How Transaction Network Analysis Catches Laundering Patterns that Rule-Based Systems Miss
Author(s): Bhavesh Awalkar Originally published on Towards AI. How Transaction Network Analysis Catches Laundering Patterns that Rule-Based Systems Miss Money laundering moves an estimated $800 billion to $2 trillion through the global financial system every year. In the United States, financial institutions …
Nvidia Just Walked Into the Laptop Business — And Apple Should Be Paying Attention
Author(s): MayhemCode Originally published on Towards AI. Subtitle So this happened today. Literally today — June 1, 2026 — Jensen Huang walked onto a stage at the Taipei Music Center for Computex 2026 and announced that Nvidia is now in the laptop …
RAG Fails Silently: Debugging Retrieval, Citations, and Unsupported Claims
Author(s): Samarth vinayaka Originally published on Towards AI. RAG Fails Silently: Debugging Retrieval, Citations, and Unsupported Claims A practical look at debugging the evidence chain in RAG systems: retrieval, context selection, answer claims, citation support, and local failure reports. RAG systems often …
I Replaced a $6,500/Month Developer with Claude Code (Opus 4.8) and Codex (GPT 5.5)
Author(s): Felix Kebaya Originally published on Towards AI. I Replaced a $6,500/Month Developer with Claude Code (Opus 4.8) and Codex (GPT 5.5) A client came to me last month with a problem. They were paying a junior developer $6,500/month for feature work …
NVIDIA’s 550B Nemotron Embarrassed Every US Open Model — and It Shouldn’t Run This Fast
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. NVIDIA's 550B Nemotron Embarrassed Every US Open Model — and It Shouldn't Run This Fast NVIDIA just shipped a 550B-parameter open model that scores 48 on the Artificial Analysis Intelligence …
Claude Code Agent Teams and Worktrees: One Claude Is Not Enough: Running Parallel Sessions Without Collisions
Author(s): Rick Hightower Originally published on Towards AI. Claude Code Agent Teams Part 15: How git worktrees and agent teams let you scale Claude Code beyond a single terminal, without overwrites, lost edits, or duplicated work In this article: A single Claude …
Claude Code Plugins: Your Claude Code Setup Is Trapped in One Repo. Plugins Set It Free.
Author(s): Rick Hightower Originally published on Towards AI. Claude Code Plugins 14: Plugins are how to package the skills, subagents, hooks, and MCP servers you have already built into a Claude Code plugin your whole team installs in a single command. You …
Sizing AI/ML Projects: A Repeatable Method That Tracks Reality
Author(s): Konrad “Stellars” Jelen Originally published on Towards AI. Sizing AI/ML Projects: A Repeatable Method That Tracks Reality Not the perfect estimate – a practical, repeatable methodology that has held up surprisingly well against what projects actually cost Why I am sharing …
The MLOps Component Nobody Builds in Their Portfolio (And Why It Matters Most)
Author(s): EMMANUEL NWANGUMA Originally published on Towards AI. The MLOps Component Nobody Builds in Their Portfolio (And Why It Matters Most) Most ML engineers know what a feature store is. Almost none have built one. Here’s everything I learned doing it from …
I Ran Claude Code on My MacBook With vllm-mlx — It Embarrassed llama.cpp by 87%
Author(s): Chew Loong Nian – AI ENGINEER Originally published on Towards AI. I Ran Claude Code on My MacBook With vllm-mlx — It Embarrassed llama.cpp by 87% I did something this week that I assumed would be a slow, frustrating downgrade: I …
What Nobody Tells You About Putting LLMs Inside Your Data Pipeline
Author(s): Sunil kumar Reddy Originally published on Towards AI. What Nobody Tells You About Putting LLMs Inside Your Data Pipeline A practitioner’s honest account — written from financial data engineering — of what breaks, what surprises you, and what six months of …
6 AI Terms Everyone Uses Right Now, But Almost Nobody Can Actually Explain
Author(s): Divy Yadav Originally published on Towards AI. Understanding these six concepts puts you ahead of most people learning AI in 2026. Most people can use words like RAG, embeddings, and context window in a sentence. Photo from ChatGPTThe article argues that …
ROCm vs CUDA: Which One Should You Actually Use for AI?
Author(s): MayhemCode Originally published on Towards AI. ROCm vs CUDA: Which One Should You Actually Use for AI? I spent about three weeks last year trying to get a PyTorch model to train on an AMD GPU. I had the hardware, I …
Full-Stack Data Scientists for the Agentic Coding World
Author(s): Michael Shapiro MD MSc Originally published on Towards AI. The Next Evolution of Data Teams For years, building data products required a chain of specialists: data engineers, data scientists, software engineers, ML engineers, MLOps teams, and product managers. This specialization enabled …
Building Production-Grade AI Skills with Snowflake Cortex AI Function Studio
Author(s): Satish Kumar Originally published on Towards AI. Building Production-Grade AI Skills with Snowflake Cortex AI Function Studio 1. Enterprise AI Reality Check Here is the uncomfortable truth about enterprise GenAI in 2026: most implementations are unmaintainable — and most teams do …
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