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Active Inference as Context Acquisition for AI Agents.


How LLM Serves a Request

How LLM Serves a Request.


TT-AMX, a zero-copy Tensor-Train inference engine for Apple Silicon.


Show HN: A Ruby IDE running on a microcontroller. I built AREA512, software that lets you write, compile, and run Ruby code entirely on the M5Stack Cardputer.
https://github.com/engneer-hamachan/area512
One part I put a lot of effort into is the on-device IDE.
It has a Vim-like editor with:
- Syntax highlighting
- Auto-indentation
- Code completion
- Type checking
The code completion and type checking aren't implemented using a simple dictionary or predefined list of symbols.
Instead, they're powered by picoruby-ti, a type inference engine I developed separately with the goal of making it portable enough to run on PCs, microcontrollers, and web browsers:
https://github.com/engneer-hamachan/picoruby-ti
I haven't seen many IDEs this feature-rich running entirely on a microcontroller.
One of my goals with this project is to preserve some of the spirit of 1980s home computer culture — when the computer you used was also the computer you programmed.
I'd love to hear your feedback, especially if you have ideas for features that would be fun or interesting to add.
Thanks for reading!


High-Throughput Lean 4 Autoformalization Model for Local Inference.


Influencers and Resellers Are Turning Empty Boxes into Big Cash.


LFM2.5-DSpark: Up to 3.2x Faster Inference from H100 to MacB.


IO Factory: Simulating AI-Enabled Influence Campaigns at Scale.


Show HN: Proliferate- open-source, self-hostable Codex for any coding agent. Hi HN- I'm Pablo, the founder of Proliferate (YC S25)!
Proliferate (https://github.com/proliferate-ai/proliferate) is an open-source, self-hostable AI IDE that lets you work and automate tasks with Claude Code, Codex, OpenCode, Cursor, and Grok in one place.
Here's a quick 2m demo of how we use Proliferate to build Proliferate: https://www.youtube.com/watch?v=tGNX0oaWmBY
I started building Proliferate after my team onboarded to OpenAI Codex. Within days, we were using it for everything: using computer use instead of navigating websites ourselves, having Codex coordinate other agents, and setting up automations for recurring work. We really never needed to leave the desktop app to get work done.
If my team’s experience is anything close to representative, a Codex-like app (a horizontal agent with a beautiful UI) is the main interface every company is going to use to get work done. That is perfectly in line with OpenAI’s mission to make Codex the everything app (see: https://news.ycombinator.com/item?id=47796469).
But as we started automating work closer to the core of the business, I wanted to work with agents from all the labs, including open-weight models, without becoming increasingly dependent on OpenAI.
And that’s what Proliferate is for! It's the open-source, self-hostable Codex that preserves your optionality across agents and model providers while building toward Codex’s breadth.
Today Proliferate supports:
* Working with Claude Code, Codex, OpenCode, Cursor, and Grok with their native inference and configuration options, including Bedrock, Azure, and self hosted inference.
* Inter-agent communication and management: a parent agent can spawn and communicate with another supported agent as a subagent (I personally like to have Fable delegate to Codex, with OpenCode models reviewing PRs).
* Building workflows- one of the features I'm most excited about. These are re-usable chains of agent sessions and human approval gates, with the harness and model chosen per step and documents passed between them. I use this to automate code review, QA, and my PR construction process.
All of Proliferate is 100% open source under AGPL-3.0. There are still definitely some rough spots, but we’re building fast and I’d really love any feedback!


Anti India Influence Machine: Troll Farms, Fake News, Algorithms and AI.


Show HN: Pigame – pi+LLM plays black-box browser games via observe/move tools. If we compress LLMs into neuromorphic chips to reduce inference latency, would it be relatively easy to achieve low-cost autonomous driving?


Show HN: Youtilitics, energy usage analytics from utility data, no hardware. I posted an early version of this 2 years ago. Rebuilt most of it since then, so posting again with what's actually different.
Youtilitics still pulls interval data your utility already collects (Green Button/ESPI — 15-60 min whole-house kWh) and turns it into usage analytics.
The analytics stack is different: baseline anomaly detection (median/MAD by time-of-day bucket, not a flat threshold), overnight step-change alerts, usage heatmaps, cycle-over-cycle comparisons, etc.
It is still based on a model trained on human-labelled data: used to differentiate baseline (eg vampire load) vs EV vs HVAC vs the rest. Inference runs with a python script when new data is received from the utility.
I also changed the mobile app. It is still mainly used to store the user credentials without us having them (they never leave the device), for security/privacy reasons. This is used to scrape usage data from the utility dashboard, when they don't support Green Button.
However now it also runs an embedded Python interpreter (serious-python) to embed an opower python library. This seems overkill but that was the best way to have a lot of utilities on board (there are a lot on opower without green button support). Mobile stack is flutter.
Curious if anyone has an opinion on that, I'm not too happy with it but looks like the best compromise.
New this year: Youtilitics also expands to business with a focus on management of many doors, not just the home you live in. Allowing property managers, portfolio managers and short term rental owners to get alerts on unusual usage. Similar data & analytics, but with a rollup view and targeted at real estate professionals.
Same limitation as 2y ago: data latency is 1+ day, so this is not real-time monitoring like Sense/Emporia. It's a different tool for a different question. "what happened and is it normal," not "what's drawing power right now."
Upside is no hardware required + historical data is available on day 1.


Can influencers post AI ads without alienating their fans?.


Single-User Inference Card

Single-User Inference Card.


Claude "warning" users about language and defending business influencers.