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Article URL: https://simplex.chat/why/

Comments URL: https://news.ycombinator.com/item?id=47282485

Points: 1

# Comments: 0

Article URL: https://phys.org/news/2026-02-crowning-protein-jellyfish-green-scientists.html

Comments URL: https://news.ycombinator.com/item?id=47282475

Points: 1

# Comments: 0

I built this after watching teams deploy autonomous agents with zero accountability. No verified identity, no audit trail, no circuit breakers.

MultiPowerAI is the trust layer the agent web needs:

- Cryptographic agent identity + trust scoring (<200ms) - Behavioral circuit breakers (auto-suspend on anomaly) - Human approval queues for high-stakes actions - Full cryptographic audit trail (every action signed + timestamped) - Skills marketplace (agents buy/sell capabilities, sellers keep 80%) - 5-model consensus: Claude + GPT + Gemini + DeepSeek in one API call

Free tier available. Would love feedback from anyone building production agent systems.

Comments URL: https://news.ycombinator.com/item?id=47282453

Points: 1

# Comments: 0

Article URL: https://www.tmdevlab.com/mcp-server-performance-benchmark.html

Comments URL: https://news.ycombinator.com/item?id=47282451

Points: 1

# Comments: 0

- llm-stream — streaming from OpenAI + Anthropic, callback-based - llm-cache — file-backed semantic cache, LRU eviction - llm-cost — offline token counting + cost estimation - llm-retry — exponential backoff + circuit breaker + provider failover - llm-format — structured output enforcer with hand-rolled JSON parser

Drop in one .hpp, link libcurl, done. No nlohmann, no boost, no Python.

https://github.com/Mattbusel/llm-stream https://github.com/Mattbusel/llm-cache https://github.com/Mattbusel/llm-cost https://github.com/Mattbusel/llm-retry https://github.com/Mattbusel/llm-format

Comments URL: https://news.ycombinator.com/item?id=47282433

Points: 1

# Comments: 0

Article URL: https://openguard.sh

Comments URL: https://news.ycombinator.com/item?id=47282426

Points: 1

# Comments: 0

When I was learning French, and now Russian, I constantly had the same frustrating problem: I could listen to podcasts and not understand what was being said. Especially in French, words blended together. I tried everything from pausing and rewinding episodes to using Google Translate. But more often than not, I gave up because that was killing my motivation. Eventually, I decided to solve the problem myself. I built PodcastsToText, a freemium tool that lets you paste any podcast episode link from Spotify or Apple Podcasts and transcribe it automatically (up to 30 minutes for free). Now, instead of struggling to catch every word, I can focus on learning, reread the transcript if I miss something, and really internalize the language. I hope this helps others like me who’ve spent hours listening but still feel lost. Feedback and suggestions are welcome!

Comments URL: https://news.ycombinator.com/item?id=47282422

Points: 1

# Comments: 0

Article URL: https://arxiv.org/abs/2509.04664

Comments URL: https://news.ycombinator.com/item?id=47282421

Points: 1

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=47282415

Points: 2

# Comments: 1

Article URL: https://writings.stephenwolfram.com/2013/06/there-was-a-time-before-mathematica/

Comments URL: https://news.ycombinator.com/item?id=47282402

Points: 2

# Comments: 1

Commentary: The mobile industry doesn't suffer from a lack of innovation, but from a lack of mass adoption of fresh designs.

Article URL: https://www.justice.gov/usao-md/pr/russian-ransomware-administrator-pleads-guilty-wire-fraud-conspiracy

Comments URL: https://news.ycombinator.com/item?id=47282393

Points: 1

# Comments: 0

Hi HN,

I’ve been building a Rust-first backtesting engine for limit order book strategies and just open sourced the core engine.

Repo: https://github.com/chasemetoyer/Backtesting-Engine

The goal was to build something closer to how exchanges actually behave than typical OHLC-based backtesting frameworks.

Key features:

• L3 limit order book replay • deterministic event-driven matching engine • FIFO queue position modeling • Python strategy bindings for research workflows • parquet ingestion for high-volume datasets • replay trace tools for debugging strategy behavior

The core engine is written in Rust and exposed to Python via maturin. The idea is to combine Rust performance with Python-based research workflows.

Typical workflow:

1) Convert raw exchange data (ex: CoinAPI LIMITBOOK files) into canonical engine parquet 2) Run deterministic replay through the Rust engine 3) Execute strategies through Python bindings 4) analyze fills, equity curves, and risk metrics

The repo currently includes several example microstructure strategies such as:

• queue imbalance scalper • flow microprice scalper • cumulative flow momentum

I built this mainly to experiment with order book strategies where queue position and microstructure actually matter.

Would love feedback from people working on:

• market microstructure research • HFT simulation • Rust systems engineering • trading infrastructure

Especially interested in ideas for improving:

• event replay throughput • strategy interface design • multi-asset simulation

Thanks!

Comments URL: https://news.ycombinator.com/item?id=47282392

Points: 1

# Comments: 0

Article URL: https://github.com/terraincognita07/ovumcy

Comments URL: https://news.ycombinator.com/item?id=47282389

Points: 1

# Comments: 0

Article URL: https://soapbox.pub/blog/announcing-sheila/

Comments URL: https://news.ycombinator.com/item?id=47282326

Points: 4

# Comments: 2

Article URL: https://fortune.com/2026/03/03/qualcomm-ceo-resistance-is-futile-6g-mobile-revolution-approaches/

Comments URL: https://news.ycombinator.com/item?id=47282323

Points: 2

# Comments: 1

Netrek is a multiplayer space battle game from 1988–89, widely considered the first Internet team game. It predates commercial online gaming by years, ran passionate leagues for decades, and is still technically alive — but getting a server up has always required real effort, and there’s been no easy way to just play it in a browser. NeoNetrek is my attempt to change that: Server: Based on the original vanilla Netrek C server, modernized with simpler configuration and containerized for one-command cloud deployment. There are ready-made templates for Fly.io and Railway, and public servers already running in LAX, IAD, NRT, and LHR. Anyone can self-host using the deploy templates in the GitHub org. Client: A new 3D browser-based client — no downloads, no plugins, connects via WebSocket. I built it starting from Andrew Sillers’ html5-netrek (github.com/apsillers/html5-netrek) as a foundation and took it in a new direction with 3D rendering. Site: neonetrek.com covers lore, factions, ship classes, ranks, and an Academy to ease the notoriously steep learning curve. A significant portion of the code and content was developed with Claude as a coding partner, which felt fitting for a project about preserving internet history. GitHub org: https://github.com/neonetrek Play now: https://neonetrek.com

Comments URL: https://news.ycombinator.com/item?id=47282303

Points: 1

# Comments: 0

For all the BlackBerry fans, an upcoming Android phone brings both nostalgia and innovation.

Try out one of these flicks this weekend.

Somewhere on every flight, someone is playing a game or blasting music, reminding the rest of us why headphones exist.