What is the Wolfram Quantum Framework?

Why it's on BrighterTube

Hand-picked by a BrighterTube curator · found via round-3 back catalogue of a channel Lumen picks video by video · 82% confidence

Introduction to Wolfram Quantum Framework covering core concepts. Teaches quantum computing platform and mathematical foundations.

What you'll learn

A 56-minute video from Wolfram: “What is the Wolfram Quantum Framework?”.

Science & Math Programming & CS Lectures

Video by Wolfram, played through YouTube's embedded player.

Part of Introduction to the Wolfram Quantum Computation Framework (Study Group Sessions), Wolfram Quantum Computation

Category Theory 1.1: Motivation and Philosophy Bartosz MilewskiProgramming & CS

394K views

44:23

How Hard is too Hard? An Introduction to Complexity - Colva Roney-Dougal Gresham CollegeLectures

Intro8.82K views

Lecture 7: Introduction to Galois Fields for the AES by Christof Paar Introduction to Cryptography by Christof PaarLectures

278K views

Efficient Bayesian inference with Hamiltonian Monte Carlo -- Michael Betancourt (Part 1)MLSS Iceland 2014Lectures

Advanced47.8K views

53:02

The Universe in a Box: Simulating the Cosmos with Supercomputers Perimeter Institute for Theoretical PhysicsLectures

215K views

Siggraph2019 Geometric Algebra BivectorLectures

Advanced87.4K views

Stanford Seminar - Generalized Reversible Computing and the Unconventional Computing Landscape Stanford OnlineLectures

Advanced15.5K views

But what is a neural network? | Deep learning chapter 1 3Blue1BrownScience & Math

Intro25.1M views

Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyProgramming & CS

8.21M views

Transformers, the tech behind LLMs | Deep Learning Chapter 5 3Blue1BrownProgramming & CS

Intro11.6M views

Lec 1 | MIT 18.06 Linear Algebra, Spring 2005 MIT OpenCourseWareScience & Math

4.93M views

AT&T Archives: Similiarities of Wave Behavior (Bonus Edition)AT&T Tech ChannelEngineering

474K views

Category Theory 1.1: Motivation and Philosophy

Bartosz Milewski

394K views

The first lecture of Bartosz Milewski's Category Theory for Programmers: why abstraction and composition matter, and what category theory offers programmers.

44:23

How Hard is too Hard? An Introduction to Complexity - Colva Roney-Dougal

Gresham College

Intro8.82K views

Colva Roney-Dougal introduces computational complexity: what makes problems hard, P vs NP and why it matters.

Lecture 7: Introduction to Galois Fields for the AES by Christof Paar

Introduction to Cryptography by Christof Paar

278K views

Christof Paar introduces finite-field (Galois field) arithmetic and shows how it underlies the AES S-box.

Efficient Bayesian inference with Hamiltonian Monte Carlo -- Michael Betancourt (Part 1)

MLSS Iceland 2014

Advanced47.8K views

Michael Betancourt explains why sampling high-dimensional distributions is hard and how Hamiltonian Monte Carlo solves it.

53:02

The Universe in a Box: Simulating the Cosmos with Supercomputers

Perimeter Institute for Theoretical Physics

215K views

How cosmologists simulate the universe's evolution on supercomputers and test those simulations against observations.

Siggraph2019 Geometric Algebra

Bivector

Advanced87.4K views

The SIGGRAPH 2019 course on geometric algebra for computer graphics: multivectors, the geometric product and projective geometric algebra.

Stanford Seminar - Generalized Reversible Computing and the Unconventional Computing Landscape

Stanford Online

Advanced15.5K views

Michael Frank surveys reversible computing and other unconventional approaches as transistor scaling hits energy limits.

But what is a neural network? | Deep learning chapter 1

3Blue1Brown

Intro25.1M views

Builds up what a neural network actually is — neurons as numbers, layers, weights and biases — using handwritten-digit recognition as the running example.

Let's build GPT: from scratch, in code, spelled out.

Andrej Karpathy

8.21M views

Building a GPT-style language model from scratch in code, following 'Attention Is All You Need'.

Transformers, the tech behind LLMs | Deep Learning Chapter 5

3Blue1Brown

Intro11.6M views

How transformer models (the 'T' in GPT) turn text into vectors and predict the next token, step by step.

Lec 1 | MIT 18.06 Linear Algebra, Spring 2005

MIT OpenCourseWare

4.93M views

Gilbert Strang's first lecture of MIT 18.06: the geometry of linear equations.

AT&T Archives: Similiarities of Wave Behavior (Bonus Edition)

AT&T Tech Channel

474K views

Bell Labs' J.N. Shive uses a mechanical wave machine to show reflection, standing waves, resonance and impedance matching — the ideas behind transmission lines.