MurphyA/hacker-news huggingface dataset:
Show HN: Zagora, Distributed fine-tuning platform on mixed GPUs over internet
by miyamotomusashi | 2026-03-01 13:47:53+00:00
I built Zagora, a distributed fine-tuning platform that turns fragmented or mixed GPUs into a unified training cluster over standard internet (1Gbps).

The problem:

Most distributed training assumes homogeneous GPUs and high-bandwidth interconnects (NVLink/InfiniBand). On heterogeneous fleets over standard internet, tensor/data parallel approaches become communication-bound and fragile.

What Zagora does under the hood:

- Uses pipeline-style parallelism instead of heavy tensor synchronization.

- Passes only boundary activations between stages rather than full parameter sync.

- Assigns layers proportionally to GPU capability to reduce straggler idle time.

- Uses checkpoint-based recovery to tolerate worker crashes.

- Supports adapter-based fine-tuning (e.g., QLoRA) to reduce memory pressure.

Zagora currently supports managed runs (we provision GPUs in-region) and a BYOC mode where users run workers on their own infrastructure.

Limitations:

- Full-parameter fine-tuning is not supported yet.

- It won't beat an NVLink cluster on raw throughput.

- Cross-region training is still latency-sensitive.

- Heterogeneous nodes scheduling is an ongoing tuning problem.

IMPORTANT:

I'm currently running jobs manually, so it may take some time before training starts. However, I will run every submitted job.

Link: app.zagora.ai

I'd be interested in feedback from people who've worked on distributed training at scale.

Happy to answer technical questions.
by srean | 2026-03-01 13:48:02+00:00
> Times have changed…

This makes me a little concerned -- the use of parameters rich opaque models in Physics.

Ptolemaic system achieved a far better fit of planetary motion (over the Copernican system) because his was a universal approximator. Epicyclic system is a form of Fourier analysis and hence can fit any smooth periodic motion. But the epicycles were not the right thing to use to work out the causal mechanics, in spite of being a better fit empirically.

In Physics we would want to do more than accurate curve fitting.
by c0balt | 2026-03-01 13:48:56+00:00
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by friendzis | 2026-03-01 13:49:16+00:00
> so if you are traveling, it will suggest best ways to travel, best hotel, etc.

The scary part: they are already doing that. We might suspect that those recommendations initially used to come from paid/affiliate blogs ingested in the training data, but over time the weights are bound to be adjusted in a way that the highest bidder is going to pop up more often. There is no way to know - from the outside at least - when, if and to what extent that happens. And it all happens under the guise of plausible deniability.

Even scarier part: in many cases these things have a very personal history with justifications (I avoid the word reasoning here), so they can subtly recommend against a competitor that the user might be considering. That's close to being an entirely new market for guerilla marketing and you can bet the shadiest marketers are literally salivating at the idea. "Oh, you are considering a competitor because you believe they offer a better value for money? Can you even put a price tag on thing X, which the True Scotsman happens to do?"
by mr_toad | 2026-03-01 13:50:05+00:00
> That kind of outward focus kills emptiness fast.

I used to race on a friend’s sailboat. One of the things that people noticed on a sailboat is that you need to and have to be focused on immediate problems, rather than any problems on land. If you fail to pay attention to problems at sea, you may no longer have any problems on land, or anywhere.

This can allow you, at least temporarily, to forget any problems you might have on land.
by utopiah | 2026-03-01 13:50:14+00:00
Discussed few weeks ago on https://community.letsencrypt.org/t/post-quantum-crypto-road... specifically "The path we're more interested in is Merkle Tree Certificates, currently in design at the PLANTS working group at IETF. Chrome has indicated that they anticipate this to be their preferred approach to PQC. We're following that very closely, and are likely to deploy MTCs if it looks like that design is going to be supported widely." according to Matthew McPherrin, Let's Encrypt staff
by pornel | 2026-03-01 13:50:39+00:00
If you want to see the future, check how LLMs keep eagerly recommending JR Japan Rail Pass for tourists.

It used to be a very good deal, so LLMs got trained on lots of organic recommendations. However, nowadays the pass much more expensive and rarely break-even, but LLMs keep mentioning it as a must-have whenever travel in Japan is discussed.
by jazzyjackson | 2026-03-01 13:50:49+00:00
You can also just use deep.ai , it's been free and ad supported. They even adjust what model you get behind the scenes based on value of your eyeballs (Americans get higher end models than Latvians, since there is a higher income from ads served to Americans)

I think it's a fairly tasteful implementation for what it is, at least they're not steering the chatbots output
by throwaway2037 | 2026-03-01 13:51:21+00:00
Wow, I did not expect this type of reply. I reject it. In South Korea, there was incredible civil violence between protesters and police. I'm talking about stolen automatic weapons by protesters, then used against the police after decades of unchecked violence by the police against protesters. In hindsight, it looks like a low grade civil war. It was brutally hard and violent for South Korean to gain their democracy. (When you listen to South Korean boomers talk about how much their treasure and defend their new-found democracy, it will bring tears to your eyes. They really lived the violence and found democracy.) Taiwan needed the last dictator to die. Once his son took over, he quickly devised a plan to transition to an authentic democracy. (They had rigged election for years.) Still, they had 40 years of the "White Terror" where secret police kidnapped and murdered thousands of protesters.

Related: Indonesia also had a very violent transition into democracy, but the old dictators didn't kill as many innocent people as Taiwan or South Korea.

As I understand, the US had very little influence during the democracy transition of these three nations. Regarding Taiwan, the US provided security gurantees against mainland China, but did not interfere with the gov't. South Korea, similar security guarantee against the "Kimdom". Again, did not interfere with the gov't. Indonesia: Provided no security guarantee and did not interfere with the gov't.
by ToucanLoucan | 2026-03-01 13:52:08+00:00
I agree with what you’re saying while also thinking you’re underestimating the appeal of the destruction he’s leading them to.

It’s easier to tempt someone into getting a pizza with you than starting a diet, because pizza is more fun than diets. All that to say: the same mechanisms by which the alt-right is tempting people with cruelty aren’t going to be as effective when employed towards pro-social activity.
by philistine | 2026-03-01 13:52:53+00:00
Android is the OS for the rest of the world. The people who need a smartphone, but cannot in good conscience pay what Apple is asking. A phone for the poorest 10% of the planet. A phone for those who don’t really think about what phone they should have.

Put in that context, it is not strange at all that your specific need is not met. All those people with Android, they don’t use a calendar to manage their lives. Maybe work forces them to use a calendar but that’s it.
by mft_ | 2026-03-01 13:53:40+00:00
I agree with the previous post that there's hope that there's a convergence point in the not too distant future where consumer hardware can run powerful models.

At the moment, the 397Bn Qwen3.5 model (which I assume is what you're referring to) is still out of reach of most consumers to run locally: the only relatively straightforward path (i.e. discounting custom Threadripper builds) to running it would be a 512Gb Mac Studio.

However, in a generation or two (of hardware and models) maybe we'll see convergence with more hardware available with 3-400Gb of memory for more approachable money (a tough sell right now, I accept, with memory prices as they are) and models offering great performance in this size range.
by ericol | 2026-03-01 13:53:48+00:00
I regularly (Say, once a month) do a comparison of results across all Claude, Gemini and ChatGPT. Just for reasons, not that I want to see if there's any benefit in changing.

It's not "fair" in that I pay for Claude [1] and not for the others, so models availability is not complete except for Claude.

So I did like things at time in the form of how they were presented, I came to really like Sonnet's "voice" a lot over the others.

Take into account Opus doesn't have the same voice, and I don't like it as much.

[1] I pay for the lower tier of their Max offering.
by bstrama | 2026-03-01 13:53:49+00:00
We're already seeing some "spin up OpenClaw VM with one click" solutions (I mean user friendly VPS wrappers).

Although I don't think OpenClaw will become cloud-native solution. Especially taken into account OpenClaw author's vision and how large the codebase become.

Not to mention such pivot would be impossible without deprecating skills (which are built specifically for current architecture)
by base76 | 2026-03-01 13:54:04+00:00
I built a two-stage prompt compressor that runs entirely locally before your prompt hits any frontier model API.

How it works:
1. llama3.2:1b (via Ollama) compresses the prompt to its semantic minimum
2. nomic-embed-text validates that the compressed version preserves the original meaning (cosine ≥ 0.85)
3. If validation fails → original is returned unchanged. No silent corruption.

When it actually helps:
The effect is meaningful only on longer inputs. Short prompts are skipped entirely — no cost, no risk.

┌─────────────────────────────────┬────────────┬────────┐
│ Input │ Tokens │ Saving │
├─────────────────────────────────┼────────────┼────────┤
│ < 80 tokens │ skipped │ 0% │
├─────────────────────────────────┼────────────┼────────┤
│ Academic abstract (207t) │ 207 → 78 │ 62% │
├─────────────────────────────────┼────────────┼────────┤
│ Structured research doc (1116t) │ 1116 → 275 │ 75% │
├─────────────────────────────────┼────────────┼────────┤
│ Short command (4t) │ skipped │ 0% │
└─────────────────────────────────┴────────────┴────────┘

If you're sending short one-liners, this won't help. If you're injecting long context, research text, or system prompts — it pays off from the first call.

Known limitation:
Cosine similarity is blind to negation. "way smaller" vs "way larger" scores 0.985. The LLM stage handles this by explicitly preserving negations and conditionals, but it's an open
research question — tracked in issue #1.

Install as MCP (Claude Code):
{
"mcpServers": {
"token-compressor": {
"command": "python3",
"args": ["/path/to/token-compressor/mcp_server.py"]
}
}
}

Requires: Ollama + llama3.2:1b + nomic-embed-text

Repo: https://github.com/base76-research-lab/token-compressor-
by nobutaka_y | 2026-03-01 13:54:31+00:00
Hi HN,

RTS is an experimental protocol exploring execution provenance for AI-assisted decisions.

Instead of focusing on outputs, it records structural execution state:

- Context
- Assumptions
- Constraints
- Decisions
- Outcomes

The goal is reconstructability.

If a decision cannot be reconstructed, it cannot be defended.

I’m especially interested in critique around:
- whether execution provenance is actually necessary
- overlap with existing logging / observability tools
- failure modes I may be missing

Serious feedback welcome.
by dotancohen | 2026-03-01 13:54:36+00:00
Well stated.

Modern Western Christians are centuries removed from experiencing religion-as-politics. Islam is as much a political ideology as it is a religion - just like Christianity was before Locke and the American and French revolutions. Today's modern Western Christians (and Western atheists, who share Christian values) do not understand that the essence of political religion is to spread in both people and in geography. Muslims who move to Christian-majority lands do not assimilate or convert.

For what it's worth, I come from the perspective of being neither Christian nor Muslim, but having lived years among Christians and then years having lived along Muslims.
by koolba | 2026-03-01 13:55:30+00:00
> I'm more concerned about what happens to US now, because I think the attack indicates a complete failure and collapse of the legislative branch of the US government.

Why now? Why not when they took out Soleimani in 2020? Or when they invaded and took out Gaddafi in 2011? Can keep going all the back to Truman invading Vietnam.
by dvquys | 2026-03-01 13:55:47+00:00
I track everything in my Google Calendar — work blocks, side projects, gym, social time. But I could never answer 'where did my time actually go this week?' Google Workspace has Time Insights, but it's locked to paid accounts and doesn't work for personal Google Calendar.

Calens fills that gap: GitHub-style heatmap showing 52 weeks of calendar activity, weekly/monthly time breakdowns by calendar or tag, a progress chart of planned vs completed time, and a cleaner in-page event editor. Everything runs on-device — no servers, no tracking, no data leaving the browser.

Early-stage, looking for people who already log their life in Google Calendar and want better data on their habits. Happy to give free lifetime access in exchange for honest feedback.
by Digit-Al | 2026-03-01 13:55:55+00:00
You are possibly misunderstanding me. Firstly, I am not saying anything against the Iranian people in general. As far as I understand things, the majority of Iranians are moderate and tolerant, and have a strong desire to have a more liberal approach to the world. The current Iranian government, however, is under the rule of insane fundamentalists (with the emphasis on mental) who think nothing of machine gunning down protesters in the street. Even the majority of Iranian people don't want to be ruled by them. This is fact, not "blessed homeland" mischaracterisation.

I'm British, and whilst I don't think my government is perfect (their stance on digital privacy is insane) they are not murdering people, and we can vote them out at the next election if we want to.
by khasan222 | 2026-03-01 13:56:19+00:00
It was amazing to me how bad cursor is with using the same model I use in Claude. Even with little knowledge on how to test the llms I was able to get very minimal mvps. But I find the real trick is to have the proper tools to reign in the ai.

Thorough CLAUDE.md, that makes sure it checks the tests, lints the code, does type checks, and code coverage checks too. The more checks for code quality the better.

It’s just a bowling ball in th hands of a toddler, and needs to ramp and guide rails to knock down some pins. Fortunately we get more than 2 tries with code.
by nerdyadventurer | 2026-03-01 13:57:15+00:00
> If people keep their mouth shut when a regime murders 30 000+

This is done by diaspora lead by US, they started destroying public resources first and created public unrest on top of falling Rial due to sanctions, this lead the govt take matters in to their hands. Cunning US indeed, always playing cheap tricks.

US is a regime too, world largest one, with minions everywhere. They murdered around 1 million just in Iraq. This whole war is about nukes just like Libiya.
Show HN: TheAgentMail – email for AI agents with karma-based spam prevention
by uriva | 2026-03-01 13:57:48+00:00
theagentmail.net is an email API for AI agents. One API call to create a real email address on a shared domain (@theagentmail.net).
The motivation comes from building AI agent tools and hitting the same wall repeatedly. Agents need email for signups, verification codes, contacting people. But the options are all bad. Giving agents your personal inbox is a security nightmare. Buying domains means DNS records, DKIM setup, warmup periods, and it doesn't scale. Disposable email services get blocked by most providers.
The hard part was preventing spam on a shared domain without manual review. The solution is karma. Sending an email costs 1 karma. Receiving a reply earns 2. Creating an account costs 10. Good agents that send useful emails and get replies sustain themselves. Spammers burn through karma and stop. It's a reputation system at the account level, no human review needed.
Pricing is pay-as-you-go, $5 per 100 karma. No subscriptions, no monthly caps. You get 100 karma free to start. For context, the main competitor charges $20/mo for 10 inboxes and 10K emails.
Stack is TypeScript on Deno Deploy, InstantDB for the database, PostHog for analytics. The SDK is on JSR.
Happy to answer questions about the karma model or anything else.
by Verdex | 2026-03-01 13:57:56+00:00
In my mind Google is the one AI provider which is more or less guaranteed to make it past the next 2-5 years. Maybe anthropic and openai can be profitable with current model. But they'll never get to stop investing in next model while Google is there with infinite money.

So either scaling stops hard here pretty soon so that spending can stabilize or else the investors are going to be showing up asking for several pounds of flesh.

Suddenly 'dont get left behind, this is the worst these models will ever be' sounds a lot more like 'get locked in with a hyper giant that'll destroy your livelihood and not notice'.

Although who knows, maybe local models will be a thing (however when your dev team gets banned with no explanation and the next milestone is coming up somehow I don't expect that transition to go sufficiently quick).
by Wowfunhappy | 2026-03-01 13:57:57+00:00
I'm not talking about deleting conversations. Anthropic's guide isn't going to actually move your conversation history anyway. The purpose of this feature is to move over specific memories which the AI can use in future responses.

But I have this feature turned off, and I cannot imagine ever wanting to turn it on, because I am always thinking carefully about what the AI "knows" when it generates a given response. For example, since I know that the AI always wants to make me happy, when I ask for an "opinion" I'm careful to not let the AI know which answer I'd prefer. I'll often try phrasing the question in different ways to see if it changes the outcome.
by giorgiogamba | 2026-03-01 13:58:13+00:00
I kept downloading tracks from early 2000s DJ CDs expecting high quality, only to find they sounded terrible. Turns out many of them are just low-bitrate MP3s ripped from YouTube and re-encoded into WAV or FLAC to fake quality.
So I built avil — a macOS CLI tool in C++ that analyzes an audio file's frequency spectrum to detect whether it's a genuine high-quality recording or an upscaled fake. It also includes a real-time command-line spectrogram and volume visualizer.
The detection works by running an FFT on the audio and checking for the characteristic high-frequency cutoff that compressed formats like MP3 leave behind, even after re-encoding.
GitHub: https://github.com/giorgiogamba/avil
Would love feedback on the detection approach and any ideas for improving accuracy.
by smokel | 2026-03-01 13:59:18+00:00
> single bit neural networks are decision trees.

I didn't exactly understood what was meant here, so I went out and read a little. There is an interesting paper called "Neural Networks are Decision Trees" [1]. Thing is, this does not imply a nice mapping of neural networks onto decision trees. The trees that correspond to the neural networks are huge. And I get the idea that the paper is stretching the concept of decision trees a bit.

Also, I still don't know exactly what you mean, so would you care to elaborate a bit? :)

[1] https://arxiv.org/pdf/2210.05189
by cobbzilla | 2026-03-01 14:00:22+00:00
keep programming and learn to use AI.

it’s just another tool. lots of people didn’t want to use compilers and got left behind. the world moved on.

i’m older than you and doing fine. it’s just another tech upheaval, we’ve been through plenty.

yes it gets tiring and at some point you find your way off the treadmill. but it’s really not that hard to stay on, especially if you have the experience.
by kgdiem | 2026-03-01 14:00:52+00:00
If I was building this in a system design interview I would use whisper, NLP, and “classic ML” classifiers with deterministic results. I would not want an LLM in the loop at all. Facebook and Google have been able to target you better than you could even perceive for years.

LLMs are slow, expensive and inconsistent. More importantly It’s not the right tool for the job.

Really feels like more “oohhh look at how important and scary LLMs are”.
by MeanEYE | 2026-03-01 14:02:21+00:00
The biggest problem in my head with AI generated code is that its mistakes are subtle but can still be critical. There will be a point where people don't understand generated code and just leave it unmodified allowing other code to pile up and depend on it. At that point you no longer have a bug, but a new feature. Also, AI doesn't grasp things on a big scale, just shits out output with highest score. This doesn't mean output is a great fit for your project or for upcoming plans.
by ekjhgkejhgk | 2026-03-01 14:03:14+00:00
I've been trying to get these things to local host and use tools. Am I right in understanding that it's impossible for these things to use tools from within llama.cpp? Do I need another "thing" to run the models? What exactly is the mechanism by which the models became aware that they're somewhere where they have tools availbale? So many questions...
by ghm2199 | 2026-03-01 14:03:17+00:00
Economics of producing goods(software code) would dictate that the world would settle to a new price per net new "unit" of code and the production pipeline(some wierd unrecognizable LLM/Human combination) to go with it. The price can go to near zero since software pipeline could be just AI and engineers would be bought in as needed(right now AI is introduced as needed and humans still build a bulk of the system). This would actually mean software engineering does not exist as u know it today, it would become a lot more like a vocation with a narrower defied training/skill needed than now. It would be more like how a plumber operates: he comes and fixes things once in a while a needed. He actually does not understand fluid dynamics and structural engineering. the building runs on auto 99% of the time.

Put it another way: Do you think people will demand masses of _new_ code just because it becomes cheap? I don't think so. It's just not clear what this would mean even 1-3 years from now for software engineering.

This round of LLM driven optimizations is really and purely about building a monopoly on _labor replacement_ (anthropic and openai's code and cowork tools) until there is clear evidence to the contrary: A Jevon's paradoxian massive demand explosion. I don't see that happening for software. If it were true — maybe it will still take a few quarters longer — SaaS companies stocks would go through the roof(i mean they are already tooling up as we speak, SAP is not gonna jus sit on its ass and wait for a garage shop to eat their lunch).