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Lore watches your screen, listens, and points at what matters. Every answer stays on your machine.
macOS 15.0+ · Private beta
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Every answer, clip, and conversation becomes a note on your Mac. The more you ask, the more Lore knows you — and the easier it gets to find what you already learned.
Lore
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Linear algebra.md
Photosynthesis.md
Sourdough notes.md
Kyoto trip.md
Clips
Practical typography.md
Attention is all you need.md
Conversations
What are eigenvalues.md
Setting up a vegetable garden.md
How to read a research paper.md
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Agent — Calendar
Calendar — May 2026
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Lunch with AnyaBooked just now
Wed May 15 · 12:30pm · Tartine Bakery
Agent · running
→ open_app("Calendar")→ snapshot_desktop()→ click_ref(@e14, "Wed 15")→ type_into_ref(@e22, "Lunch with…")✓ done — 12:30pm slot booked
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Companion — Linear Algebra
You’re watching · Linear Algebra Lecture 4
A v⃗ = λ v⃗
Listening · adding to wiki/eigenvalues.md
Companion · ambient
“That's the eigenvalue equation — A scales v by λ without rotating it.”
A place where everything you learn lives.
Every conversation, clip, and answer is a markdown file in your vault — yours, on disk, in plain text. The Workspace is the window into that vault; clipping is one of the simplest ways to feed it.
Workspace
A real workspace for everything you've learned.
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eigenvalues.md
clips/cursor-ai-blog.md
research/Linear Algebra
Eigenvaluesresearch/eigenvalues.md
7 propertiesSOURCEMIT 18.06URLocw.mit.eduCAPTURED2d agoTAGmathTAGlinear-algebraREAD6 min
Eigenvalues
An eigenvector v of a square matrix A satisfies Av = λv, where λ is the corresponding eigenvalue1.
Geometrically, applying A to v stretches it along its own axis without rotating it2. The scale factor is λ.
See also [[singular-value-decomposition]] and [[principal-component-analysis]]. The connection to PCA falls out of the spectral theorem3.
Why it matters
Eigendecomposition is the engine behind PageRank, principal component analysis, quantum mechanics, and almost every method in linear algebra that “diagonalizes” a transformation.
What are eigenvalues, intuitively?
What are eigenvalues, intuitively? Trying to understand the MIT 18.06 lecture I just clipped.
retrieve · k=8
An eigenvalue is the scale factor that survives a linear transformation1. If you apply a matrix A to a vector v, most of the time v tilts in some new direction. But certain special vectors — the eigenvectors — point in a direction that doesn’t move; the matrix only stretches them.
The amount of that stretch is the eigenvalue2. Negative eigenvalues flip the vector; zero eigenvalues collapse it3. The set of eigenvalues describes the “shape” of the transformation — what it stretches, what it leaves alone.
Continue this thread…
Sonnet
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What are eigenvalues, intuitively?
What are eigenvalues, intuitively? Trying to understand the MIT 18.06 lecture I just clipped.
retrieve · k=8
An eigenvalue is the scale factor that survives a linear transformation1. If you apply a matrix A to a vector v, most of the time v tilts in some new direction. But certain special vectors — the eigenvectors — point in a direction that doesn’t move; the matrix only stretches them.
The amount of that stretch is the eigenvalue2. Negative eigenvalues flip the vector; zero eigenvalues collapse it3. The set of eigenvalues describes the “shape” of the transformation — what it stretches, what it leaves alone.
Continue this thread…
Sonnet
Clipping
Save anything. Find it later.
Drag a URL onto Lore, or type /clip in Quick Chat. Lore fetches the page, summarizes it, tags it, and drops a markdown clip into your vault — automatically backlinked to whatever you were working on.
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- Citation-readyClips become first-class sources — they show up as numbered citations in chat answers and as nodes in the vault graph. Your reading turns into a research library.
Quick Chat — /clip
You’re reading
Why typography matters
practical-typography.com
/clip practical-typography.com↵
PT
Why typography mattersSaved
A practical guide on why fonts and spacing make professional documents read as legitimate — by the author of Practical Typography.
#typography#design#readability
Coming soon
Continue the conversation.
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