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From the Algorithmic Toolbox to LP, Coding, and ML | Stanford CS161 Lecture 18

The finale recaps the CS161 toolbox and points toward LP duality, Reed–Solomon coding, and ML-assisted algorithms. Officially, this lecture has slides but no notes.

In the AI Era, Taste Is an Amplifier

AI pushes execution cost toward zero. People with good taste create more value; people with poor taste create more garbage. The difference is not whether you can use AI, but whether your mind contains something worth amplifying before you use it. This series documents my attempt to sharpen judgment systematically.

What Paper Still Earns in a Digital-First Study Stack: Three Places It Works, and One It Doesn't

Once studying went fully digital, paper still holds three places with real evidence: reading (paper over screens at g ≈ −0.21 across 171,055 participants, widening to 0.35–0.48 when scrolling is required), writing while you answer (on screen, harder questions draw less scratch work, not more), and drawing (45% recall against 20% for writing). The one claim most people lean on, that handwritten notes stick better, spans −0.008 to +0.248 across four meta-analyses with no consensus.

AI Makes Things Smooth Exactly Where They Should Be Hard: What Generative AI Does to Learning

The single most-cited meta-analysis on ChatGPT in education (g = 0.867, ~500k views) was retracted by Nature in April 2026. But the positive finding was not overturned — the issue is that it measures performance while the AI is available. Bastani's PNAS RCT measured something else: +48% accuracy during practice with GPT-4, then 17% below never-users once access was removed.

Learning How to Learn: Auditing the Course 4.17 Million People Took — What Holds Up, What's Just a Metaphor

Dunlosky's 2013 review rated 10 study techniques; only self-testing and distributed practice earned 'high utility'. But a 2026 systematic review puts the effect at 0.22–0.46, and Pan & Rickard's transfer meta-analysis finds 'no positive transfer' once publication bias is corrected — making the premise in the framework's own name the piece that tests worst.

learningdeep-dive

Evergreen Books Still Trending in 2026: A Reading List Built from Threads, Dcard, and Vocus Signals

24 evergreen books across productivity, life design, brain science, psychology, and money — selected using actual discussion evidence from Threads, Dcard, PTT, and Vocus between late 2025 and mid-2026. Strongest signal: Rewire by Nicole Vignola hit top 3 on both Eslite and Books.com.tw H1 2026 bestseller charts.