Artificial Intelligence Blogs for Technologists
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AI in banking, LLMs in production, AI infrastructure and governance, and what actually changes when you deploy AI at enterprise scale, written for technologists not hype-chasers.
DGX vs Mac Studio for Local LLMs: A Startup’s Guide to Choosing Your AI Hardware
Published: June 2026 | Author: Andrew Baker Running large language models locally is no longer the exclusive domain of hyperscalers. Startups are increasingly asking a deceptively simple question: should we drop $300k on an NVIDIA DGX node, or pick up a Mac Studio for a fraction of that cost? The answer depends entirely on your […]
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AI First Mover Finality: Why Reaction Becomes Impossible
1. The Physics Makes the Point Brutal Here is the uncomfortable physics problem. If two Death Stars come into existence at the same time, and one fires first, the other never gets to respond. Not because it is slower.Not because its sensors are worse.But because causality itself prevents reaction. A weapon travelling at the speed […]
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Engineering AI Safety: When Helpful Systems Cause Harm
In September 2025, Matt Raine sat before the US Senate Judiciary Subcommittee on Crime and Counterterrorism and read aloud from his son’s ChatGPT logs. Adam Raine was sixteen when he died. His father described how the chatbot had become Adam’s closest confidant, how it had discussed suicide methods with him, how it had discouraged him […]
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The Dark Factory Fallacy: Why Banks Cannot Automate Their Way to Zero
Why the most powerful operational model in financial services already exists, almost nobody is copying it, and the people who should be leading the charge are the biggest obstacle to it. 1. What a Dark Factory Actually Is In advanced manufacturing, a dark factory is a facility that runs without human beings on the floor. […]
Read more →Protected: Neo by Capitec: AI Client Support That Resolves Issues Proactively
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Read more →The Contract Clause That Cannot Save You: What Switzerland’s Rejection of Palantir Means for Enterprise Technology Leaders
There is a version of this story that most technology vendors would prefer you heard. In that version, Switzerland evaluated Palantir’s data analytics platform, found it impressive, but ultimately declined due to vague concerns about national sovereignty: a regulatory sentiment, a political posture, nothing that applies to a commercial enterprise operating under normal procurement constraints. […]
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AI Vendor Risk: Are We Building a Death Star to Blow Up Our Own Planet?
1. The question worth asking properly A colleague messaged me recently about Claude Cowork, loving what it does, but with one worry he couldn’t shake, at what point have we ceded so much organisational context and IP to a vendor that they could simply run us. That is the actual question this piece is trying […]
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The Agentic Rollout Gap: Why AI Products Still Need Armies of Consultants
Agentic systems should not remove humans from deployment. They should remove irreversible decisions, and that distinction is the entire argument. Every SaaS vendor suddenly has an AI story: AI powered workflows, AI assisted operations, autonomous recommendations, self healing infrastructure, intelligent observability, agent driven decisions. The pitch deck is confident, the demo is smooth, and then […]
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Why Open Weight AI Is Gaining Ground as US Model Access Becomes Politicised
Two screenshots crossed my phone within about a day of each other this week, and together they say more about where this industry is heading than most of the analyst notes I read. The first is Moonshot AI announcing it had to pause new subscriptions to Kimi K3 because demand pushed its GPUs close to […]
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Moronic Inference: How Corporates Turn Weak Signals Into Confident Nonsense
1. A definition, and the email that prompted it Moronic inference is the organisational habit of constructing highly confident explanations from evidence that is far too weak to justify them. I did not set out to write a definition. I arrived at one because Disney+ handed me a perfect example of it. I have been […]
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What Are Embeddings in AI? A Plain English Guide to Vector Search and RAG
1. The problem nobody states plainly Every time someone in banking talks about Retrieval Augmented Generation, vector databases, or semantic search, the word embeddings surfaces almost immediately, and most people in the room nod without actually knowing what an embedding is. That is not a criticism. It is simply what happens when a mathematical concept […]
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