InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now. Learn more →
SpinStep Alternatives
Similar projects and alternatives to SpinStep
-
openpilot
openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars.
-
InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
-
transformers.js
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
-
ghostty
👻 Ghostty is a fast, feature-rich, and cross-platform terminal emulator that uses platform-native UI and GPU acceleration.
-
-
-
-
portable-hnsw
What if an HNSW index was just a file, and you could serve it from a CDN, and search it directly in the browser?
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
rss-aggregator-using-cohere-embeddings-bedrock
A sample rss aggregator application demonstrating the use of Cohere Embeddings
-
-
Imath
Imath is a C++ and python library of 2D and 3D vector, matrix, and math operations for computer graphics
SpinStep discussion
SpinStep reviews and mentions
-
Spherical CNNs (2018)
Great subject, thanks. I recently built SpinStep[0], a lightweight tool for visualizing and stepping through CNN (convolutional neural network) computations.
It lets you upload a model, then see—layer by layer—how inputs are transformed, which kernels activate, and how feature maps evolve. It’s not just pretty viz: it's a hands-on exploration of what’s actually happening under the hood in CNNs.
For anyone who's been frustrated by the opaque "black‑box" nature of CNNs, SpinStep might be a fun way to poke around and build intuition. I
[0] https://github.com/VoxleOne/SpinStep/blob/main/docs/index.md
-
Animate a mesh across a sphere's surface
Neat approach! For this kind of mesh animation on a sphere’s surface, another path worth exploring is quaternion-based orientation traversal. I’ve been experimenting with this in SpinStep[0] — a Python library that uses quaternions to step through spatial structures based on orientation rather than position.
It’s particularly helpful when you want smooth, rotation-aware transitions (like gliding across a sphere’s surface) without relying solely on angles or coordinate systems. Could be interesting to try a similar traversal heuristic in a Three.js context using Quaternion.slerp().
[0]https://github.com/VoxLeone/SpinStep/blob/main/README.md
-
Autonomous drone defeats human champions in racing first
>>Just wait until these things can move through space with physical/gyro sensors on their own,
and better guidance software. Yeah, there's a lot of room for improvement
"Traditional waypoint navigation assumes movement through a series of Cartesian positions. But in pursuit dynamics, for example, what matters is directional alignment over time"
https://github.com/VoxleOne/SpinStep/blob/main/docs/01-ratio...
-
Ray Tracing in J
Fascinating article – a great example of J's array-processing power for concise, performant geometric computation.
It got me thinking about how different paradigms could complement this. I've been working on a Python project[0], which is a framework for quaternion-driven traversal of tree-like structures based on orientation rather than just position or order.
Essentially, J handles the low-level "how" of vector math at scale, while SpinStep-like concepts could provide a higher-level, more semantic "what" and "why" for decisions driven by explicit orientation sets and angular relationships.
It's an interesting thought experiment on combining the raw power of array languages for geometry with more specialized frameworks for orientation-based reasoning.
[0] https://github.com/VoxleOne/SpinStep
-
Compiling a Neural Net to C for a 1,744× speedup
Well done — really enjoyed this. We could use this kind of optimization in our library[0], which builds differentiable logic networks out of gates like AND, XOR, etc.
It focuses on training circuit-like structures via gradient descent using soft logic semantics. The idea of compiling trained models down to efficient bit-parallel C is exactly the kind of post-training optimization we’ve been exploring — converting soft gates back into hard boolean logic (e.g. by thresholding or symbolic substitution), then emitting optimized code for inference (C, WASM, HDL, etc).
The Game of Life kernel is a great example of where logic-based nets really shine.
[0]https://github.com/VoxLeone/SpinStep/tree/main/benchmark
- Show HN: SpinStep – Quaternion-based 3D graph explorer
-
Embeddings Are Underrated
I've been exploring the idea of building a new kind of data traversal engine — not based on linear or tree structures, but on *quaternions* and 3D orientation. It's inspired by a small project called [SpinStep](https://github.com/VoxLeone/SpinStep), which uses quaternion math (yaw, pitch, roll) to move through a graph via rotation, not position.
At first, it’s a fun math trick. But then I realized: this could be much more. What if we combined this with *Quaternion Neural Networks (QNNs)* — deep learning models that embed graph data in quaternion space, capturing structure and symmetry in a compact way?
Imagine this architecture:
* *SpinStep* handles orientation-based traversal across a graph of data points.
-
A note from our sponsor - InfluxDB
www.influxdata.com | 20 Jun 2025
Stats
VoxleOne/SpinStep is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of SpinStep is Python.