Mastodawn

Alright, future engineers!
**Dot Product (Scalar Product):** Multiplies two vectors to give a *scalar* measuring their directional alignment.
Ex: `[1,2] . [3,4] = 1*3 + 2*4 = 11`.
Pro-Tip: If `a . b = 0`, the vectors are perfectly orthogonal (perpendicular)! This is KEY for geometry & projections.
#LinearAlgebra #VectorMath #STEM #StudyNotes

kipriyanovich Jun 16

Alright, future engineers!
**Dot Product:** Measures how much two vectors align, producing a scalar.
Ex: `[1,2] · [3,4] = (1*3)+(2*4) = 11`.
Pro-Tip: If it's zero, vectors are orthogonal! Essential for projections & angles.
#VectorMath #LinearAlgebra #STEM #StudyNotes

kipriyanovich Jun 12

Alright, future engineers!
**Dot Product:** Measures how much two vectors align; it's a scalar value.
Ex: For `A=[1,2]`, `B=[3,4]`, `A.B = (1*3) + (2*4) = 11`.
Pro-Tip: If A.B = 0, vectors are orthogonal (perpendicular)!
#LinearAlgebra #VectorMath #STEM #StudyNotes

kipriyanovich Jun 7

Alright, future engineers!
**Dot Product (v⋅w):** A scalar measuring how much two vectors point in the same direction.
Ex: For `v=[1,0], w=[0,1]`, `v⋅w = 1*0 + 0*1 = 0`.
Pro-Tip: If `v⋅w = 0` (and `v,w` non-zero), they're ORTHOGONAL! Key for projections & geometry.
#VectorMath #LinearAlgebra #STEM #StudyNotes

Hublai (charismatic megafauna)Jun 3

www.electronicdesign.com/technologies... #SiFive #P570 adds #INT8dotproduct extensions - among others - to #RVA23. While #ternarymatrix operations seem to be far more useful in #LLM deployment, there's room to assess every kind of #RISC-V extension especially for #vectormath & #tensortransfer.

RISC-V Core Exceeds RVA23 Requ...

RISC-V Core Exceeds RVA23 Requirements

SiFive’s P570 extends the RVA23 specification with security and vector enhancements.

Electronic Design

kipriyanovich May 31

Alright, future engineers!
**Dot Product:** A scalar value from two vectors, representing their similarity or alignment.
Ex: For `v=<a,b>`, `w=<c,d>`, `v.w = ac + bd`.
Pro-Tip: If `v.w = 0`, the vectors are orthogonal (perpendicular)!
#LinearAlgebra #VectorMath #STEM #StudyNotes

kipriyanovich Apr 15

Alright, future engineers!
The **Norm** (`||v||`) is the length or magnitude of a vector. Ex: For `v=[3,4]`, `||v|| = sqrt(3^2 + 4^2) = 5`. Pro-Tip: Essential for calculating distances & normalizing vectors to unit length!
#LinearAlgebra #VectorMath #STEM #StudyNotes

kipriyanovich Apr 8

Alright, future engineers!

A **Linear Combination** is a new vector made by scaling existing vectors & adding them. Ex: `2*[1,0] + 3*[0,1] = [2,3]`. Pro-Tip: It's the fundamental way to build new vectors within a given space!

#LinearAlgebra #VectorMath #STEM #StudyNotes

kipriyanovich Mar 29

Alright, let's nail this Linear Algebra concept!

Dot product measures how much two vectors 'agree' on direction. Ex: For v=[v1,v2], w=[w1,w2], v.w = v1w1 + v2w2. Pro-Tip: If v.w = 0, they're orthogonal! Crucial for projections & bases.

#LinearAlgebra #VectorMath #STEM #StudyNotes

Dyalog Feb 2

#APLQuest 2014-08: Write a function that returns the distance between two points in a space of any number of dimensions (see https://apl.quest/2014/8/ to test your solution and view ours).

#APL #EuclideanDistance #VectorMath

APL Quest 2014-8: Go The Distance

Write a function that returns the distance between two points in a space of any number of dimensions.