HackerNews

Factoring RSA 260

Article URL: https://cognition.com/blog/factoring-rsa-260 Comments URL: https://news.ycombinator.com/item?id=49633534 Points: 83 # Comments: 11
HackerNews

Show HN: What if the speed of light was 5 km/h?

I've always wanted to make a visualization where the speed of light was scaled down to human speeds, so that we could intuit relativistic effects with everyday objects. Here is the first version of it! Comments URL: https://news.ycombinator.com/item?id=49637385 Points: 253 # Comments: 103
HackerNews

OpenAI might have stolen another major proof

Article URL: https://twitter.com/ValerioCapraro/status/2097791836269977996 Comments URL: https://news.ycombinator.com/item?id=49638353 Points: 156 # Comments: 51
HackerNews

DeepSeek v4.1 Flash

Article URL: https://twitter.com/deepseek_ai/status/2097930608790167907 Comments URL: https://news.ycombinator.com/item?id=49639090 Points: 116 # Comments: 19
🌍 Dev.to

AI Video Just Became Programmable Television

A strange thing happened when fal made H3 Max faster than realtime. The obvious benchmark story was: a 5-second video can render in under 3 seconds. The more interesting story is what developers started building once generation became faster than playback. They built television. The first demo got banned Fal engineer Rehan Sheikh connected H3 Max to a livestream inspired by the "interdimensional cable" idea from Rick and Morty. The important technical property ...
🌍 Dev.to

Node.js API Boundaries for Realtime Quota Protection in Live Auction Dashboards

Short answer: put a small, explicit quota boundary in front of every realtime connection, make reconnect and backfill consume a separate budget, and measure freshness rather than WebSocket count. For a live auction dashboard, this keeps a reconnect storm from starving the bids, typing indicators, and read receipts that operators actually need. The page that wakes the on-call engineer is usually not the page they needed. It says realtime_connections > 50,000 or reports a spike of HTTP 429...
Partition once versus filter twice for bulk email validation
🌍 Dev.to

Partition once versus filter twice for bulk email validation

The decision The partition function separates the array into the elements that satisfy the condition from those that do not docs . The filter function iterates over an array and applies an expression that returns matching values docs . Both scripts compute the task to split payload.records into accepted ids and rejected records with a reason, plus a retry count, by an email match. First approach The partition once approach uses the import line import * from dw::core::Array...
🌍 Dev.to

Building a Browser-Local Moving Checklist Without User Accounts

Many planning tools begin with sign-up, cloud storage, and collaboration features. For a moving checklist, I wanted to test a narrower idea: can a useful planning tool work without requiring an account? MovePlaybook is a browser-based moving checklist. A user starts with a move date, reviews a generated task plan, adjusts tasks when circumstances change, and can print or save the plan as a PDF. The technical constraint was privacy: the product should remain useful even when the plan is sto...
FlowGit: The Ultimate Native Git Client — Full Feature Showcase, Architecture & Why It Outclasses Electron
🌍 Dev.to

FlowGit: The Ultimate Native Git Client — Full Feature Showcase, Architecture & Why It Outclasses Electron

⚡ FlowGit: The Ultimate Visual Git Client — Full Architectural & Feature Deep Dive "Visual First – Zero Terminal Friction – No-Fear Git" Lõi Rust Native • Đồ Thị 60 FPS • Kéo Thả Rebase • Thùng Rác 48h Chống Mất Mã Nguồn For years, developers have been forced to choose between two extremes: The Terminal CLI: Infinite power, but terrifying syntax, high cognitive load, zero visual intuition, and constant fear of fat-fingering an irreversible git reset --hard . Exi...
🌍 Dev.to

We rewrote LF Edge eKuiper in Rust: 425k eps, 8MB RAM, 13ms boot (vs Flink, Go eKuiper & Benthos)

Over at I-Dacs Labs , we run high-throughput telemetry pipelines on edge devices (Raspberry Pis, Advantech gateways, and embedded x86/ARM boxes). We've been using LF Edge eKuiper for local stream processing (SQL filtering, sliding windows, and MQTT/Kafka sinks), but kept hitting the classic edge computing wall: JVM engines (Apache Flink) : Incredible throughput, but require >1 GB RAM and take 20+ seconds to boot. Unusable on small industrial hardware. Go engines (Upstream eKuipe...
When Cleanup Resets the Retry Budget
🌍 Dev.to

When Cleanup Resets the Retry Budget

When Cleanup Resets the Retry Budget A retry limiter can record an attempt correctly and still lose control before the next call. An Orca recovery-module experiment exposed the reason: display cleanup erased a terminal's recovery history while that terminal remained eligible for another remount. The useful review target is the cleanup predicate. Adapted from the complete English research article . Two indexes disagree about one object Orca is a desktop tool for org...
Introducing GitTrends AI v5.0: Real-Time GitHub Velocity & 1-Click MCP Discovery for Coding Agents
🌍 Dev.to

Introducing GitTrends AI v5.0: Real-Time GitHub Velocity & 1-Click MCP Discovery for Coding Agents

🚀 Why Traditional GitHub Trending Falls Short for AI Engineers If you build with AI coding agents (Claude Code, Cursor, Codex, Antigravity), you’ve probably noticed a major blind spot in developer tooling: discovery . GitHub's native trending feed is useful, but: It ignores velocity dynamics: A repo with 50 stars gaining 40/day is moving faster than a 100k repo gaining 5, but gets buried. No taxonomy for the Agent Ecosystem: There’s no native way to filter specifically for ...
🌍 Dev.to

AI Orchestration for Enterprise .NET Applications: Scaling Intelligent Agents with Azure

Quick Answer AI Orchestration for Enterprise .NET Applications: AI orchestration adds a disciplined layer to .NET apps, coordinating agents, caching, state, and compliance to reduce latency, cost, and hallucinations. AI Orchestration for Enterprise .NET Applications – A Production‑Ready Playbook Scaling Pitfalls of Single-Request AI Calls In many .NET shops the first step to “add AI” is to fire a single HttpClient request from a Razor page. That works for a han...
🌍 Dev.to

How to Assign Seller Login OTP Templates: SMS and Email Delivery Governance

Short answer: assign the authentication team ownership of the login OTP contract, keep the marketplace team responsible for new-order messages, and compare SMS and email using verified-code outcomes rather than send or open events. That boundary keeps a seller's two-factor login safe when the order-notification copy changes, and it gives US and EU rollout decisions a measurable trail. The operational constraint is template ownership. A seller can receive an order alert and a login code within...
🌍 Dev.to

You probably do not need 264 AI agents

Disclosure: Software Sausage is our product. Agency Agents did not sponsor, review, or endorse this article. AI tools helped draft and edit it; the evidence boundary is stated below. You probably do not need 264 AI agents. You need bounded roles and a gate The Agency Agents repository is difficult to ignore: 264 specialized agent definitions, broad coding-harness support, and—when I reviewed it on September 9, 2026—roughly 151,000 GitHub stars. The tempting conclusion is tha...
🌍 Dev.to

Multi-Provider LLM Router, or How I Got Tired of Forgetting Which API Format I Had To Use

If you've ever built an application that integrates with multiple LLM providers (Anthropic, Google, OpenAI, DeepSeek), you already know the pain: Each provider has its own distinct Python SDK. Streaming responses using Server-Sent Events (SSE) requires divergent parser logic. Thinking / Reasoning blocks are formatted completely differently. I recently extracted the core streaming router from my platform into an open-source FastAPI template. Here is how it works. Obje...
🌍 Lobsters

Efficient and accurate systems for querying unstructured data

Abstract: (shortened) In recent years, automatic analysis over this unstructured data has become possible via machine learning (ML). Analysts can use ML to extract structured information from these unstructured sources, such as object types and location from a video. The structured information can subsequently be used in downstream analysis, e.g., the urban planner can count the number of cars that passed by an intersection. Unfortunately, using ML for these analyses is challenging. Deployin...