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Matchlock – Secures AI agent workloads with a Linux-based sandbox

https://github.com/jingkaihe/matchlock
66•jingkai_he•6h ago•21 comments

Dave Farber has died

https://lists.nanog.org/archives/list/nanog@lists.nanog.org/thread/TSNPJVFH4DKLINIKSMRIIVNHDG5XKJCM/
67•vitplister•2h ago•11 comments

Curating a Show on My Ineffable Mother, Ursula K. Le Guin

https://hyperallergic.com/curating-a-show-on-my-ineffable-mother-ursula-k-le-guin/
30•bryanrasmussen•4h ago•12 comments

Reverse Engineering Raiders of the Lost Ark for the Atari 2600

https://github.com/joshuanwalker/Raiders2600
31•pacod•5h ago•1 comments

Why E cores make Apple silicon fast

https://eclecticlight.co/2026/02/08/last-week-on-my-mac-why-e-cores-make-apple-silicon-fast/
79•ingve•2h ago•67 comments

DoNotNotify is now Open Source

https://donotnotify.com/opensource.html
254•awaaz•6h ago•44 comments

Show HN: It took 4 years to sell my startup. I wrote a book about it

https://derekyan.com/ma-book/
16•zhyan7109•3d ago•4 comments

Beyond agentic coding

https://haskellforall.com/2026/02/beyond-agentic-coding
174•RebelPotato•12h ago•58 comments

Show HN: LocalGPT – A local-first AI assistant in Rust with persistent memory

https://github.com/localgpt-app/localgpt
271•yi_wang•12h ago•131 comments

Show HN: Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs

https://cinegraphs.ai/
40•graphpilled•2h ago•10 comments

Rabbit Ear "Origami": programmable origami in the browser

https://rabbitear.org/book/origami.html
43•molszanski•3d ago•3 comments

A11yJSON: A standard to describe the accessibility of the physical world

https://sozialhelden.github.io/a11yjson/
24•robin_reala•5d ago•3 comments

Slop Terrifies Me

https://ezhik.jp/ai-slop-terrifies-me/
89•Ezhik•3h ago•78 comments

The Legacy of Daniel Kahneman: A Personal View (2025)

https://ejpe.org/journal/article/view/1075/753
25•cainxinth•3d ago•3 comments

We mourn our craft

https://nolanlawson.com/2026/02/07/we-mourn-our-craft/
434•ColinWright•19h ago•580 comments

SectorC: A C Compiler in 512 bytes (2023)

https://xorvoid.com/sectorc.html
331•valyala•20h ago•67 comments

LLMs as the new high level language

https://federicopereiro.com/llm-high/
156•swah•5d ago•295 comments

I write games in C (yes, C) (2016)

https://jonathanwhiting.com/writing/blog/games_in_c/
208•valyala•20h ago•228 comments

OpenClaw Is Changing My Life

https://reorx.com/blog/openclaw-is-changing-my-life/
29•novoreorx•7h ago•61 comments

The Architecture of Open Source Applications (Volume 1) Berkeley DB

https://aosabook.org/en/v1/bdb.html
58•grep_it•5d ago•8 comments

Arcan Explained – A browser for different webs

https://arcan-fe.com/2026/01/26/arcan-explained-a-browser-for-different-webs/
9•walterbell•5h ago•0 comments

Software factories and the agentic moment

https://factory.strongdm.ai/
252•mellosouls•23h ago•408 comments

Speed up responses with fast mode

https://code.claude.com/docs/en/fast-mode
205•surprisetalk•20h ago•217 comments

Hoot: Scheme on WebAssembly

https://www.spritely.institute/hoot/
203•AlexeyBrin•1d ago•43 comments

Roger Ebert Reviews "The Shawshank Redemption" (1999)

https://www.rogerebert.com/reviews/great-movie-the-shawshank-redemption-1994
42•monero-xmr•8h ago•49 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
390•jesperordrup•1d ago•125 comments

Stories from 25 Years of Software Development

https://susam.net/twenty-five-years-of-computing.html
223•vinhnx•23h ago•26 comments

uLauncher

https://github.com/jrpie/launcher
46•dtj1123•5d ago•18 comments

Modern and Antique Technologies Reveal a Dynamic Cosmos

https://www.quantamagazine.org/how-modern-and-antique-technologies-reveal-a-dynamic-cosmos-20260202/
12•sohkamyung•5d ago•0 comments

Brookhaven Lab's RHIC concludes 25-year run with final collisions

https://www.hpcwire.com/off-the-wire/brookhaven-labs-rhic-concludes-25-year-run-with-final-collis...
88•gnufx•19h ago•65 comments
Open in hackernews

I Spent Three Nights Solving Listen Labs Berghain Challenge (and Got #16)

https://kuber.studio/blog/Projects/How-I-Spent-Three-Nights-Solving-Listen-Labs-Berghain-Challenge
63•kuberwastaken•4mo ago

Comments

chriskw•4mo ago
Nice to see another participant's thinking process for the puzzles! I ended up getting 5th place using dynamic programming for all of the scenarios, but I'm under the impression that almost everybody in the top 20 had almost equally good strategies and most of the variance in scores was due to luck with the sequence of people they got.

A quick sanity check is in Scenario 2, you needed 300 creative people each with a ~6.2% chance of showing up. The odds of getting a sequence of people where that's even possible for the first place score (2906 rejections + 1000 accepts = 3906 total people) is on the order of 1 in 10000, and that's without even factoring in the other constraints.

mpeg•4mo ago
That's what I thought when I saw the challenge originally... maybe a better way of running it would have been to have each run be with a deterministic seed, and apply to all candidates.

That way people can test offline with random sequences, but the leaderboard runs have the same seed for everyone. Maybe I'm missing something obvious, but I think this would have lessened the impact of luck.

chriskw•4mo ago
The tricky thing is the code for making decisions runs locally on the contestants machine, so the first time they submit they can record the sequence locally and compute the best set of actions for the next time they submit. Even if the sequence is somehow tied to a user's account so they can't resubmit against the same sequence, they could do the same thing with an alt account and feed the sequence to a main account.

Sites like Kaggle usually get around this problem by running contestant code in a containerized environment server side, but even then you can get clever with tricks to leak info.

lupire•4mo ago
The in game leaderboard can use different, changing, seeds, and a final score can use a final secret seed.
hermannj314•4mo ago
I peaked at around 21st but stopped playing because it seemed to be a lottery.

I ran simulations with perfect information and found the lower bound for scores. Scenario 2 was mean 3743 rejections with 265 std deviation. This is the curve formed from simulated data and a strategy that had with perfect information, i.e. you could build the best possible strategy after knowing the random assignments.

So winners had scores that I could not even theoretically achieve unless I could see 1000s of scenarios.

So I ran my code locally and was happy that my code was always just a few rejections off of optimal and called that a private success.

florianj•4mo ago
How did you use DP for scenario 2 and 3? The table seems to be way to big unless you do some optimizations.

Also did you optimize for the best case in any way vs expected cases?

chriskw•4mo ago
The trick for Scenarios 2 and 3 is that most of the constraints don't end up being bottlenecks. For example in Scenario 2, well-connected pretty much always gets satisfied while doing the other constraints, so the DP table only needs 4 dimensions (space, Berlin local, techno lover, creative).

My other trick was to only build the full DP table for the latter half of the game (i.e. when all the constraints are at least 50% satisfied) which across 4 dimensions reduces the size by a factor of 16. For the beginning half of the game I combined Berlin and techno into a single parameter, which technically isn't perfect but doesn’t matter too much in the early game. I wrote up my approach here if you want more details: https://chriskw.xyz/2025/09/16/Berghain/

Re: optimizing for best case vs expected case, I thought about that but in simulations my strategy mostly performed the same as a "perfect knowledge" strategy where you could see all of the people in line ahead of time and retroactively accept people. When it under performed it was usually because some miraculous string of people showed up near the end, but betting on that happening seemed like it would do more harm than good, i.e. it would throw away more best case scenarios than it would salvage.

kuberwastaken•4mo ago
summed it way better than I could haha, also would be checking out the post, seems fun :)
kuberwastaken•4mo ago
I KNOW RIGHT, if it were more stable and less luck based, it would've been a lil more fun :)

Also, I do remember seeing you on the leaderboard, cool stuff!!!

bogdan-foo•4mo ago
"Whenever it looked like the networking issue was happening, a script automatically tore down the machine and spun up a new one with a new IP. If this really wasn’t just a me problem I’d be curious to hear what everyone else near the top of the leaderboard was doing to circumvent this."

I remembered that I have a free VPN subscription and put it to good use. When requests started to fail, a script changed my IP to another random country.

As for the solution, I used an approach similar to primal-dual optimization + some manual tweaks that made sure it capitalized when the random gods provided. To make sure I'm close to the optimal, I saved the streams and run an offline solver.

4gotunameagain•4mo ago
Wait until they find out that guest list on Berghain does not guarantee entry !

What is the probability of a person with both the attributes "looks like they belong to berghain" and "can solve an obscure live optimisation challenge" ?

j4hdufd8•4mo ago
What are you implying about people that go to Berghain?
stavros•4mo ago
They don't look like they can solve some obscure optimisation challenge.
aqme28•4mo ago
> What is the probability of a person with both the attributes "looks like they belong to berghain" and "can solve an obscure live optimisation challenge" ?

As someone who goes there often, I can say it's surprisingly high

4gotunameagain•4mo ago
Surprisingly high is not high, or we're meeting different kinds of people in there ;)
bowsamic•4mo ago
How do you know someone goes to Berghain? Don’t worry, they’ll tell you
kuberwastaken•4mo ago
LMAO
vovavili•4mo ago
>What is the probability of a person with both the attributes "looks like they belong to berghain" and "can solve an obscure live optimisation challenge" ?

As a person who has been there, you'd be surprised. Strict door policy is sort of a soft intelligence test, and the music there is so insanely good that it attracts highly creative, highly open folks.

kuberwastaken•4mo ago
> What is the probability of a person with both the attributes "looks like they belong to berghain" and "can solve an obscure live optimisation challenge" ?

You can make a hiring puzzle out of that.

NooneAtAll3•4mo ago
> For Scenario 1 (just two traits), he solved it exactly using dynamic programming.

I wonder if this exact solve tried setting "more rejections than X" as failure, so that you can get better best case for the cost of dropped worst cases

florianj•4mo ago
Great write-up. Love how everyone is sharing their solutions. Fun fact, this is an actual business problem we have to solve at our company (Listen Labs).

We have an AI customer interviewing platform our customers ask us things like: “I want to talk to 200 people, at least 100 who are ChatGPT Pro users, 75 who use Gemini weekly, and 50 from each region of the US.”

We don’t know those attributes upfront, so we have to ask participants screening questions and decide in real time whether to move forward.

Of course, it's a bit different as we optimize for the average case, not the best case, and we don't know the distributions (but can estimate with LLMs!).

kuberwastaken•4mo ago
Okay now it makes sense why you'd test for these LOL

really like whoever's idea was to make this a challenge like this was, viral potential and being actually useful :)

kuberwastaken•4mo ago
Totally DID NOT realize this did well here until I checked my analytics haha, HN is so cool with this stuff