Hacker News · Feb 16, 2026 · Collected from RSS
Hey HN, I don’t know who else has the same issue, but: Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI. Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts. In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing. This is an open & unconventional textbook covering maths, computing, and artificial intelligence from the ground up. For curious practitioners seeking deeper understanding, not just survive an exam/interview. To ambitious students, an early careers or experts in adjacent fields looking to become cracked AI research engineers or progress to PhD, dig in and let me know your thoughts. Comments URL: https://news.ycombinator.com/item?id=47036063 Points: 7 # Comments: 0
01 Vectors Spaces, magnitude, direction, norms, metrics, dot/cross/outer products, basis, duality Available 02 Matrices Properties, special types, operations, linear transformations, decompositions (LU, QR, SVD) Available 03 Calculus Derivatives, integrals, multivariate calculus, Taylor approximation, optimisation and gradient descent Available 04 Statistics Descriptive measures, sampling, central limit theorem, hypothesis testing, confidence intervals Available 05 Probability Counting, conditional probability, distributions, Bayesian methods, information theory Available 06 Machine Learning Classical ML, gradient methods, deep learning, reinforcement learning, distributed training Available 07 Computational Linguistics syntax, semantics, pragmatics, NLP, language models, RNNs, CNNs, attention, transformers, text diffusion, text OCR, MoE Coming 08 Computer Vision image processing, object detection, segmentation, video processing, SLAM, CNNs, vision transformers, diffusion, flow matching, VR/AR Coming 09 Audio & Speech DSP, ASR, TTS, voice & acoustic activity detection, diarization, source separation, active noise cancelation, wavenet, conformer Coming 10 Multimodal Learning fusion strategies, contrastive learning, VLMs, image tokenizer, video audio co-generation Coming 11 Autonomous Systems perception, robot learning, VLAs, self-driving cars, space robots Coming 12 Computing & OS discreet maths, computer architecture, operating systems, RAM, concurrency, parallelism, programming languages Coming 13 Data Structures & Algorithms arrays, trees, graph, search, sorting, hashmaps Coming 14 SIMD & GPU Programming ARM & NEON, X86 chips, RISC ships, GPUs, TPUs, triton, CUDA, Vulkan Coming 15 Inference quantisation, streamingLLMs, continuous batching, edge inference, Coming 16 Intersecting Fields quantum ML, neuromorphic ML, AI for finace, AI for bio Coming 17 Henry's Research Findings I run many hyperfocused experiemts and will share findings Coming