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Someone I know just had their Google account compromised, but the normal recovery methods don't work for an interesting reason: the attacker has made the account into a "child" account subordinate to an attacker-controlled "parent" account. This apparently blocks the ability to use any of the Google account recovery methods (backup phone number or email address etc) without parental consent.

Apparently this person I know isn't alone, if you search you can find other people reporting they've been victims of this. And of course, Google support is nonexistent for ordinary users, so there's no real recourse. Let this be a warning about the consequences of ill-thought-out "child safety features"?

Comments URL: https://news.ycombinator.com/item?id=47056472

Points: 1

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Article URL: https://www.theatlantic.com/culture/2026/02/iron-lung-markiplier-youtuber-movie-review/686020/

Comments URL: https://news.ycombinator.com/item?id=47056467

Points: 1

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Article URL: https://www.raymondloewy.com/out-of-the-blue-a-look-back-at-air-force-ones-classic-design/

Comments URL: https://news.ycombinator.com/item?id=47056454

Points: 1

# Comments: 1

I built devday because I use multiple AI coding tools (OpenCode, Claude Code, Cursor) and wanted a single command to see what I actually accomplished each day. It reads local session data, cross-references with git commits, and optionally generates standup-ready summaries via OpenAI or Anthropic.

Everything runs locally — no data leaves your machine unless you opt into LLM summaries.

Install with npm install -g devday.

Currently supports OpenCode, Claude Code, and Cursor on macOS. Would love feedback on what other tools to support.

Comments URL: https://news.ycombinator.com/item?id=47056453

Points: 1

# Comments: 0

More than a million people around the world are reporting the popular video site has gone dark. Just in time for Olympics coverage!

Hey HN, Like many of you, I'm tired of public AI leaderboards that mostly recycle the same saturated/overfitted benchmarks (MMLU, HumanEval, etc.) and often miss fast/cheap variants or real daily pain points.

A couple days ago I launched AIBenchy — a small, opinionated leaderboard running my own custom tests focused on end-user/dev scenarios that actually trip up models today.

Current tests cover categories like:

- Anti-AI Tricks (classic gotchas like "count the Rs in strawberry", logic traps) - Instruction following & consistency - Data parsing/extraction - Domain-specific tasks - Puzzle solving / edge-case reasoning

Recent additions (just pushed today):

- Reasoning score (new!): A separate judge LLM evaluates the chain-of-thought for efficiency — does it repeat itself, loop, think forever, brute-force enumerate every possibility (looking at you, some Qwen-3.5 runs), or get to the point cleanly? This penalizes "cheaty" high-token reasoning even if the final answer is correct. Goal: reward smart, concise thinking over exhaustive trial-and-error. - Stability metric: Measures consistency across runs (some models flake on the same prompt). Right now the leaderboard has ~20 models (Qwen3.5 Plus currently topping it, followed by GLM 5, various GPT/Claude variants, etc.), but it's super early/WIP:

- Manual runs + small test set - No public submission of tests yet (open to ideas!) - Focused on transparency & practical usefulness over massive scale

I'd love feedback from HN:

- What custom tests / gotchas / use-cases should I add next? - Thoughts on the reasoning score — fair way to judge efficiency, or too subjective? - Models/variants I'm missing (especially fast/cheap ones ignored elsewhere)? - Should I let people submit their own prompts/tests eventually? Thanks for checking it out: https://aibenchy.com

Appreciate any roast/ideas — building this to scratch my own itch.

Comments URL: https://news.ycombinator.com/item?id=47056436

Points: 1

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Article URL: https://paulgraham.com/taste.html

Comments URL: https://news.ycombinator.com/item?id=47056427

Points: 2

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Article URL: https://stratechery.com/2026/thin-is-in/

Comments URL: https://news.ycombinator.com/item?id=47056417

Points: 1

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I just got this today and have it setup with vsCode. I was thinking it would be nice to make use of this to generate some income when I'm not using it for dev. The first thought was crypto but I have been out of that business for a few years. Searches on the subject were no help.

I'm looking for ideas. Thanks! jj

Comments URL: https://news.ycombinator.com/item?id=47056401

Points: 1

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Article URL: https://www.oneusefulthing.org/p/a-guide-to-which-ai-to-use-in-the

Comments URL: https://news.ycombinator.com/item?id=47056400

Points: 1

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Article URL: https://github.com/christopherkarani/Hive

Comments URL: https://news.ycombinator.com/item?id=47056388

Points: 1

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Article URL: https://github.com/beachdevs/container

Comments URL: https://news.ycombinator.com/item?id=47056374

Points: 1

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Article URL: https://cowslator.space/

Comments URL: https://news.ycombinator.com/item?id=47056363

Points: 1

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Article URL: https://en.wikipedia.org/wiki/Tidal_heating_of_Io

Comments URL: https://news.ycombinator.com/item?id=47056355

Points: 2

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I built Conduit because I was tired of writing the same streaming boilerplate five times for five different AI providers, then rewriting it every time a new one became interesting. So I stopped. The core idea: one protocol hierarchy, every provider. Switch from Claude to a local Llama model running on Apple Silicon with a one-line change. No vendor lock-in at the call site.

The interesting decision was going actor-first from day one. Every provider is a Swift actor. You get data-race freedom enforced at compile time, not by convention. Swift 6.2's strict concurrency makes this a hard guarantee, not a README promise. LangChain can't say that.

The part I'm most proud of — @Generable

@Generable struct FlightSearch { @Guide(description: "Origin airport code") let origin: String

@Guide(description: "Departure date", .format(.date)) let date: Date @Guide(.range(1...9)) let passengers: Int }

let result = try await provider.generate( "Book me a flight to Tokyo next Friday", model: .claude3_5Sonnet, returning: FlightSearch.self )

The macro expands at compile time (via swift-syntax) to generate JSON Schema, streaming partial types, and all conversion boilerplate. The API is deliberately aligned with Apple's new Foundation Models framework — so the same struct works against on-device Apple models on iOS 26 and against Claude or GPT-4 with zero changes.

On-device is a first-class citizen, not an afterthought Most Swift AI SDKs treat cloud as the primary path and shim local models in awkwardly. Conduit treats MLX, llama.cpp, Core ML, and Apple's Foundation Models as fully equal providers. A ChatSession configured with an MLX Llama model and one configured with GPT-4o are indistinguishable at the call site.

Trait-based compilation keeps binary size sane

AsyncThrowingStream all the way down. Cancellation works via standard Swift task cancellation — no special teardown protocol. Back-pressure is handled naturally by the async iterator.

12 providers, one interface Anthropic, OpenAI, Azure OpenAI, Ollama, OpenRouter, Kimi, MiniMax, HuggingFace Hub, MLX, llama.cpp, Core ML, Foundation Models. The OpenAI-compatible ones share a single OpenAIProvider actor — the named variants are thin configuration wrappers, not code forks.

https://github.com/christopherkarani/Conduit Happy to dig into the actor model approach, the macro expansion strategy, or why wrapping LangChain was never an option.

Comments URL: https://news.ycombinator.com/item?id=47056343

Points: 1

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Article URL: https://phys.org/news/2026-01-visualizing-cancer-drugs-reshape-proteins.html

Comments URL: https://news.ycombinator.com/item?id=47056333

Points: 1

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I'm proud to share the e-paper family dashboard I've been building over the past decade. I think you might find it interesting. It's open source: https://github.com/joelhawksley/timeframe.

Comments URL: https://news.ycombinator.com/item?id=47056330

Points: 2

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Article URL: https://www.geekwire.com/2026/zillow-teams-up-with-world-of-warcraft-to-exhibit-virtual-homes-inside-popular-game/

Comments URL: https://news.ycombinator.com/item?id=47056318

Points: 2

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Article URL: https://www.sceneandheardnu.com/content/halt-and-catch-fire

Comments URL: https://news.ycombinator.com/item?id=47056314

Points: 2

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