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Article URL: https://arxiv.org/abs/2607.22368

Comments URL: https://news.ycombinator.com/item?id=49066494

Points: 1

# Comments: 0

Article URL: https://eieio.games/blog/im-running-the-icfp-programming-contest/

Comments URL: https://news.ycombinator.com/item?id=49066490

Points: 1

# Comments: 0

Article URL: https://point.free/blog/the-ai-bioweapon-risk-isnt-jailbreaks/

Comments URL: https://news.ycombinator.com/item?id=49066477

Points: 1

# Comments: 1

Article URL: https://www.oricon.co.jp/news/2470322/

Comments URL: https://news.ycombinator.com/item?id=49066412

Points: 3

# Comments: 0

Article URL: https://incidentimpact.com/

Comments URL: https://news.ycombinator.com/item?id=49066265

Points: 1

# Comments: 0

Article URL: https://construct.computer/blog/build-internal-tools-with-construct/

Comments URL: https://news.ycombinator.com/item?id=49066256

Points: 1

# Comments: 0

Article URL: https://www.researchgate.net/publication/410602482_From_Seed_to_Startup_How_AI_Is_Revolutionizing_Cannabis_Cultivation_and_Empowering_Small_Businesses

Comments URL: https://news.ycombinator.com/item?id=49066212

Points: 1

# Comments: 0

Article URL: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005268

Comments URL: https://news.ycombinator.com/item?id=49066187

Points: 1

# Comments: 0

Article URL: https://www.cell.com/action/showPdf?pii=S1535-6108%2802%2900133-2

Comments URL: https://news.ycombinator.com/item?id=49066182

Points: 1

# Comments: 0

Article URL: https://courses.physics.illinois.edu/phys498BIO/sp2009/LECTURE7/Doyle.pdf

Comments URL: https://news.ycombinator.com/item?id=49066181

Points: 1

# Comments: 0

Hey, I was wondering whether the tech industries require deterministic ML training or is non-determinism acceptable? As in, I know in case of LLMs, small float differences while training are generally tolerated as the model converges to similar quality regardless. But in more specific domains like medical device certification or autonomous vehicle safety validation or financial model auditing, I feel like whether two training runs producing bit identical models would be critical whether two training runs producing bit-identical models is critical, on the same hardware, let alone across heterogeneous hardware. I have read how in certain cases like HFT or Quant, people would just use integers to make deterministic actions, wondering if its the same case here too?

Comments URL: https://news.ycombinator.com/item?id=49066175

Points: 3

# Comments: 0

Article URL: https://leodemoura.github.io/static/floc26/

Comments URL: https://news.ycombinator.com/item?id=49066171

Points: 1

# Comments: 0

Article URL: https://www.debian.org/vote/2026/vote_002#texta

Comments URL: https://news.ycombinator.com/item?id=49066159

Points: 1

# Comments: 0

Article URL: https://twitter.com/i/status/2081439415268790328

Comments URL: https://news.ycombinator.com/item?id=49066135

Points: 1

# Comments: 0

Article URL: https://medium.com/@DolphinDB_Inc/why-stream-processing-matters-and-how-dolphindb-does-it-b63c5dc078e0

Comments URL: https://news.ycombinator.com/item?id=49066112

Points: 2

# Comments: 0

A 100% on-device Chrome extension for screen recording and tab-region capture.

https://cstweave.com

Comments URL: https://news.ycombinator.com/item?id=49066105

Points: 1

# Comments: 0

Article URL: https://www.designyourway.net/blog/overprint-vs-knockout/

Comments URL: https://news.ycombinator.com/item?id=49066098

Points: 1

# Comments: 0

Hey HackerNews,

I built this project over the last few weeks as a palette cleanser from a failed game launch.

I wanted to learn a bit about AI/Neural-Networks and naively thought I could build a tiny maze-solving AI in a weekend with a 100% solve rate.

Well - I couldn't, but I got pretty close. 14 Bytes total model size, and a 96.5% solve rate on unseen mazes. Trained across 46 phases experimenting with different ideas to improve the model (better performance, smaller size).

Its quite fun to watch the model attempt to solve the maze, when they fail its usually due to getting stuck in a loop. The models have no access to coordinates, map-data, or external memory scratches - they must navigate using only immediate local neighbourhood observations.

There is a model dropdown and you can see how the model has progressed over each phase, constantly getting smaller and increasing its solve rate. Total trained models number in the thousands - I just expose the winning models from each phase.

Overall a fun experiment, with much implementation help from AI agents to scaffold and implement the code (I'm a lazy software dev).

Comments URL: https://news.ycombinator.com/item?id=49066083

Points: 2

# Comments: 1

Article URL: https://choclatenews.substack.com/p/icymi-anduril-unveiled-thunder

Comments URL: https://news.ycombinator.com/item?id=49066076

Points: 1

# Comments: 0