Hacker News

Article URL: https://vfxforth.com/flag/jfar/vol4/no4/article4.pdf

Comments URL: https://news.ycombinator.com/item?id=46928905

Points: 1

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Article URL: https://apps.apple.com/us/app/cymatica-sounds-visualizer/id6748863721

Comments URL: https://news.ycombinator.com/item?id=46928895

Points: 1

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Article URL: https://gitblack.vercel.app/

Comments URL: https://news.ycombinator.com/item?id=46928894

Points: 2

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Article URL: https://arxiv.org/abs/2602.04816

Comments URL: https://news.ycombinator.com/item?id=46928890

Points: 1

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Article URL: https://www.youtube.com/shorts/WALQOiugbWc

Comments URL: https://news.ycombinator.com/item?id=46928879

Points: 1

# Comments: 1

Article URL: https://rhetoric.byu.edu/Figures/C/correctio.htm

Comments URL: https://news.ycombinator.com/item?id=46928876

Points: 1

# Comments: 0

Article URL: https://chillphysicsenjoyer.substack.com/p/trying-to-make-an-automated-ecologist

Comments URL: https://news.ycombinator.com/item?id=46928839

Points: 1

# Comments: 0

Article URL: https://www.twz.com/air/watch-ukraines-minigun-firing-drone-hunting-turboprop-in-action

Comments URL: https://news.ycombinator.com/item?id=46928827

Points: 1

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Article URL: https://ai-interviewer.nuvoice.ai/

Comments URL: https://news.ycombinator.com/item?id=46928826

Points: 1

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Article URL: https://www.fda.gov/news-events/press-announcements/fda-intends-take-action-against-non-fda-approved-glp-1-drugs

Comments URL: https://news.ycombinator.com/item?id=46928810

Points: 12

# Comments: 3

Article URL: https://supernote.eu/choose-your-product/

Comments URL: https://news.ycombinator.com/item?id=46928783

Points: 3

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Article URL: https://serce.me/posts/2026-02-05-we-are-qa-engineers-now

Comments URL: https://news.ycombinator.com/item?id=46928778

Points: 1

# Comments: 0

Hi HN,

We recently ran an experiment to answer a simple question:

Does coordinating multiple AI agents as a team actually help with real software engineering tasks, compared to a single strong agent?

To test this, we evaluated our system on SWE-bench Verified. The benchmark consists of real GitHub issues that require understanding codebases, modifying multiple files, running tests, and iterating.

Instead of treating software engineering as a single-agent patch generation problem, we model it as an organizational process.

Our system uses a team of agents with explicit roles:

* manager: plans work, assigns tasks, integrates results * researcher: explores the codebase, issue history, constraints * engineer: implements fixes in isolated environments * reviewer: inspects changes, requests revisions, validates results

There is no fixed pipeline and no predefined number of steps. Agents communicate via structured artifacts (plans, diffs, reviews) and produce real GitHub pull requests with full history.

For evaluation, we compared three setups on SWE-bench Verified:

* single-agent baseline: GPT-5 medium reasoning + shell * agent team (ours): GPT-5 (manager, researcher) + GPT-5 Codex (engineer, reviewer), both medium reasoning * stronger single-model reference: GPT-5.2 (high reasoning)

Results:

* the agent team resolves ~7% more issues than the single-agent GPT-5 medium reasoning baseline * despite using medium reasoning models, the agent team shows ~0.5% better quality than a single GPT-5.2 (high reasoning) agent

Beyond resolution rate, the main benefits are cleaner responsibility boundaries, context isolation, easier debugging and the ability to use different models for different roles.

Code + trajectories are open source: https://github.com/agynio/platform

Paper with methodology and results: https://arxiv.org/abs/2602.01465

Would love to hear your thoughts.

Comments URL: https://news.ycombinator.com/item?id=46928777

Points: 2

# Comments: 0

Article URL: https://www.latent.space/p/adversarial-reasoning

Comments URL: https://news.ycombinator.com/item?id=46928771

Points: 1

# Comments: 0

Hey, so I built a way to search podcast transcripts by speaker and hence also a way to follow people within them.

Poddley let's you search quotes and filter by name and vice versa. You can find ev everything they've said across all their with timestamps and with a read-along UI.

You can also RSS feeds for specific people instead subscribing to entire shows. I started this because I wanted to find podcasts where my favorite speakers talked about my favorite things (in my case that was certain longevity-research). However simply searching for stuff like "rapamycin", would yield quotes by 99% people I wasn't interested in.

I think this could be useful for people that are journalists, hobbyists, casual people and pretty much everyone that's interested in finding quotes and talking-areas in a podcast by people they respect/want to listen more to etc.

Currently indexing about 10 podcasts due to POC.

Comments URL: https://news.ycombinator.com/item?id=46928683

Points: 1

# Comments: 0

Article URL: https://www.cnbc.com/2026/02/05/layoff-and-hiring-announcements-hit-their-worst-january-levels-since-2009-challenger-says.html

Comments URL: https://news.ycombinator.com/item?id=46928682

Points: 9

# Comments: 0

Article URL: https://github.com/ArthurHeymans/emacs-tramp-rpc

Comments URL: https://news.ycombinator.com/item?id=46928399

Points: 1

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Article URL: https://akiraux.vercel.app/

Comments URL: https://news.ycombinator.com/item?id=46928359

Points: 1

# Comments: 1

Article URL: https://post.substack.com/p/there-must-be-something-like-the

Comments URL: https://news.ycombinator.com/item?id=46928343

Points: 1

# Comments: 0

The idea is to recreate the entire movie theater experience, including the worst parts.

This mode would add audience reactions like laughter, gasps, and clapping at key moments, so movies feel like an event again.

But it would also faithfully recreate the true theater experience:

* People shouting comments at the screen like they are part of the movie

* Someone standing up at the exact worst moment and blocking your view

* A person behind you explaining the plot to their friend in a whisper that is somehow louder than normal talking

* Random coughing fits that last way too long

* Someone’s phone lighting up like a small sun during a dark scene

* Constant seat shuffling and aggressive snack rustling

This feature would remind people why watching movies at home is better. Conveniently, on Netflix.

What do you think of this idea?

Comments URL: https://news.ycombinator.com/item?id=46928337

Points: 2

# Comments: 0