Lecture 13 starts from the failures of single-tasking and load-time relocation, uses an MMU with base/bound to create isolated virtual and physical address spaces and traps, then introduces segmentation to escape one contiguous region.
Lecture 14's official PDF is byte-identical to Lecture 13; this article records the gap and focuses on how multiple base/bound/protection entries enable growth, sharing, and compaction while retaining fixed-count, fragmentation, and rigid-layout limits.
Lecture 15 uses fixed pages to remove inter-process external fragmentation, then connects x86-64's four-level walk, sharing and aliasing, and the TLB to trade-offs among translation speed, sparse tables, context switches, and page size.
Demand paging loads pages only when needed; present bits, precise exceptions, and restartable instructions let the kernel safely fill them from executables, zero-fill, or backing store.
Lecture 17 separates demand paging into fetching and replacement: MIN cannot know the future, exact LRU is too expensive, and Clock uses reference/dirty bits to find a page old enough to evict; when active working sets exceed RAM, even a 1% fault rate can cause an approximately 1,000-fold slowdown.
A disk hides mechanical seek and rotation behind a linear block API; modern I/O then uses memory-mapped registers, DMA queues, and interrupts so the CPU mainly issues commands and receives completions.
A file system maps durable byte collections onto disk blocks; contiguous, linked, and FAT allocation trade locality, growth, random access, and metadata cost.
The 4.3BSD inode uses direct, single-indirect, and double-indirect tiers so lookup depth scales with file size; FIFO, SPTF, SCAN, and CSCAN then trade seek cost, fairness, and wait time.
Block cache retains hot indexes, bitmap slack preserves placement choices, and fragments plus delayed allocation trade later, better information for locality.
Directories map text names to file-system-local inode numbers; hard links share inode identity and reference counts, while symlinks store paths and permit cross-filesystem references with loops and dangling targets.
A single file-system operation updates several blocks, but a crash can occur between any two writes; this lecture compares how fsck, ordered writes, and write-ahead logging trade recovery time, performance, durability, and consistency.
Lecture 24 continues from the WAL entry point into transactions, idempotent replay, and checkpoints, showing why consistency is not durability and why a journal does not replace fsync or backups.
Lecture 25 separates assumption, inference, and substitution as ways to establish trust, then examines how social recommendations, generative AI, and synthetic media amplify over-trust; the response is preserved provenance, independent validation, and coordinated responsibility.
Flash programs pages but erases whole units; an FTL hides the asymmetry with out-of-place mapping, then manages amplification through garbage collection, temperature segregation, wear leveling, and TRIM.
A VM expands the process interface into a machine interface; the hypervisor directly executes ordinary instructions, traps privileged operations, and virtualizes interrupts, I/O, and two-stage address translation.
Lecture 28 reduces the semester to concurrency, memory, and storage, then uses four ideas—virtualization, atomicity, locality, and layering—to explain how operating systems manage shared resources.
Stanford has no AI degree; AI is a track inside CS. CMU launched the first U.S. B.S. in Artificial Intelligence in 2018, divided AI into four clusters, required one course from each, and made ethics a graduation requirement. At the master's level, MSAII sits not in CS but in the Language Technologies Institute; 84 of its 195 units cover an innovation process ending in a fundable capstone. Two official-page conflicts emerged during verification: whether the AI Core has two or three courses, and whether MSAII totals 192 or 195 units.
AI Engineer reached 600,000 YouTube subscribers in under three years not because it mastered video production, but because it barely needs to produce videos at all: recordings from eight conferences a year create an inexhaustible supply of YouTube material. The real constraint on content creation is structure, not skill.
CS103 is Stanford's mathematical foundations of computing course: the first half teaches proof writing through sets, logic, graphs and induction, and the second half covers finite automata, Turing machines, decidability and P vs NP. Slides, problem sets, starter files and the homegrown handouts are all public, and the autograded problems can be checked locally; solutions, practice exams and lecture recordings sit behind Stanford login.
CS107 is Stanford's computer systems course: it goes from bits, C strings and pointers to x86-64 assembly and the runtime stack, and ends with writing your own heap allocator, across seven assignments. Lecture slides, assignment specs and worked lab solutions are public; the assignment starter code lives on Stanford's AFS and is out of reach without a campus account.