up straight. Meta Just Built an …
LLM Benchmarks Are Junk Science
Author(s): Kaushik Rajan Originally published on Towards AI. An Oxford review of 445 benchmarks found 84% lack basic statistical testing. Models score 90% on standard tests but 2% on unseen problems. A 5-question smell test for any benchmark claim. Over the past …
Building a Long-Running Conversational AI Agent with Intelligent Context Management
Author(s): Jageen Shukla Originally published on Towards AI. Learn how to build an AI agent that remembers unlimited conversation history using Redis, ChromaDB vector search, and intelligent context management. Full source code available on GitHub and you can read this blog free …
TAI #198: Real-Time Speech AI Gets Serious: Google and OpenAI Race to Own the Voice Layer
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie Real-time speech AI has been progressing quietly for the past year, but the past few weeks have delivered enough to warrant a dedicated look. …
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