Engineering knowledge, taught with the help of AI.

Kadosh Engineering Limited builds technical courses and the computing behind them: video lessons, automatic transcripts and questions that check understanding. Knowledge flows like water, and we build the channel.

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How a lecture becomes an interactive course

  1. 1. Lecture video

    Recorded once and hosted on our own media domain.

  2. 2. Transcript

    Speech recognition adds timed subtitles.

  3. 3. Questions

    Drafted with AI, reviewed by a teacher, placed at the right second.

  4. 4. Course

    Published as an interactive lesson on Moodle.

Ripples, beams and lattices

The same ideas return from rivers to spacetime: waves that travel, energy that converges, order that comes from a lattice.

Illustration of two black holes merging, with ripples spreading through a grid of spacetime

Gravitational waves

Ripples in spacetime produced by two merging black holes.

Illustration of many laser beams converging on a small fuel capsule inside a fusion chamber

Inertial-confinement fusion

Laser beams converge on a tiny fuel capsule.

Illustration of a quantum processor chip with a square lattice of qubits and a few highlighted errors

Quantum error correction

A lattice of qubits that detects and fixes errors.

Knowledge moves like water

Rivers and the water cycle are engineering classics. They are also a good model for learning: knowledge flows, speeds up through narrow points, then returns to feed what comes next.

The water cycle

Water never leaves the system: it evaporates, condenses, falls as rain and gathers again in rivers and seas.

How a river flows

Q = A · v

The flow rate Q stays the same along the river. Where the channel narrows, the area A is smaller, so the speed v rises.

From a brain cell to an artificial neuron

Neural networks are loosely inspired by how brain cells pass signals. Each artificial neuron adds up its weighted inputs and decides what to send on. This is what lets a model turn speech into text.

A brain cell

Dendrites receive signals, the cell body combines them, and the axon sends the result to the next cell through a synapse.

An artificial neuron

Inputs are multiplied by weights, summed with a bias, and passed through an activation function.

y = f(w₁x₁ + w₂x₂ + w₃x₃ + b)

Training adjusts the weights w and the bias b.

What we do

Three fields, one working method.

Engineering

Physics, chemistry, hydraulics and applied engineering, explained step by step with worked examples.

AI computing

Speech recognition turns lecture videos into transcripts and AI drafts the questions. A person reviews everything before students see it.

Education

Interactive videos, quizzes and clear learning goals, delivered on a Moodle platform.

Get in touch

Questions about a course or a project? Write to us.

contact@kadoshengineering.com

Kadosh Engineering Limited