<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>The AI Engineer&apos;s Grimoire — recent revisions</title><description>A field reference for how these systems actually work: attention, training dynamics that fail quietly, inference kernels, the interpretability toolkit, and the attack surface that follows.</description><link>https://aiwiki.thehackersbrain.dev/</link><language>en</language><atom:link href="https://aiwiki.thehackersbrain.dev/rss.xml" rel="self" type="application/rss+xml"/><item><title>Multi-Head Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/multi-head-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/multi-head-attention/</guid><description>h attention operations in d/h-dimensional subspaces, summed back into the residual stream.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>transformer</category><category>core</category></item><item><title>Building the attention weights</title><link>https://aiwiki.thehackersbrain.dev/notes/building-the-attention-weights/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/notes/building-the-attention-weights/</guid><description>From &quot;which positions matter&quot; to softmax over scaled dot products, by elimination.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate><category>Notes</category><category>attention</category><category>foundations</category><category>maths</category></item><item><title>The quadratic problem</title><link>https://aiwiki.thehackersbrain.dev/notes/the-quadratic-problem/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/notes/the-quadratic-problem/</guid><description>Where the n² really comes from, and why the escape routes divide into exactly three kinds.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate><category>Notes</category><category>attention</category><category>efficiency</category><category>foundations</category></item><item><title>Why attention exists</title><link>https://aiwiki.thehackersbrain.dev/notes/why-attention-exists/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/notes/why-attention-exists/</guid><description>The fixed-size bottleneck that broke sequence-to-sequence models, and the obvious fix nobody could take.</description><pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate><category>Notes</category><category>attention</category><category>history</category><category>foundations</category></item><item><title>Attention Sinks</title><link>https://aiwiki.thehackersbrain.dev/entries/attention-sinks/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/attention-sinks/</guid><description>Softmax must sum to one, so heads need somewhere to dump mass; evict it and generation collapses.</description><pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>inference</category><category>long-context</category></item><item><title>Reading an attention matrix</title><link>https://aiwiki.thehackersbrain.dev/notes/reading-an-attention-matrix/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/notes/reading-an-attention-matrix/</guid><description>What the n×n matrix contains, what the pretty heatmaps show, and how much of it is an artefact.</description><pubDate>Mon, 31 Aug 2026 00:00:00 GMT</pubDate><category>Notes</category><category>attention</category><category>interpretability</category><category>foundations</category></item><item><title>Additive Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/additive-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/additive-attention/</guid><description>The original mechanism: a learned MLP scores each query–key pair.</description><pubDate>Sun, 30 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>history</category><category>foundations</category></item><item><title>LLM-as-Judge</title><link>https://aiwiki.thehackersbrain.dev/entries/llm-as-judge/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/llm-as-judge/</guid><description>Using a model to score model outputs, and the biases that come with it.</description><pubDate>Sun, 30 Aug 2026 00:00:00 GMT</pubDate><category>Evaluation</category><category>metric</category><category>preference</category></item><item><title>Linear Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/linear-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/linear-attention/</guid><description>Drop the softmax, reassociate the matmuls, and decode in constant memory.</description><pubDate>Sat, 29 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>efficiency</category><category>recurrence</category></item><item><title>Chinchilla Scaling Laws</title><link>https://aiwiki.thehackersbrain.dev/entries/chinchilla-scaling-laws/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/chinchilla-scaling-laws/</guid><description>Compute-optimal allocation between parameters and training tokens.</description><pubDate>Fri, 28 Aug 2026 00:00:00 GMT</pubDate><category>Training</category><category>scaling</category><category>training</category></item><item><title>Scaled Dot-Product Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/scaled-dot-product-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/scaled-dot-product-attention/</guid><description>Content-based retrieval over key–value pairs with 1/√d_k logit scaling.</description><pubDate>Fri, 28 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>transformer</category><category>core</category></item><item><title>Sparse Autoencoders</title><link>https://aiwiki.thehackersbrain.dev/entries/sparse-autoencoders/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/sparse-autoencoders/</guid><description>Overcomplete dictionary learning on activations for monosemantic features.</description><pubDate>Fri, 28 Aug 2026 00:00:00 GMT</pubDate><category>Interpretability</category><category>sparse</category><category>features</category></item><item><title>Multi-Head Latent Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/multi-head-latent-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/multi-head-latent-attention/</guid><description>Cache a shared low-rank latent instead of per-head keys and values.</description><pubDate>Thu, 27 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>kv-cache</category><category>inference</category></item><item><title>FlashAttention</title><link>https://aiwiki.thehackersbrain.dev/entries/flash-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/flash-attention/</guid><description>Tiled, IO-aware attention kernel; recomputes softmax statistics online.</description><pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate><category>Inference</category><category>attention</category><category>kernels</category><category>memory</category></item><item><title>Grouped-Query Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/grouped-query-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/grouped-query-attention/</guid><description>g key–value heads shared across h query heads; the dial between MHA and MQA.</description><pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>kv-cache</category><category>inference</category></item><item><title>Speculative Decoding</title><link>https://aiwiki.thehackersbrain.dev/entries/speculative-decoding/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/speculative-decoding/</guid><description>Draft model proposes tokens; target model verifies in one pass.</description><pubDate>Wed, 26 Aug 2026 00:00:00 GMT</pubDate><category>Inference</category><category>decoding</category><category>latency</category></item><item><title>Block-Sparse Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/block-sparse-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/block-sparse-attention/</guid><description>Local windows plus a few global tokens, chosen before the scores are computed.</description><pubDate>Tue, 25 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>sparse</category><category>long-context</category></item><item><title>Direct Preference Optimisation</title><link>https://aiwiki.thehackersbrain.dev/entries/direct-preference-optimisation/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/direct-preference-optimisation/</guid><description>Closed-form preference objective that removes the reward model.</description><pubDate>Tue, 25 Aug 2026 00:00:00 GMT</pubDate><category>Training</category><category>RL</category><category>alignment</category></item><item><title>GRPO</title><link>https://aiwiki.thehackersbrain.dev/entries/grpo/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/grpo/</guid><description>Group-relative advantages from sampled completions; no value network.</description><pubDate>Tue, 25 Aug 2026 00:00:00 GMT</pubDate><category>Training</category><category>RL</category><category>alignment</category></item><item><title>LoRA</title><link>https://aiwiki.thehackersbrain.dev/entries/lora/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/lora/</guid><description>Low-rank additive update to frozen weight matrices during adaptation.</description><pubDate>Tue, 25 Aug 2026 00:00:00 GMT</pubDate><category>Fine-tuning</category><category>fine-tuning</category><category>peft</category></item><item><title>Causal Masking</title><link>https://aiwiki.thehackersbrain.dev/entries/causal-masking/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/causal-masking/</guid><description>The triangular mask that turns one forward pass into n training examples.</description><pubDate>Mon, 24 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>training</category><category>core</category></item><item><title>Induction Heads</title><link>https://aiwiki.thehackersbrain.dev/entries/induction-heads/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/induction-heads/</guid><description>A two-head circuit that completes [A][B]…[A] with [B]; the substrate of in-context learning.</description><pubDate>Sun, 23 Aug 2026 00:00:00 GMT</pubDate><category>Interpretability</category><category>circuits</category><category>causal</category></item><item><title>SwiGLU</title><link>https://aiwiki.thehackersbrain.dev/entries/swiglu/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/swiglu/</guid><description>Gated feed-forward block; a Swish gate multiplied into a linear branch.</description><pubDate>Fri, 21 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>ffn</category><category>core</category></item><item><title>Cross-Attention</title><link>https://aiwiki.thehackersbrain.dev/entries/cross-attention/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/cross-attention/</guid><description>Queries from one sequence, keys and values from another.</description><pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>attention</category><category>conditioning</category><category>multimodal</category></item><item><title>Selective State Space Models</title><link>https://aiwiki.thehackersbrain.dev/entries/state-space-models/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/state-space-models/</guid><description>Linear recurrence with input-dependent dynamics; Mamba and the S4 line.</description><pubDate>Wed, 19 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>sequence</category><category>recurrence</category><category>sparse</category></item><item><title>Activation Patching</title><link>https://aiwiki.thehackersbrain.dev/entries/activation-patching/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/activation-patching/</guid><description>Causal intervention swapping activations between clean and corrupt runs.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate><category>Interpretability</category><category>causal</category><category>circuits</category></item><item><title>Proximal Policy Optimisation</title><link>https://aiwiki.thehackersbrain.dev/entries/proximal-policy-optimisation/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/proximal-policy-optimisation/</guid><description>Clipped surrogate advantage objective with KL control to a reference.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate><category>Training</category><category>RL</category><category>alignment</category></item><item><title>QLoRA</title><link>https://aiwiki.thehackersbrain.dev/entries/qlora/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/qlora/</guid><description>4-bit NF4 base weights with paged optimiser state and LoRA adapters.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate><category>Fine-tuning</category><category>fine-tuning</category><category>quantisation</category></item><item><title>Rotary Position Embedding</title><link>https://aiwiki.thehackersbrain.dev/entries/rotary-position-embedding/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/rotary-position-embedding/</guid><description>Relative position injected as a per-pair rotation in complex subspaces.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate><category>Architectures</category><category>position</category><category>attention</category></item><item><title>Statistical Power for Evals</title><link>https://aiwiki.thehackersbrain.dev/entries/statistical-power/</link><guid isPermaLink="true">https://aiwiki.thehackersbrain.dev/entries/statistical-power/</guid><description>Error bars, paired tests and how many items an eval actually needs.</description><pubDate>Tue, 18 Aug 2026 00:00:00 GMT</pubDate><category>Evaluation</category><category>metric</category><category>data</category></item></channel></rss>