Posts

Will AI Energy Demand Taper Off?

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Anyone following the AI boom will have heard two arguments pulling in opposite directions. The first says hardware and algorithms are improving so fast — chips getting quicker per watt, models shrinking through quantisation and distillation, software stacks tightening at every layer — that energy use should eventually level off. The second says the opposite: tech giants are signing multi-gigawatt power deals, bringing retired nuclear plants back online, and forecasting demand curves that only go up. I wanted to work out which story actually holds, so I went through the industry data myself. My conclusion is that the second camp has it right. Efficiency keeps improving, but it is not enough on its own. Total demand is going to keep accelerating for the rest of the decade. Why Efficiency Doesn't Mean Less Energy The reason the efficiency argument falls short has a name: Jevons' Paradox . Back in 1865, the economist William Stanley Jevons noticed something counterintuitive ab...

The year of the Linux desktop?

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Linux is celebrating its 35th birthday , and commentators are once again asking if 2026 will finally be the "year of the Linux desktop". For the broader industry, that phrase has been a running joke for decades. But for me, the answer is much simpler: Linux has been the right environment for my work for years, and I have never really looked back. My own journey with Linux began in 1999, when I set out to build an open source development environment. That was a decision driven by my professional work. In those early days, I was focused on development tools and machine performance. I tuned kernels, adjusted desktop settings, and stripped systems down to maximise the performance of my modest hardware. I moved between RPM- and DEB-based distributions, and I even spent a rewarding period on FreeBSD. It was a good learning experience, and it was fun. That sense of fun is often overlooked, but it matters. As a developer, having access to a broad range of command-line tools and...

The Review Bottleneck

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A Reader Pushes Back Why Lean? argued that formal methods are the industry's answer to a world where testing can no longer keep up with the cost of failure. A reader, commenting on that post , pointed out something the post had left out entirely: sometimes bugs survive not because testing failed to catch them, but because nobody was ever going to fix them. That comment, and the conversation it started, turned into more than a reply. It was the second half of the argument. The Bugs We Choose Not to Fix The reader's point was blunt and specific: a company they had just left refused to fix known bugs because the market and investors wanted to see year-on-year growth, and growth comes from shipping new features, not from fixing what already exists. Bugs get "fixed" only when a client trips over one in production. In effect, the user base becomes an informal, unpaid QA layer — crowdsourced testing whether they like it or not. This is a different failure mode from ...

Why Lean?

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The Real Issue Is Trust Modern society runs on software that is increasingly essential and increasingly fragile. The problem is not simply that code has bugs. The deeper issue is that we have built a digital civilisation on systems whose correctness is assumed rather than demonstrated. The examples are familiar, and they are getting more costly. In 2025, a routine firewall upgrade caused the Optus emergency calling outage : ordinary calls were automatically rerouted to another network without incident, but Triple Zero calls were silently left undelivered for hours. The fault was narrow, yet it landed precisely on the one function that mattered most, raising serious questions about how deeply society depends on systems we assume are safe and reliable. In 2026, the Telstra outage brought widespread disruption across a continent, showing how a single infrastructure failure can cascade through communications, commerce, and daily life. In a world where a single logic error can disabl...

The Alien Intelligence of AI

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It is a comfortable belief: AI is just a mirror. Critics often dismiss large AI systems, especially large language models, as statistical parrots that reflect our words, images, and ideas without any deeper agency. They argue that such systems cannot come up with new ideas. I think that is wrong. The question is not whether AI has consciousness or human-style understanding. The question is whether it can see associations and links that humans often miss. Human civilisation also advances through copying and recombination. We build on what came before. AI does something related, though in a different manner. It notices connections across vast bodies of data and turns those relationships into outputs that can feel surprising to us. In this essay I will look at several examples — a Go match, a mathematical proof, a rocket engine, a strange portrait, and a drug candidate — where I think AI has done something novel and interesting. Move 37: A Strategy That Broke Human Intuition In Mar...

Information Theory as the Fundamental Architecture of Reality

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Introduction: The Informational Universe We typically perceive our world through the lens of tangible matter and flowing energy. We see a landscape of atoms, forces, and heat. However, modern science is beginning to realise that these physical properties might merely be the surface of a deeper architecture. At its most fundamental level, the universe appears to be composed of “bits” of information. Consider the extraordinary feat of a single microscopic cell: how does it “know” how to construct a complex human being? The answer lies not just in chemistry but in the sophisticated processing of data. By shifting our perspective to information theory, we can begin to decode the underlying software of existence and see ourselves as nodes within a vast, self-optimising system. This article follows that idea from first principles to wider systems. It moves from Shannon’s formal definition of information, through biology and thermodynamics, then into active theoretical debates in physics...

Is Gravity Just Spacetime's Temperature?

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Why This Debate Matters Contemporary physics faces a quiet but profound crisis. Our picture of the universe rests on two extraordinary frameworks that do not fit neatly together: General Relativity (GR), which describes spacetime as a smooth continuum curved by mass, and Quantum Mechanics (QM), which describes reality as discrete particles governed by chance. That tension sits alongside another stubborn cosmic puzzle: if the second law of thermodynamics dictates that the universe must become increasingly disordered over time, how can an expanding cosmos give rise to complex, ordered structures like galaxies, stars, planets, and life? Standard cosmology often attributes cosmic acceleration to a static cosmological constant or an undetected form of dynamical dark energy. Gravity from Entropy (GfE), developed by mathematician Ginestra Bianconi , offers a fresh perspective. Rather than adding missing particles or modifying GR arbitrarily, GfE treats gravity as an emergent, thermo...