When AI Leaves the Data Centre: Robots, Power Grids & the New Attack Surface 🤖⚡

AI is moving rapidly beyond chat windows and into the physical world — powering robots, vehicles, industrial systems, edge devices and critical infrastructure.

In this episode of Cloud Dialogues, Georgia and Matt are joined by Alex Turner, founder of Admiral, to explore what happens when increasingly capable AI systems meet the messy reality of hardware, legacy networks and infrastructure that cannot simply be rebooted.

They discuss:

* 🧠 Why frontier AI labs are talking about slowing development — and whether there are commercial incentives behind the message * 💣 The possibility of deploying “time bombs” into code that may be readable, but unnoticed * 👀 Why telling an AI system what not to do is not the same as building a real guardrail * ⚡ How AI could lower the expertise required to attack power grids and critical infrastructure * 🏭 Why legacy industrial systems and SCADA networks may be particularly exposed * 📡 How cheaper, more powerful edge hardware is bringing real-time AI into the physical world * 🚛 What happens when a software update bricks an entire fleet of devices * 🔥 Why autonomous devices need observability, controlled rollouts and a genuine kill switch * 🤖 The future of robots, automated restaurants and AI-powered machines operating around us * ⚙️ Whether smaller, type-safe decision models like JEV could become more useful than giant language models for certain operational tasks

The future of AI may not look like a chatbot.

It may look like a robot, a delivery vehicle, a power-grid controller or a machine quietly making decisions at the edge — often on someone else’s network.

And the uncomfortable question is: who is watching what happens when those systems go wrong?

You can find Alex on LinkedIn: https://www.linkedin.com/in/alexanderpaulturner and Admiral at https://admrl.co

What happens to software engineering when developers stop writing code and start directing, evaluating and correcting AI?

In this episode, Georgia and Matt are joined by Annie Vella, former Distinguished Engineer at Westpac New Zealand, to explore how AI coding tools are reshaping software engineering.

Drawing on her research into AI-assisted development, Annie introduces the idea of “supervisory engineering”: the growing work of directing AI, evaluating its output, correcting mistakes and integrating generated code into complex systems.

They explore:

• The hidden cognitive load behind AI-generated code • Why code review is becoming a major bottleneck • What accountability means when engineers approve code they didn’t write • Whether we’re automating the craft and enjoyment out of software development • Why foundational engineering skills matter more than ever • What the next generation of developers should be learning • How small teams can capitalize on AI without losing essential human capabilities

It’s a conversation about the future of software development, but also about something much bigger: what happens to human judgment, learning and pride when more of our thinking is delegated to machines?

In Episode 42 of Cloud Dialogues, Georgia and Matt are joined by AI ethicist and The Mathpath founder Aubrey Blanche for a candid, provocative and surprisingly funny conversation about responsible AI in the real world.

We explore:

🔐 AI security and sovereignty Frontier-model hype, open-weight models, enterprise security, data residency and why Microsoft doesn’t necessarily need the “best” product to win.

🧠 “More capable,” not “smarter” Why anthropomorphising AI distorts how we understand - and interact with - the technology.

⚖️ What algorithmic discrimination actually looks like Why “the evil computer did it” is rarely an accurate or useful diagnosis - and why understanding the mechanism matters if we genuinely want to fix it.

📈 The problem with productivity as the goal Making broken processes faster may simply produce more garbage, more efficiently.

🎯 Incentives drive behaviour Including the inevitable consequences of token-maxing dashboards, performance targets based on AI usage and telling employees they must use six tools whether they need them or not.

👩‍💻 Why eliminating junior roles is spectacularly shortsighted Tokens may now be more expensive than interns - and without junior employees today, organisations won’t have senior experts tomorrow.

👥 Pair prompting and human expertise How teams can use AI to accelerate delivery while preserving reasoning, shared knowledge, mentorship and technical skills.

💸 The economics behind the AI narrative Why frontier-model companies need an enormous addressable market to justify their valuations - and why that makes “AI will replace all human labour” an extremely convenient story.

🌍 Who gets to shape AI? Who decides what should be automated? Whose problems receive investment? Who benefits from the dominant narrative - and what possible futures disappear when we accept it without question?

A practical discussion about adopting AI intentionally, creating genuine business value and building systems that work without forgetting the humans inside them.

Also featuring:

✨ 100 beautiful AI-generated slides that may or may not be useful 🔥 The consultant you hire when you want the truth 🪙 Tokens being set on fire for the performance dashboard 🚗 AI’s ongoing refusal to wash Aubrey’s car