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Aether Lang · part of Seal's Topology Land

A runtime whose loops stop when their shape does.

A small language where 🦭 until ends a loop on a condition, persistent homology is a built-in call, and every capability on this site is either tested or labelled roadmap.

Get started Language Topology Status matrix GitHub

let count = 0~

🦭 until count >= 10 {
    count = count + 1~
}

What it is

Bounded contracts: the runtime keeps structure, so a cheap invariant can drive the decision. Theory →

flowchart LR
  A["Source, signal, tensor, binary, or system state"] --> B["Typed runtime object"]
  B --> C["Embedding, block, graph, or state vector"]
  C --> D["Topology, bound, drift, or threshold"]
  D --> E["Execution, convergence, pruning, or rejection decision"]

What Is Active Today

  • Lexer, parser, AST, interpreter, and Titan VM scaffolding in aether-lang.
  • CLI commands: aether repl, aether run, and aether check.
  • Variables, assignments, arithmetic, comparison, logical operators, lists, functions, if, while, for, and seal until.
  • Manifold embedding from numeric lists through a fixed 3D time-delay workspace.
  • Block extraction and geometric block metadata.
  • Bounded persistent homology over Vietoris-Rips and lazy witness complexes.
  • DSL topology calls: topology.ph, topology.betti, and topology.intervals.
  • ML primitives in aether-core: tensors, losses, regression, clustering, classification, neural layers, autograd scaffolding, convolution, data loading, and gossip consensus.
  • Sparse-event scheduler and geometric governor tests in the kernel/core stack.
  • Ten integrated modules in aether-core, each a certificate or a typed refusal: linking numbers, rounding certificates, segment arrangements, the resolvent operator, orbit bounds, monodromy deciders, cell tracking, coupling operators, segment witnesses and runtime planning. See Integrated Mathematics.

What Is Roadmap Or Gated

  • Hardware acceleration and GPU claims.
  • Production security claims for binary authentication.
  • End-to-end benchmark speedups.
  • Full language-level type checking.
  • Framework parity with PyTorch, TensorFlow, CUDA, or Triton.
  • Bare-metal bootability as a user-facing distribution target.

None is described as active until tests and artifacts cover the claim.

Learning Path

  1. Read the language pipeline to understand source-to-runtime flow.
  2. Read persistent homology and derivations before relying on topology terms.
  3. Read the runtime surface and status matrix to separate active behavior from scaffolding.
  4. Run the local checks before trusting any performance or backend statement.

Evidence Policy

Every active claim should have one of three forms:

  • a unit test or integration test;
  • a runnable CLI or benchmark artifact;
  • a docs-only theory or roadmap statement clearly labeled as such.

Theory →