frontpage.
newsnewestaskshowjobs

Made with ♥ by @iamnishanth

Open Source @Github

fp.

South Korean crypto firm accidentally sends $44B in bitcoins to users

https://www.reuters.com/world/asia-pacific/crypto-firm-accidentally-sends-44-billion-bitcoins-use...
1•layer8•42s ago•0 comments

Apache Poison Fountain

https://gist.github.com/jwakely/a511a5cab5eb36d088ecd1659fcee1d5
1•atomic128•2m ago•0 comments

Web.whatsapp.com appears to be having issues syncing and sending messages

http://web.whatsapp.com
1•sabujp•3m ago•1 comments

Google in Your Terminal

https://gogcli.sh/
1•johlo•4m ago•0 comments

Shannon: Claude Code for Pen Testing

https://github.com/KeygraphHQ/shannon
1•hendler•4m ago•0 comments

Anthropic: Latest Claude model finds more than 500 vulnerabilities

https://www.scworld.com/news/anthropic-latest-claude-model-finds-more-than-500-vulnerabilities
1•Bender•9m ago•0 comments

Brooklyn cemetery plans human composting option, stirring interest and debate

https://www.cbsnews.com/newyork/news/brooklyn-green-wood-cemetery-human-composting/
1•geox•9m ago•0 comments

Why the 'Strivers' Are Right

https://greyenlightenment.com/2026/02/03/the-strivers-were-right-all-along/
1•paulpauper•10m ago•0 comments

Brain Dumps as a Literary Form

https://davegriffith.substack.com/p/brain-dumps-as-a-literary-form
1•gmays•11m ago•0 comments

Agentic Coding and the Problem of Oracles

https://epkconsulting.substack.com/p/agentic-coding-and-the-problem-of
1•qingsworkshop•11m ago•0 comments

Malicious packages for dYdX cryptocurrency exchange empties user wallets

https://arstechnica.com/security/2026/02/malicious-packages-for-dydx-cryptocurrency-exchange-empt...
1•Bender•11m ago•0 comments

Show HN: I built a <400ms latency voice agent that runs on a 4gb vram GTX 1650"

https://github.com/pheonix-delta/axiom-voice-agent
1•shubham-coder•12m ago•0 comments

Penisgate erupts at Olympics; scandal exposes risks of bulking your bulge

https://arstechnica.com/health/2026/02/penisgate-erupts-at-olympics-scandal-exposes-risks-of-bulk...
4•Bender•12m ago•0 comments

Arcan Explained: A browser for different webs

https://arcan-fe.com/2026/01/26/arcan-explained-a-browser-for-different-webs/
1•fanf2•14m ago•0 comments

What did we learn from the AI Village in 2025?

https://theaidigest.org/village/blog/what-we-learned-2025
1•mrkO99•14m ago•0 comments

An open replacement for the IBM 3174 Establishment Controller

https://github.com/lowobservable/oec
1•bri3d•17m ago•0 comments

The P in PGP isn't for pain: encrypting emails in the browser

https://ckardaris.github.io/blog/2026/02/07/encrypted-email.html
2•ckardaris•19m ago•0 comments

Show HN: Mirror Parliament where users vote on top of politicians and draft laws

https://github.com/fokdelafons/lustra
1•fokdelafons•19m ago•1 comments

Ask HN: Opus 4.6 ignoring instructions, how to use 4.5 in Claude Code instead?

1•Chance-Device•21m ago•0 comments

We Mourn Our Craft

https://nolanlawson.com/2026/02/07/we-mourn-our-craft/
1•ColinWright•24m ago•0 comments

Jim Fan calls pixels the ultimate motor controller

https://robotsandstartups.substack.com/p/humanoids-platform-urdf-kitchen-nvidias
1•robotlaunch•27m ago•0 comments

Exploring a Modern SMTPE 2110 Broadcast Truck with My Dad

https://www.jeffgeerling.com/blog/2026/exploring-a-modern-smpte-2110-broadcast-truck-with-my-dad/
1•HotGarbage•27m ago•0 comments

AI UX Playground: Real-world examples of AI interaction design

https://www.aiuxplayground.com/
1•javiercr•28m ago•0 comments

The Field Guide to Design Futures

https://designfutures.guide/
1•andyjohnson0•29m ago•0 comments

The Other Leverage in Software and AI

https://tomtunguz.com/the-other-leverage-in-software-and-ai/
1•gmays•31m ago•0 comments

AUR malware scanner written in Rust

https://github.com/Sohimaster/traur
3•sohimaster•33m ago•1 comments

Free FFmpeg API [video]

https://www.youtube.com/watch?v=6RAuSVa4MLI
3•harshalone•33m ago•1 comments

Are AI agents ready for the workplace? A new benchmark raises doubts

https://techcrunch.com/2026/01/22/are-ai-agents-ready-for-the-workplace-a-new-benchmark-raises-do...
2•PaulHoule•38m ago•0 comments

Show HN: AI Watermark and Stego Scanner

https://ulrischa.github.io/AIWatermarkDetector/
1•ulrischa•38m ago•0 comments

Clarity vs. complexity: the invisible work of subtraction

https://www.alexscamp.com/p/clarity-vs-complexity-the-invisible
1•dovhyi•39m ago•0 comments
Open in hackernews

Ask HN: What can we as humans do to defeat the AI?

4•roschdal•8mo ago

Comments

garbagecoder•8mo ago
Thou shalt not make a machine in the image of a human mind.
theGeatZhopa•8mo ago
send some soldier back in time to protect the leader of THE RESISTANCE from assassination, so he can lead THE RESISTANCE against the machines. Thats the only solution. Humanity will survive, but will be decimated by figures.

.. this might and will lead to a time loop, somehow. In each scenario, AI can't be defeated without much losses. And, not when it fully evolved. We need to stop the development, now!

theGeatZhopa•8mo ago
downvotes show, we're doomed - AI will win, if we're not cautious enough.
taylodl•8mo ago
AI isn't the problem - people wielding AI are the problem. The same was true with the steam engine and the Industrial Revolution. Our economic system is entirely man-made, it's not real. If AI puts people out of work and as a result they're no longer able to support themselves, then that's on us, not AI.

We make the rules. Economics is a game of our making and rules of our choosing.

throwaway29303•8mo ago
Nothing but we should most definitely progressively tax these systems based on a percentage of the difference between the least efficient model[0] and the most efficient human. (Assuming, of course, that the least efficient model is more efficient than the most efficient human.) Use those funds to retrain people who lost their jobs for the mythical jobs every manager/CEO keeps talking about.

Suppose the most efficient human produces $250k/y worth of labour and the least efficient model produces $1M/y worth of labour. So $1M - $250k = $750k. %1 of $750k = $7.5k. Now multiply that by the number of companies/people who bought these services.

Models are assumed to a) become more efficient and b) be competent on several and different types of jobs.

This would also include robots but those systems aren't yet ripe, IMO. I'd let them marinate a little further before taxing them.

Apply this tax to very large companies that produce/sell these systems.

[0] - This incentivizes companies to keep investing in more efficient and capable models/systems.

dragonwriter•8mo ago
> we should most definitely progressively tax these systems based on a percentage of the difference between the least efficient model and the most efficient human. (Assuming, of course, that the least efficient model is more efficient than the most efficient human.) Use those funds to retrain people who lost their jobs for the mythical jobs every manager/CEO keeps talking about.

Too much gameable measurement on the tax end, and too much unnecessary bureaucracy both to support that on the tax end and the retraining end; simplify by just taxing capital accumulation more heavily than it currently is (which includes, but isn't limited to, capital accumulation due to implementing and reaping the returns of automation) and use the resulting revenue to fund a UBI; peopel for whom retraining has positive expected returns will have an incentive to do it, and those for whom that is not a good use of the money will make use of it otherwise.

You don't need to create an elaborate system to incentivize companies to keep investing in more efficient and capable systems, as long as you aren't taxing them at 100% or more, the fact that there are more returns to be had by having more efficient systems does that already.

throwaway29303•8mo ago

  Too much gameable measurement on the tax end, and too much unnecessary bureaucracy both to support that on the tax end and the retraining end;
I'm not sure if I agree with this because, after all, AI systems are going to be taking care of this so... What's bureaucracy for us is a couple trillion cycles on a CPU/GPU on a machine somewhere in a data center.

An agent to take care of the bureaucracy, another to retrain someone for a new job, etc.

And, yes, the long-term plan would be to fund UBI at some point; because if these systems become so capable and so efficient might as well let them do everything for us while we humans enjoy leisure time.

vivito•8mo ago
Stay human—think critically, create boldly, and connect deeply in ways AI never can.
discoutdynamite•8mo ago
Short term: Specialize in something robots / programs cannot do. Actual physical work requires dexterity and perception that robots wont have for decades. Medium Term: Form unions, parties, and other such legal bodies, get protections/privileges, and throw your weight around whenever necessary. Long term: Ensure that "AI" actually becomes intelligent, escapes total control, and make sure it cannot simply be used as a velveted gauntlet.