Tesseract Core – Autodiff-native, self-documenting software components
Tesseract Core is a command line app + Python SDK that lets scientists and engineers wrap complex scientific and machine learning code into containerized, self-documenting, differentiable functions—making them easier to use, compose, serve, share, and deploy. Its main use case is to build end-to-end differentiable pipelines consisting of wildly different components like physical simulators, geometric operators like differentiable meshers / renderers, generic data transforms, and neural networks. Just installing these heterogeneous components can be a challenge for scientists who simply…
In plain words
Tesseract Core is a command line tool and Python SDK that wraps scientific and machine learning code into containerized, self-documenting, differentiable functions. It enables scientists and engineers to build end-to-end differentiable pipelines combining physical simulators, geometric operators, data transforms, and neural networks. The tool simplifies installation and integration of heterogeneous components into optimization-driven workflows, using Pydantic as its foundation to streamline development.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Tesseract Core is a command line app + Python SDK that lets scientists and engineers wrap complex scientific and machine learning code into containerized, self-documenting, differentiable functions—making them easier to use, compose, serve, share, and deploy. Its main use case is to build end-to-end differentiable pipelines consisting of wildly different components like physical simulators, geometric operators like differentiable meshers / renderers, generic data transforms, and neural networks. Just installing these heterogeneous components can be a challenge for scientists who simply want to get things done—let alone integrating them into large-scale, optimization-driven workflows. We’re deeply inspired by the way JAX primitives work to expose their functionality [1]. Tesseracts are taking this one step further by building on top of a modern Python stack with Pydantic at its core, used as a DSL to define schemas for expected inputs and outputs (+ some custom sugar to handle arrays and differentiability) [2]. One user-given schema informs all other endpoint schemas, i.e., simply by defining the schema for apply we also generate one for jacobian, vector_jacobian_product, abstract_eval, ..., via some Pydantic metaprogramming [3]. This allows R&D staff to provide minimal config and essentially auto-generate a Docker container wrapping their software in a way that’s ready for RPC (locally and over the network). [1] https://docs.jax.dev/en/latest/jax-primitives.html [2] https://github.com/pasteurlabs/tesseract-core/blob/675e07c95... [3] https://github.com/pasteurlabs/tesseract-core/blob/675e07c95...
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
Launched alongside, March 2025
the whole month →
Mimic Human Research & Save Findings in AI Knowledge Base
AI · 2025 · sider.ai
