Series
Under the Hood
How the technology actually works — deep dives into the systems we use every day.
Under the Hood · The AI Field Guide
How LLMs Actually Work
Tokens, transformers, attention, and the training pipeline: what large language models actually do when they 'predict the next token', why they hallucinate, and why they're so good at code.
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Under the Hood · The AI Field Guide
To LLMs... and Beyond!
LLMs are one corner of a much larger field. Diffusion models, reasoning models, multimodal systems, open-weight vs closed -- what they are, how they differ, and how to choose.
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Under the Hood · Time
What Time Is It?
The hour on your phone is a fragile compromise between the sun and politics. Sundials, shipwrecks, railway time, DST, and the volunteer-maintained database that keeps the world's clocks roughly honest.
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Under the Hood · Time
What Day Is It?
The date next to the time on your phone is its own kind of fragile. Calendars argue with the moon, the sun, and each other; whole days have been deleted by decree; and the year number on your screen depends on which monk's arithmetic your ancestors trusted.
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Under the Hood · Time
Ticks or Tocks?
A second used to be a fraction of the day. Now it's defined by the vibrations of a caesium atom, and even that might not be precise enough. From quartz watches to optical lattice clocks, the story of how we learned to count time.
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Under the Hood · The AI Field Guide
The Other Transformers
BERT and T5 are transformers too, but they aren't trying to be ChatGPT. They're trying to be the boring layer underneath, classifiers, embeddings, structured transformations, and they're often a better answer than an LLM.
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Under the Hood · Time
Time Is Weirder Than You Think
Time doesn't flow at the same rate everywhere. It slows near massive objects, dilates at high speeds, and might not 'flow' at all. From GPS corrections to black holes, the physics that makes time strange.
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Under the Hood · The AI Field Guide
The Reranker You Didn't Know You Needed
RAG explanations stop at 'embed the query, look up the nearest documents, hand them to the LLM.' That's the demo. In production, there's a second pass between the lookup and the LLM, and it's the one that actually makes retrieval work.
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Under the Hood · Time
Does Time Even Exist?
The arrow of time isn't in the equations. "Now" isn't a location. The most fundamental theories of physics may contain no time variable at all. A tour of the foundations, from the block universe to the holographic principle.
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Under the Hood · The AI Field Guide
After the Transformer
Transformers have ruled language modelling for nearly a decade. They have a known weakness, and several research lines are trying to replace them. Mamba, RWKV, RetNet, Hyena, diffusion-for-text, what they are, what they fix, and which ones are likely to matter.
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Under the Hood · Time
Can You Turn Back Time?
General relativity permits time loops. Quantum mechanics hints that the future can influence the past. Hawking threw a party for time travellers and nobody came. The physics of time travel is stranger, and more serious, than science fiction suggests.
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Under the Hood · The AI Field Guide
Before the Transformer
n-grams. HMMs. CRFs. The language models and sequence taggers that ran the internet before deep learning, and that quietly still do, in autocomplete, spam filters, biomedical NER, speech recognition. What they are, why they still ship, and when they're the correct answer.
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Under the Hood · Time
The Clock Inside You
Your body has its own clock, and it doesn't care about UTC. It runs on light, adenosine, and a cluster of 20,000 neurons behind your eyes. Jet lag, shift work, larks and owls, the biology of time is a different machine from the physics, and it keeps its own hours.
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Under the Hood
A Gentle Guide to Typography: From Chisels to Character Sets
A warm, thorough walk through the world of typography, from hand-carved letters and Gutenberg's press to fonts, glyphs, kerning, serifs, and Unicode. Everything you wanted to know about how written language gets its shape.
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Under the Hood · The AI Field Guide
The Boring Baseline That Wins
TF-IDF, logistic regression, naive Bayes, k-means, LDA. The fifty lines of scikit-learn that beat your fancy model on the small problem you actually have. Why these baselines still win, and why the correct starting point in 2026 is often the same as it was in 2006.
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Under the Hood · Time
Why Does Thursday Last Forever?
A watched pot never boils. Holidays vanish. Childhood lasted decades and your thirties were a weekend. The clock doesn't care, so why does your brain?
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Under the Hood · The AI Field Guide
Rules, Grammars, and Regex
Sometimes the correct answer to 'what model should I use?' is no model at all. Hand-written rules, regular expressions, finite-state transducers. They're deterministic, auditable, free at inference, and frequently the correct tool for the job.
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Under the Hood · Time
Time Is Wrong Everywhere All at Once
Your laptop's clock is wrong. So is the server's. So is every other computer on the network. The question isn't how to make them agree, it's what to do when they can't. From Lamport clocks to Google Spanner, the story of time in distributed systems.
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Under the Hood · The AI Field Guide
Search and Planning
Most of what people called 'AI' before deep learning was search. A* finding the route, alpha-beta playing the chess move, STRIPS sequencing the plan. The algorithms that run your map app, your build system, your warehouse robot, and your game opponent.
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Under the Hood · The AI Field Guide
Knowledge, Logic, and Constraints
Reasoning from facts and rules, the way the AI textbooks of the 1980s thought we'd build minds. Propositional and first-order logic. Knowledge bases. Datalog. Modern descendants. SAT solvers, SMT solvers, and the production rule engines running insurance and banking. When if-this-then-that wins.
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Under the Hood
How Estimation Works (And Why It Doesn't)
The cone of uncertainty, the planning fallacy, story points, throughput-based forecasting, and Monte Carlo simulation, why software estimation is so hard, and what actually works.
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Under the Hood · The AI Field Guide
Bayesian Reasoning
Probability is the third leg of classical AI. Bayesian networks, Kalman filters, particle filters, multi-armed bandits. The mathematics that fuses sensor noise into a position estimate, that decides whether to show a user this ad or that one, that diagnoses faults from intermittent symptoms.
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