frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Due to the AI memory crisis, Apple is bringing back the original Apple I

https://old.reddit.com/r/MacStudio/comments/1ugkygr/due_to_the_ai_memory_crisis_apple_is_bringing/
1•akirahittoxyz•23s ago•0 comments

The US lifts its block on Mythos 5

https://twitter.com/Techmeme/status/2070638481265905837
2•bobrenjc93•2m ago•0 comments

Ask HN: Any OSS models as good as GPT-4o-mini?

2•ra0x3•6m ago•0 comments

Mankato Unofficial Website

http://city-mankato.us/
2•limbicsystem•6m ago•0 comments

Why does kinetic energy increase quadratically, not linearly, with speed? (2011)

https://physics.stackexchange.com/questions/535/why-does-kinetic-energy-increase-quadratically-no...
2•ProxyTracer•7m ago•0 comments

I built a tiny free app to track money saved by skipping small purchases

https://skipd.coffee/
1•dariyam•10m ago•0 comments

Show HN: Imap2gmail – A self-contained mass-migrations orchestrator for Gmail

https://github.com/overflowy/imap2gmail
1•overflowy•11m ago•0 comments

Workbench: A TUI for parallel coding agents

https://github.com/erikqu/workbench-cli
2•erikqu•12m ago•1 comments

Assessing GPT-5.6 Sol Against Cybersecurity Benchmarks

https://www.irregular.com/research/assessing-gpt-5.6-sol
1•edanm•13m ago•0 comments

Show HN: Skillmaxxing – make every agent self-evolving

https://github.com/Bennyoooo/skillmaxxing
2•bennyjiang•13m ago•0 comments

AI in Mathematics Is Forcing Big Questions

https://spectrum.ieee.org/ai-in-mathematics
2•rbanffy•14m ago•0 comments

Inference Cards

https://cmart.blog/inference-cards/
1•zdw•15m ago•0 comments

Heavener: What happens when you can't afford EDR licenses

https://blog.otterpwn.com/projects/heavener
1•hexagr•17m ago•0 comments

GeoSpoof vs. Geoceptor – comparing two iOS location spoofing tools

https://geospoof.com/blog/geoceptor-vs-geospoof
1•sgro•21m ago•0 comments

Ask HN: Model access depends on citizenship. What should Non-US founders do?

1•recsv-heredoc•21m ago•1 comments

Structured Primary Keys

https://modern-sql.com/blog/2026-06/structured-primary-keys
1•birdculture•21m ago•0 comments

Tell Zillow: Fee-Simple vs. Leasehold Filter

2•HoldOnAMinute•25m ago•1 comments

How to Make the World's Best Black Shirt [video]

https://www.youtube.com/watch?v=u_BdsucFI9E
1•riknos314•30m ago•0 comments

Show HN: All-in-one memory for AI Agents

https://parcle.ai/second-brain
1•longtermop•30m ago•0 comments

iOS 27 Adds Mac-Like Recovery Mode for iPhone and iPad

https://www.macrumors.com/2026/06/22/ios-27-adds-mac-like-recovery-mode/
2•antfarm•31m ago•0 comments

Show HN: RAG Vector DB Cost Calculator

https://tools.superml.org/calculators/rag-vector-db-cost-calculator
1•bps1418•31m ago•0 comments

Academy Software Foundation Launches New Wayland for Artists Working Group

https://www.aswf.io/blog/academy-software-foundation-launches-new-wayland-for-artists-working-group/
2•agluszak•32m ago•0 comments

I've built an iOS app to spoof location, no PC needed

1•alienshello•38m ago•0 comments

Skill for generating cheatsheet PDF optimized for the reMarkable eink

https://github.com/Deca/remarkable-cheatsheet
1•Decag•40m ago•0 comments

How much compute does the world need?

https://www.ft.com/content/a5475746-510b-4b3f-8039-3fea1fb7c207
1•1vuio0pswjnm7•40m ago•0 comments

US strikes Iran in response to drone strike on commercial ship

https://www.aljazeera.com/news/2026/6/26/us-strikes-iran-in-response-to-drone-strike-on-commercia...
8•thisislife2•41m ago•5 comments

OpenTag: An open-source alternative to Claude in Slack

https://github.com/CopilotKit/OpenTag/
3•davidmckayv•41m ago•0 comments

Anthropic Moves Toward Deal with US to Lift Curbs on AI Models

https://www.bloomberg.com/news/articles/2026-06-26/anthropic-moves-toward-deal-with-us-to-lift-cu...
2•mfiguiere•51m ago•0 comments

The action is off-balance sheet

https://marginpoints.substack.com/p/the-action-is-off-balance-sheet
1•historian1066•53m ago•0 comments

The Long-Term Threat to the Memory Chip Boom Is Innovation

https://www.wsj.com/finance/the-long-term-threat-to-the-memory-chip-boom-is-innovation-bb289488
3•bookofjoe•55m ago•1 comments
Open in hackernews

The gap between open weights LLMs and closed source LLMs

https://blog.doubleword.ai/frontier-os-llm
63•kkm•1h ago

Comments

samat•1h ago
Article confuses open source models with open weights models.

Not the same thing.

It’s used right in the articles body, but title is misleading.

NitpickLawyer•1h ago
Literally no one cares. There are "full" open certified GMO free grass fed training data blah blah models. Apertus, Olmo, etc. No one cares. For all intents and purposes people use the term to describe a model that you can run locally and are allowed to modify and re-release. The rest is useless semantics. No one can "rEpRoDuCe" a model anyway.
throwuxiytayq•51m ago
No-one cares to quit social media or stop using Windows, but it’s a goal worthy of discussion all the same.

The name is bad, doesn’t even make any fucking sense and it gives open source a bad rep.

komadori•28m ago
I wouldn't say that no one cares, but obviously many fewer people care when the cost of "recompiling" a model from its open source training pipeline is so high. Also, if you only have the weights, you can still use it to generate training data for a new model (i.e. distillation) so it's inherently less locked down then closed source binaries were.
reinitctxoffset•57m ago
I was advocating for "available weight" as a value neutral term for a while.

I gave up. No one cares. And no one will ever tell the truth about the training anyways.

Substantial and growing freedom beats zero freedom ever again.

jackconsidine•1h ago
Achilles and the tortoise [0] is usually a fallacy. If the tortoise has a head start, then Achilles will never catch it because in the time it takes Achilles to reach the tortoise's location the tortoise has moved some degree further, ad infinitum. Obviously not real because Achilles will pass the tortoise -- I think a fallacy because the framing creates a fake asymptote (they will both pass the point where they're approaching a tie).

In this case it may actually apply though, no? Open models get better from closed model distillation?

[0] https://en.wikipedia.org/wiki/Zeno%27s_paradoxes

profsummergig•1h ago
IMHO, the biggest problem with the future of open weights models is that currently, open weights models are the result of philanthropy by some private org. (e.g. DeepSeek).

The spigot can be turned off at any time.

Until there's some sort of "community owned hardware", open weights models are always at risk of being discontinued.

Shitty-kitty•58m ago
It's just a smart business decision that allows their models to compete and gain market-share against much pricier private models. No philanthropy there.
NitpickLawyer•57m ago
Yeah, but the biggest plus for open models is that they can never be taken away. In other words, whatever capabilities they reach (even if there will never be another model), those stay forever. That can't be said for API-based models where a provider can sunset models whenever they feel like (i.e. gpt5-mini will soon be gone, and replaced by a more expensive 5.4-mini, same for goog, etc).

And there will always be incentivised parties that release models. Nvda for one has every incentive to keep the nemotron line going, as they're directly profiting from people running this. And the models aren't really far from open SotA anyway.

Goog will probably continue to release the small models, since they'll use them for browser stuff anyway, and know that they'll leak. So for them it's a win-win to release the small models and gain some dev market share.

And the chinese labs also have incentives to keep releasing models, and will likely continue to get gov support to do so (yay commercial wars between nations).

felooboolooomba•37m ago
> they can never be taken away

Your right to 3d print whatever you want is about to be taken away (in California).

What software you can run on your computer can already be restricted.

Absolutely everything can be taken away. The simplest way to remove open models is probably to declare them a tool that terrorists could use. Crazy? Yes, the world is totally crazy these days.

jacobgold•1h ago
It would be interesting to know how much of a boost the closed models and companies are giving the open models.

If the closed models stop improving will the progress of open models slow?

amluto•27m ago
> It would be interesting to know how much of the "distillation" boost is helping the open weight models keep up.

Some people in China surely know.

> Like if the closed models stop improving will all the closed models also stop improving?

Seems extremely unlikely, unless the models all hit some kind of wall soon. The Chinese companies may be behind the US in compute capacity, but they have excellent researchers [0] who are probably approximately as good as their US counterparts at the kind of problem generation and RL that is currently working so well.

I would be very surprised, though, if the models cannot continue to be improved rapidly in any area that allows a tight feedback loop like programming, at least up to the point where we puny humans lose the ability to define objective functions.

(And, conversely, I don’t expect magic in fields where the feedback is slow or expensive. A model is not about to reliably invent a wonderful medicine for the same reason that a large and extremely competent pharma company cannot: the evaluation process is extremely slow and it’s so expensive that the kind of utterly enormous corpus that is driving the current progress in coding is simply not available. Running RL on m iterations of n medication-development trajectories each is going to cost n*m times $10-100 million and take m years if it’s even possible at all.)

[0] The US advantage in this space will likely decline, since the brain drain from the rest of the world via the US university system to US labs is drying up.

amunozo•25m ago
Why are we assuming only American labs can innovate? DeepSeek already innovated a lot in efficiency, for example.
justindotdev•46m ago
at first glance, these graphs are confusing
nsingh2•11m ago
Yea these plots are too noisy and dense. Especially that second one, lines all over the place.
gehsty•46m ago
Interesting to consider this inline with recent us export bans, could the US be squandering its lead by giving the open source, largely Chinese labs catch up (in terms of model quality available to masses), will US labs be able to maintain the lead without users being able to use their latest models?
llmslave•40m ago
The gap is huge and im tired of reading these articles constantly
JumpCrisscross•25m ago
Now let’s look at the economics of buying versus renting. I’ve seen a lot of attention given to hardware capital costs. But a comment the other day got me thinking about power costs, too—at what performance differential do these factors intersect to make on-prem economically competitive with datacenters for businesses?
cj•24m ago
At what point will model advancement start to have minimal to no value for the majority of use cases?

Or is the idea that more advanced models will unlock more use cases?

dabinat•4m ago
I believe the open model party will eventually end. Perhaps because companies realize it’s too much of a commercial advantage, countries don’t want to give other countries commercial or military help, or maybe even an outright ban after someone uses an open model to guide them through how to make a bomb.
_pdp_•4m ago
Frankly it does not matter if there is gap because for most practical use-cases the end user can barely perceive the difference in intelligence.

On paper frontier models will be ahead of the curve but I don't think hardly anyone will be able to tell if a piece of work, say a landing page, is created with Fable or GLM and that is the point. The perceptible intelligence will reach a point beyond which it is no longer considered, except for some narrow use-case.

redox99•29m ago
That only affects people in California. Whereas Fable being shut down affects people all over the world.
jfim•11m ago
True, but the capabilities and knowledge of that model are also frozen in time, so the value of that model declines over time.

A model that writes code without knowledge of any language or library changes for half a decade is less useful. A 2021 era chatgpt would be quite quaint in 2026.

Right now the Chinese labs might have incentives to release their models for free, and maybe Google is happy to release open weights today, but I'm sure there are already bean counters at Google salivating at the idea of having Gemini in Chrome as part of a Google AI monthly subscription just like YouTube premium and other Google subscriptions.

UncleOxidant•10m ago
> Nvda for one has every incentive to keep the nemotron line going

They're releases so far have been kind of lackluster compared to Qwen and other Chinese models. My suspicion is that Nvidia won't be releasing models that appear to compete with frontier models because that would upset their big customers.

fridder•51m ago
We need a SETI@Home but for model training
kamranjon•45m ago
Have been thinking about this a lot lately.
0x3f•37m ago
Consumer hardware over the internet is not really suitable for this, AFAIK.
Azantys•27m ago
I think model training is pretty hard to do efficiently on a vastly distributed network. If the model cant fit into the VRAM of the node your performance becomes so bad its useless, so a distributed model could only be properly trained if the size of the model doesnt exceed the majority of the nodes VRAM sizes. Maybe there is a different way of doing training but this would be the only way I can see. And it would still be much worse than just using a big datacenter where everything is fully interconnected. BOINC projects work great because its usually just a lot of small compute and memory required so every old desktop and laptop can contribute. Training a model which can compete and is not tiny requires neither low compute or low memory amount. BOINC tasks take minutes usually or sometimes hours but not weeks or months like training a model from scratch. But something like 7B or lower could maybe be trained like this. Im not sure but I think someone is already working on something like this but I dont remember the name of the project.
recursive•46m ago
This seems backwards. Access to Fable can be removed. I don't see how an open weight model can ever be put back into the bag though.
Smaug123•35m ago
The model itself, sure; the comment is about the production of more advanced models (to keep open weights near the frontier).
ForHackernews•35m ago
It's not pure philanthropy: https://gwern.net/complement
notnullorvoid•33m ago
> Until there's some sort of "community owned hardware"

Or until some bright people figure out drastically more efficient means of training.

UncleOxidant•12m ago
> The spigot can be turned off at any time.

True. And it's possible that this has already happened at Alibaba Qwen - at least for the smaller models that people had a chance of running at home (122B and smaller).