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The European Union is implementing new rules to prevent the destruction of unsold clothes and shoes by 2026. The regulations aim to promote sustainable practices in the fashion industry and reduce textile waste.

The article discusses the development of OpenClaw, an open-source alternative to the popular video game Claw. It highlights the technical details, challenges, and community involvement in creating a faithful recreation of the classic game while exploring the legal implications and future plans for the project.

The article describes the LT6502, a low-power, high-performance microcontroller designed for embedded applications. It highlights the chip's key features, including its low power consumption, high processing speed, and extensive peripheral support.

The article discusses the evolution of CSS and explores the latest advancements in modern CSS, including new features, techniques, and best practices for creating responsive and visually appealing web designs.

Palantir, a data analytics company, has secured a contract with New York City's public hospital system, raising concerns about privacy and data usage. The article explores the potential implications of this partnership and the ongoing debate surrounding Palantir's involvement in government projects.

Ars Technica published an article containing fabricated quotations and has retracted it. The editors have issued a note addressing the issue, taking responsibility and outlining the steps taken to address the situation.

Body: I built a polyphonic synthesizer in Python with a tkinter GUI styled after the Moog Subsequent 37.

  Features: 3 oscillators, Moog ladder filter (24dB/oct), dual ADSR envelopes, LFO, glide, noise generator, 4 multitimbral channels, 19 presets, rotary
  knob GUI, virtual keyboard with mouse + QWERTY input, and MIDI support.

  No external GUI frameworks — just tkinter, numpy, and sounddevice.

Hi everyone,

I run a generative AI infra company, unified API for 600+ models. Our team started deploying AI agents for our marketing and lead gen ops: content, engagement, analytics across multiple X accounts.

OpenClaw worked fine for single agents. But at ~14 agents across 6 accounts, the problem shifted from "how do I build agents" to "how do I manage them."

Deployment, monitoring, team isolation, figuring out which agent broke what at 3am. Classic orchestration problem.

So I built klaw, modeled on Kubernetes: Clusters — isolated environments per org/project Namespaces — team-level isolation (marketing, sales, support) Channels — connect agents to Slack, X, Discord Skills — reusable agent capabilities via a marketplace

CLI works like kubectl: klaw create cluster mycompany klaw create namespace marketing klaw deploy agent.yaml

I also rewrote from Node.js to Go — agents went from 800MB+ to under 10MB each.

Quick usage example: I run a "content cluster" where each X account is its own namespace. Agent misbehaving on one account can't affect others. Adding a new account is klaw create namespace [account] + deploy the same config. 30 seconds.

The key differentiator vs frameworks like CrewAI or LangGraph: those define how agents collaborate on tasks. klaw operates one layer above — managing fleets of agents across teams with isolation and operational tooling. You could run CrewAI agents inside klaw namespaces.

Happy to answer questions.

The article discusses a new technique called 'Continuous Batching' that improves the efficiency of deep learning models by optimizing the batch size during training. It explains how this method can lead to faster convergence and better performance compared to traditional fixed-batch training.

The U.S. Department of Homeland Security has reportedly issued hundreds of subpoenas to identify and potentially prosecute individuals who have criticized the Immigration and Customs Enforcement (ICE) agency online, raising concerns about free speech and government overreach.

The article discusses the current shortage of hard disk drives (HDDs) and its impact on the artificial intelligence (AI) industry. It highlights how leading HDD manufacturer Western Digital has experienced significant supply challenges, leading to shortages and increased demand for AI-focused storage solutions.

The Dutch Defense Secretary has expressed concerns about the software issues affecting the F-35 fighter jet, highlighting the challenges of maintaining the aircraft's capabilities and calling for a collaborative effort to address these technical problems.

The Cincinnati Animal Care Shelter warns that microchips used to identify pets may fail after a major microchip company went out of business, leaving pet owners and shelters with limited options to track lost animals.

This article discusses the life and career of Peter Thiel, a prominent American entrepreneur, venture capitalist, and political activist. It covers his role as a co-founder of PayPal, his investments in companies like Facebook, and his controversial political views and involvement in the 2016 US presidential election.

GPU rental prices are super volatile but there's no derivatives market to hedge. I built a perpetual futures platform to see what this could look like.

The idea is airlines hedge jet fuel, starbucks hedges coffee beans - as GPU compute becomes critical infrastructure the same hedging tools should exist. Not sure if anyone actually needs this but it was interesting to build.

How it works: - Pulls live H200 spot prices from Vast.ai every 15s into a tradeable index - Full perp mechanics: funding rates, mark price calc, real-time P&L - Event-driven Rust backend with supervisor pattern and circuit breakers - Next.js frontend with TradingView charts, real-time WebSocket updates

What's real vs simulated: - Real: Index construction, funding rate engine, forward curve, state persistence - Simulated: Order book depth and trade matching (its a single-client demo)

The backend is the part I'm most proud of - isolated tasks coordinated by a supervisor, each has it's own state machine so if one component fails it doesn't take down the others. Tried to build it with production patterns in mind even though its just a demo.

Also made a 15-page derivatives pricing doc that covers the economic model and hedging scenarios. Basically: rental prices = f(CAPEX, utilization, depreciation) so futures pricing reveals market expectations about GPU supply/demand.

GitHub: https://github.com/zacharyfrederick/compex

Would love feedback on the architecture or if the market mechanics actually make sense. First time building something like this.

The article discusses concerns about the AI industry's pursuit of profit at the expense of safety, as evidenced by recent high-profile staff departures from AI companies. It suggests that these departures raise worries about the industry's commitment to responsible development and ethical practices.

The article explores the concept of 'unreal numbers' - mathematical entities that cannot be represented using conventional numeric systems. It delves into the implications of these abstract constructs and their potential applications in various fields, including computer science and physics.

Peter Steinberger, the creator of the OpenClaw software framework, has joined OpenAI, the artificial intelligence research company. This move highlights the continued talent acquisition efforts by OpenAI as they advance their work in AI development and research.

The article describes the horrors experienced by children during the Siege of Sarajevo, where snipers targeted and killed civilians, including young children, in the streets of the city. It highlights the traumatic impact of the war on the city's youth and the lasting effects of the violence on the Bosnian people.

The World Health Organization (WHO) has criticized a U.S.-funded clinical trial of a new vaccine for newborns, calling it unethical and raising concerns about the welfare of the infants involved. The trial was conducted in low-income countries without proper informed consent from parents.