Hacker News

Comments URL: https://news.ycombinator.com/item?id=47085549

Points: 1

# Comments: 0

Article URL: https://furotmark.github.io/2026/02/05/Using-An-Agent-Engine-AI-Agent-From-Dotnet.html

Comments URL: https://news.ycombinator.com/item?id=47085542

Points: 1

# Comments: 0

Article URL: https://github.com/whacked/cow/blob/main/vibe%20benchmarking%20json%20schema%20validators.md

Comments URL: https://news.ycombinator.com/item?id=47085517

Points: 1

# Comments: 0

Email: intelligencecyberwizard@cyber-wizard.com We typically respond within 24 hours. If you don’t receive a reply, your email may have been flagged as spam—please resend it. Security Notice: If anyone contacts you on Telegram, Facebook, Instagram, Quora, or X claiming to be Intelligence Cyber Wizard and asks for credentials or upfront payment, it is a scam. We never initiate contact, request credentials, take upfront payments, or sell wallet-opening software. Where are you located? Our head office is in San Francisco, USA with additional labs and secure server facilities in multiple locations worldwide. What makes Intelligence Cyber Wizard different? Active media and conference presence Since 2016, we have participated as partners or sponsors at major global crypto conferences in: Miami, Malta, Rome, Frankfurt, London Singapore, Dubai, Tokyo, Hong Kong About Us The journey began in 2016 when a close friend lost access to a Ledger wallet containing 150 ETH. After successfully recovering it over two evenings, we realized how widespread this problem was. 2018: Intelligence Cyber Wizard LLC incorporated in Delaware and San Francisco, USA 2021: Opened a branch in Zug, Switzerland Today: Multiple laboratories worldwide, continuously advancing recovery techniques Intelligence Cyber Wizard is among the oldest incorporated companies dedicated to recovering lost Bitcoin and Ethereum wallets.

Comments URL: https://news.ycombinator.com/item?id=47085488

Points: 1

# Comments: 0

Article URL: https://www.coinerella.com/made-in-eu-it-was-harder-than-i-thought/

Comments URL: https://news.ycombinator.com/item?id=47085483

Points: 87

# Comments: 20

Article URL: https://xeiaso.net/blog/how-http-requests-work-2020-05-19/

Comments URL: https://news.ycombinator.com/item?id=47085467

Points: 1

# Comments: 0

Article URL: https://spectrum.ieee.org/olympics-curling-robot-ai

Comments URL: https://news.ycombinator.com/item?id=47085453

Points: 1

# Comments: 0

Article URL: https://www.ft.com/content/6eca9b40-a775-470f-83f0-a6f72e616230

Comments URL: https://news.ycombinator.com/item?id=47085451

Points: 3

# Comments: 0

Article URL: https://shkspr.mobi/blog/2024/02/internationalise-the-fediverse/

Comments URL: https://news.ycombinator.com/item?id=47085434

Points: 4

# Comments: 0

Article URL: https://github.com/SchedMD/slurm

Comments URL: https://news.ycombinator.com/item?id=47085432

Points: 1

# Comments: 0

Article URL: https://blog.jetbrains.com/rust/2026/02/11/state-of-rust-2025/

Comments URL: https://news.ycombinator.com/item?id=47085429

Points: 3

# Comments: 0

Article URL: https://jimmyhmiller.com/learn-codebase-visualizer

Comments URL: https://news.ycombinator.com/item?id=47085425

Points: 1

# Comments: 0

Article URL: https://fosdem.org/2026/schedule/event/8WJKEH-package-registry-economics/

Comments URL: https://news.ycombinator.com/item?id=47085423

Points: 1

# Comments: 0

Article URL: https://devdong.textlanes.com/en/dont-touch-the-mouse

Comments URL: https://news.ycombinator.com/item?id=47085415

Points: 1

# Comments: 1

# Show HN: AstroLens -- AI that watches the sky and finds what nobody catalogued

*https://github.com/samantaba/astroLens** (MIT licensed, Python)

AstroLens is an open-source tool that downloads images from sky surveys (SDSS, ZTF, DECaLS, Pan-STARRS, Hubble, and others), runs them through a Vision Transformer + out-of-distribution ensemble + YOLOv8 pipeline, computes galaxy morphology, and cross-references everything against SIMBAD/NED/VizieR. It's designed to run autonomously for days.

*Results from a 3-day validation run* (zero human intervention):

published results in https://www.linkedin.com/pulse/astrolens-v110-teaching-ai-wa...

- 20,997 images from 7 sources analyzed - 3,458 anomaly candidates across 354 sky regions - Independently recovered SN 2014J (Type Ia supernova in M82), NGC 3690 (galaxy merger), and SDSS J0252+0039 (gravitational lens) - YOLO transient detection went from 51.5% to 99.5% mAP50 by training on data collected during the run itself - 140 self-correction cycles, zero errors

*What makes it interesting*: The pipeline is self-correcting — it adjusts OOD thresholds, rebalances survey sources based on anomaly yield, recalibrates its reference distributions, and handles errors autonomously. It's not a batch job; it's a continuous system that gets better as it runs.

*Honest limitations*: It found known objects, not new discoveries — this validates the pipeline but the real test is pointing it at less-explored regions. OOD detection on astronomical images is inherently noisy (the boundary between "unusual galaxy" and "imaging artifact" is fuzzy). The self-correcting system helps, but false positives remain a challenge.

Runs on a laptop (CPU/MPS/CUDA). Desktop app, web UI, CLI, Docker.

Built with Python 3.10+, FastAPI, PyTorch, Ultralytics, PyQt5.

Comments URL: https://news.ycombinator.com/item?id=47085410

Points: 1

# Comments: 0

Article URL: https://timharford.com/2026/02/the-paradox-of-work/

Comments URL: https://news.ycombinator.com/item?id=47085388

Points: 3

# Comments: 0

Article URL: https://nav.al/ai

Comments URL: https://news.ycombinator.com/item?id=47085285

Points: 1

# Comments: 0

Understand what your agents do in production, and how much does it cost.

Comments URL: https://news.ycombinator.com/item?id=47085283

Points: 1

# Comments: 0

I wrote a guide that walks through building a minimal GPU-initiated networking library from the ground up. It covers RDMA transport with libfabric on AWS EFA, PCIe topology-aware GPU-NIC placement, GPUDirect RDMA via DMA-BUF, CUDA IPC for intra-node NVLink transfers, and the symmetric memory model that ties it all together. Each section includes working code and benchmarks.

Comments URL: https://news.ycombinator.com/item?id=47085282

Points: 1

# Comments: 0

With everyone using Claude Code, Cursor, Codex, and the other 100 AI coding agents that i missed, I’m wondering how much editor mastery still matters like w/ Vim

Being honest the real reason i wanna learn Vim is to boost my ego & assert my dominance, so i can tell people "i use vim btw", but also part of me thinks investing time could still pay off for speed, ergonomics, and working over SSH overall...

but a bigger part also suspects the marginal gains i would gain would disappear when more of the work is delegated to AI anyway, like why would i learn Vim if i'm just going to be prompting Opus all day?

For anyone who's been using Vim for while AND uses AI to code (i'm assuming everyone codes with AI to some degree) my question is: Does learning Vim still meaningfully improve your day to day productivity EVEN with AI, or is it mostly personal preference at this point?

Comments URL: https://news.ycombinator.com/item?id=47085255

Points: 10

# Comments: 0