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The DuckDB Local UI

The DuckDB Local UI

Gemini Robotics

Gemini Robotics

Mark Klein, AT&T whistleblower who revealed NSA mass spying, has died

Mark Klein, AT&T whistleblower who revealed NSA mass spying, has died

Show HN: We built a Plug-in Home Battery for the 99.7% of us without Powerwalls

Hi HN! I’m Cole Ashman, founder of Pila Energy. I’ve spent my career working on home energy systems—first as an engineer on Tesla’s Powerwall, where I focused on the Backup Gateway, Solar Inverter, and metering systems. More recently, I led Product at SPAN, where we built the Smart Electrical Panel and integrated with most major home solar, EV, and battery systems.<p>Pila (<a href="https://pila.energy/" rel="nofollow">https://pila.energy/</a>) is a home battery that plugs into a standard wall outlet, provides smart backup power, energy shifting, and grid services. It’s more than a power bank—it’s a distributed energy system that can scale across multiple rooms, entire buildings, and work together in real time as a coordinated system. We built Pila to be local first with an open API to allow developers to build use cases on top of our hardware (Home Assistant, etc).<p>Big batteries like Tesla Powerwall and Enphase are great if you own a home and can afford a $10K+ electrical project, but they require permanent installation, electricians, and panel upgrades—which makes them inaccessible for renters, apartments, and cost-conscious homeowners. Over 50% of the cost of installing a Powerwall isn’t even the battery itself—it’s soft costs: labor, permitting, etc. We wanted to create an entry point for more people to access energy security at home.<p>How does it work?<p>Plug Pila into any 120V wall outlet, and power passes through to connected devices and appliances. The inverter, LFP battery, BMS, grid disconnection, controller, and wireless connectivity are all built in. (details at <a href="https://pila.energy/tech-specs" rel="nofollow">https://pila.energy/tech-specs</a>)<p>When an outage happens, the onboard inverter detects the power loss within 20ms and automatically disconnects from the grid (islanding). Whether you’re home or away, backup kicks in instantly. A built-in cellular radio ensures you get a notification even if your home WiFi is out. Pila is 1.6kWh. That will backup a standard fridge for over a day.<p>One key challenge we faced with a distributed architecture was coordination between batteries, for things like solar-following and managing real-time draw from your utility connection. Unlike large garage systems, where you can run a wired CAN bus, our batteries are spread across the home. We’re solving this with a sub-GHz wireless mesh network—self-healing, coordinator-less, and designed to make setup and expansion as simple as plugging in another unit.<p>Long-term, we’d love to open up this protocol to provide a more reliable communication layer for energy products in noisy built environments—reducing reliance on consumer Wi-Fi.<p>We want to deliver the value you’d expect from a whole-home battery like Powerwall, in a plug-in format. That means going beyond a basic lead acid UPS with real home energy management, useful insights about power use, power larger loads like sump pumps, and even deliver grid services.<p>Most portable batteries are missing the functionality that makes a home battery useful: no bidirectional power, no integration with solar or smart home systems, and no ability to manage home energy dynamically. They tend to be boxy, ruggedized, meant to be moved around, not seamlessly integrated into your living space. On top of that, many use e-mobility battery chemistries, which are great for delivering high power on demand but wear out faster when cycled daily for home energy use.<p>As a renter myself, I started Pila because these awesome energy products aren’t accessible enough. And frankly, generators are loud, expensive, and a pain to deal with. Even many Powerwall owners I’ve talked to say they really care about keeping the fridge, WiFi, and a sump pump running—so why does energy resilience have to be so complicated and expensive?<p>As the grid struggles to keep up with demand, we believe modular, renter-friendly batteries can make home energy resilience more accessible.<p>What's been your experience with home batteries? What recent power outages have you had, and how were you affected?

New tools for building agents

Fastplotlib: GPU-accelerated, fast, and interactive plotting library

What makes code hard to read: Visual patterns of complexity (2023)

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Factorio Learning Environment – Agents Build Factories

I'm Jack, and I'm excited to share a project that has channeled my Factorio addiction recently: the Factorio Learning Environment (FLE).<p>FLE is an open-source framework for developing and evaluating LLM agents in Factorio. It provides a controlled environment where AI models can attempt complex automation, resource management, and optimisation tasks in a grounded world with meaningful constraints.<p>A critical advantage of Factorio as a benchmark is its unbounded nature. Unlike many evals that are quickly saturated by newer models, Factorio's geometric complexity scaling means it won't be "solved" in the next 6 months (or possibly even years). This allows us to meaningfully compare models by the order-of-magnitude of resources they can produce - creating a benchmark with longevity.<p>The project began 18 months ago after years of playing Factorio, recognising its potential as an AI research testbed. A few months ago, our team (myself, Akbir, and Mart) came together to create a benchmark that tests agent capabilities in spatial reasoning and long-term planning.<p>Two technical innovations drove this project forward: First, we discovered that piping Lua into the Factorio console over TCP enables running (almost) arbitrary code without directly modding the game. Second, we developed a first-class Python API that wraps these Lua programs to provide a clean, type-hinted interface for AI agents to interact with Factorio through familiar programming paradigms.<p>Agents interact with FLE through a REPL pattern: 1. They observe the world (seeing the output of their last action) 2. Generate Python code to perform their next action 3. Receive detailed feedback (including exceptions and stdout)<p>We provide two main evaluation settings: - Lab-play: 24 structured tasks with fixed resources - Open-play: An unbounded task of building the largest possible factory on a procedurally generated map<p>We found that while LLMs show promising short-horizon skills, they struggle with spatial reasoning in constrained environments. They can discover basic automation strategies (like electric-powered drilling) but fail to achieve more complex automation (like electronic circuit manufacturing). Claude Sonnet 3.5 is currently the best model (by a significant margin).<p>The code is available at <a href="https://github.com/JackHopkins/factorio-learning-environment" rel="nofollow">https://github.com/JackHopkins/factorio-learning-environment</a>.<p>You'll need: - Factorio (version 1.1.110) - Docker - Python 3.10+<p>The README contains detailed installation instructions and examples of how to run evaluations with different LLM agents.<p>We would love to hear your thoughts and see what others can do with this framework!

Show HN: Seven39, a social media app that is only open for 3 hours every evening

I built this site as a quick test if a time boxed social media experience feels better than an endless one. So far I've just been using it with friends and it feels nice, but it seems like it is time to bring it to a larger audience.<p>Let me know what you think! It is just based on EST for now, sorry.

Happy 20th birthday, Y Combinator

Happy 20th birthday, Y Combinator

A 10x Faster TypeScript

A 10x Faster TypeScript

Canon EF and RF Lenses – All Autofocus Motors

Hi there! I have written an e-book about all autofocus motor types used in Canon EF & RF lenses from the past 40 years.

Canon EF and RF Lenses – All Autofocus Motors

Hi there! I have written an e-book about all autofocus motor types used in Canon EF & RF lenses from the past 40 years.

Music labels will regret coming for the Internet Archive, sound historian says