MurphyA/hacker-news huggingface dataset:
Show HN: I turned my AI chat history into a portable cognitive fingerprint
by waterwitch | 2026-03-04 02:03:57+00:00
I run two businesses across too many AI tools and got tired of re-explaining myself every time I switched contexts, so I built something that reads your conversation exports from ChatGPT, Claude, Gemini, or Grok and generates a structured model of how you actually reason. Not a summary of what you've talked about. Ten dimensions (incl. decision speed, abstraction level, conflict response) scored with Bayesian updating and 90-day temporal decay so the profile continually updates.

The fingerprint is portable via MCP. I launched it to be compatible with Claude Pro (Claude Code or regular .ai interfaces) on first message and it adapts. Onboarding is about 2 minutes: you upload an export, watch it build in real time, and get a before/after demo using a real question pulled from your own history. One generic Claude response next to one shaped by your fingerprint.

I built it solo with AI-native dev tools in about 30 days. pgvector semantic search, OpenAI embeddings, Claude Haiku for cognitive extraction, Supabase/Postgres backend, OAuth 2.0 with PKCE for Claude.ai, REST API with OpenAPI spec for ChatGPT.

First 25 beta users are free, $10/mo after that.

Try it: https://trypaolo.com

Happy to answer questions about how it works under the hood, and always welcome feedback/bug reports etc.
by YmiYugy | 2026-03-04 02:04:02+00:00
This might be a "the grass is greener on the other side" situation because I do a lot more web than native dev, but in my experience native while just as quirky as web will usually give you low level APIs to work around design flaws.
On web it too often feels like you can either accept a slightly janky result or throw everything away and use canvas or webgl.
Here are some recent examples I stumbled across:
- try putting a semi transparent element on part of an image with rounded corners and you will observe unfixable anti-alias issues in those corners
- try animating together an input with the on screen keyboard
- try doing a JS driven animation in a real app (never the main thread feels hopeless and houdini animation worklets never materialized)

I don't think it's that native has nothing to offer. I think that developing (in case of desktop) for 3 different platforms all with own complication of what is native UI is a nightmare. macos has swiftui (incomplete), uikit and appkit, linux in practice gtk/qt, windows winui 3 (fundamentally broken) with WPF and WinForms still hanging around .
by davegoldblatt | 2026-03-04 02:04:26+00:00
That's basically what the data shows. His overall accuracy is a distraction. The specific technical calls are sharp. The "deep learning is hitting a wall" family of claims is where the evidence pushes back hardest, and the volume kept increasing even as contradictions piled up.

I wrote up the full pattern here: https://davesquickhits.substack.com/p/the-most-expensive-kin...
by thatwasunusual | 2026-03-04 02:04:53+00:00
Not related to this release, but their trade-in for old hardware is a joke to me. My 2019 MBP i9 2.4GHz w/64GB RAM and 2TB SSD is worth $200. It seems to me that they don't even want a trade-in; it makes much more sense to me to just keep the old MBP and use it as a dev server, home assistant, docker hub thing or something.
by nvlled | 2026-03-04 02:05:16+00:00
> half sarcasm, half real-talk.

If you could pause a bit from being awed by your own perceived insightfulness, you would think a just bit harder and realize that LLMs can generate hundreds of thousands of code that no human could every verify within a finite amount of time. Human-written software is human verifiable, AI-assisted human-written software is still human verifiable to some extent, but purely AI-written software can no longer be verified by humans.
by camerons03 | 2026-03-04 02:05:37+00:00
Piping a few hundred Substack posts through Claude and ChatGPT and slapping a "hybrid reconciliation layer" on top doesn't magically turn token prediction into empirical evidence.

Someone is so thin-skinned about a single guy writing a skeptical Substack that they spent their weekend building a dual-pipeline automation tool, scraping four years of his writing, instead of just building a product that actually disproves him. I’m not saying I agree with everything the man says, but until a human actually verifies these verdicts, this is just burnt tokens.
by logicprog | 2026-03-04 02:06:09+00:00
I think it's pretty clear that he hasn't kept up with the state of the art.

He has no idea what coding agents are capable of or how useful they are; he doesn't pay attention to any of the contributions to math or science that these models are making; he continually assists that because agents aren't ready to face customers in uncontrolled environment, they're completely useless even for employees and workers; he just last year posted an article complaining that LLMs don't use web search to find information (he asked the information about a friend), when almost all of them do now, even in their default interfaces; he still thinks hallucinations are a problem with any weight in things like mathematics and programming where it's very easy to verify the types of things hallucinations would cause a problem with; I think he still adheres to the stochastic parrot mindset even though that's not even the most relevant part of their training anymore.

Most importantly, although he seems to have made a single substack post making this argument, it doesn't seem to have really percolated through the rest of his thinking: that the cutting edge of LLMs right now, agents, are actually exactly the kind of neurosymbolic system, where neural networks provide an interface with the outside world and a creativity and problem-solving engine to provide the sort of fuzzy pattern matching and adaptability that is needed, while symbolic code-based systems ensure that guardrails are met, requirements are met, and for accurate information is provided and so on, that he wants. I think his objection might be that the problem is that the problem solving and reasoning engine at the core is still an LLM. But the thing is that you need the kind of pattern matching and flexibility and adaptability that you get from an LLM drive things, to have the end result be anything different than just an expert system with a slightly better natural language interface pasted on. And I think it's pretty clear at this point that expert systems are dead. They haven't done anything as remotely interesting or useful as what we're seeing LLMs do.

I think like another commenter says that his whole stick is pointing out obviously true basic features of LLMs like that they hallucinate or don't perfectly adhere to prompt guardrails, or that there's too much hype in the industry right now, and a lot of the companies suck in a vaguely standard big tech Silicon Valley way, and extrapolating to some broader point, which is that everyone should have listened to him and done what he said when he wrote that book back in the 90s (iirc).
by rvz | 2026-03-04 02:06:16+00:00
That's if you trust and believe that the LLMs themselves are 'correctly' scoring.

I wouldn't immediately even agree with an assessment made by these LLMs if I were Gary Marcus as that could immediately contradict any of the claims he even made and falling into the trustworthy trap. I'd remain skeptical as ever...

...because this is the worst of the red flags that ultimately supports Gary's argument that the LLM results may be untrustworthy:

All verdicts are LLM-scored, not human-verified.

People should check for themselves and draw their own conclusions.

> The crash hasn't come.

yet.
by nurettin | 2026-03-04 02:06:19+00:00
I just start llama.cpp serve with the gguf which creates an openai compatible endpoint.

The session so far is stored in a file like /tmp/s.json messages array. Claude reads that file, appends its response/query, sends it to the API and reads the response.

I simply wrapped this process in a python script and added tool calling as well. Tools run on the client side. If you have Claude, just paste this in :-)
by alex1138 | 2026-03-04 02:06:34+00:00
Whatsapp is one of the only instances I can think of in corporate acquisitions where the side being acquired lashes out at the acquiring side as much as this ("It's time. Delete Facebook")

You're talking about someone who changes privacy settings, who was told about gay people being automatically added to groups and posting on their walls so it outed them, being told about this and dismissing it. Or "graph search". He doesn't think people deserve any respect when it's not him?
by lambdasquirrel | 2026-03-04 02:06:44+00:00
Depends on how you look at it. In terms of overcoming fundamental limitations, I would argue it has indeed hit a wall. ChatGPT is how old, but LLMs still can't actually count?

But then, to your point, what does it matter, if they're still as useful as they are? Even at this stage, Claude Code makes Jira halfway bearable.

Of course, we have to consider the devil's advocate as well. Most CEOs don't seem to be reporting great ROI on their "AI" investments.
Show HN: 3D scenes stored in shareable URLs
by whothatcodeguy | 2026-03-04 02:06:48+00:00
You're looking at the demo project I've been using to build my browser-based 3d modeler and animator!

Recently I thought "wouldn't it be cool if you can send these projects around with just url data" and voila. Obviously only works with smaller projects, but still pretty fun.

If you make anything fun, send it in here.
by littlexsparkee | 2026-03-04 02:07:03+00:00
> It’s for survival not enjoyment. So it doesn’t make society better to have a diversity of food.

100% disagree, I love being able to enjoy and learn about different cuisines, it's an opportunity to connect with people I wouldn't have otherwise. In my metro area there's Ethiopian, Oaxacan, Ukrainian, Yemeni, etc. If it weren't for the variety, eating out would have no appeal to me.
by Garlef | 2026-03-04 02:07:03+00:00
I think this is a very interesting question.

But I think getting good AI features into a game requires a very very high engineering effort that is easily underestimated.

Current game engines are very good at creating large worlds with interactable assets: "Pull a lever and the door opens", "enter a building and a preprogrammed event starts", etc.

They are also good at physics simulations.

But ultimately, most of the content is hand-crafted/"hardcoded". And the systems in systemic games are very simple. (With a few exceptions like Dwarf Fortress).

In order to to - for example - let an AI introduce an ad-hoc questline, a lot would need to be formalized.

Imagine the following scenario: When I was playing Cyberpunk 2077 I hoped that I could roleplay as a corpo, slowly going up the ranks, backstabbing, etc. But the sheer amount of social and economic simulation this kind of openness would require is huge.

And it does not help that the work of writers is undervalued in the industry. And also that most creatives are in the anti-AI camp.
by _ache_ | 2026-03-04 02:07:22+00:00
I switch from ThinkPad to Framework because they couldn't send me a replacement keyboard. They want me to send the keyboard back to get a refund but I never receive it so... I never did get a refund.

Later, Framework send me a laptop in 1 week and later a replacement screen in less then a week. It's been 3 years ago now.
by shirro | 2026-03-04 02:07:43+00:00
In 30 years the only sort of novel idea anyone has come up with for making money out of tech that has got any real traction is harvesting people's data. Web search - data harvesting. Social media - data harvesting. LLM as a service - data harvesting. Is that because the same money people keep betting on the same sorts of ideas from the same sort of graduates from the same cultural background?

There was crypto coins but pyramid schemes have been around forever.

Why would anyone with a shred of awareness want to subscribe to any LLM service. Particularly a foreign one where that data could potentially end up in the hands of business competitors, political enemies, extortionists or others. That goes for all of the cloud really. Like WTF people. Why do you do this?
by hnfong | 2026-03-04 02:07:43+00:00
I don't understand what you mean by "prediction". Are you simply saying you're not using the AI tools out there and making a claim that they don't boost productivity at all?

Otherwise, even if the existing tools are overhyped (eg. instead of "exponential" gains, they are simply incrementally better), you're still gaining productivity by adopting them. And if they change your workflow, then "almost every part of our work looks different, and will continue to evolve" would be true.
by tombert | 2026-03-04 02:08:36+00:00
Not with Linux, typically. If you don't have drivers included in the kernel, it requires a lot of effort to get things working. I've done it many times, so now I will generally only buy laptops that have decent Linux support. [1]

I've had the laptop for about two years now and it still runs just as well as the day I bought it. I'm very happy with it.

[1] No I will not stick with Windows. Please feel free to read through my comment history to see why, but TL;DR I just don't like it.
by munch-o-man | 2026-03-04 02:09:37+00:00
author here: I've been running this in my homelab nomad/consul/vault cluster for a while now and it has been working great. My temporal job that does nightly backups of nomad/consul/vault/postgres now has an extra step to push to s3-orchestrator too and if it gets an error that no backend has available space it will delete the oldest backup of that type and then try again. Right now I have it doing "spread" routing between OCI and Cloudflare s3-compatible storage because they offer the best always-free s3 storage and I was already using cloudflare and running four nomad clients on oracle cloud connected to my cluster via wireguard (I would never give oracle a cent of my money but when they are offering 26gb of compute in always-free tier I'll take every bit of it thanks).

The coolest way to test this out is to just clone it and then run either:

make nomad-demo

make kubernetes-demo

that will spin up the docker-compose crap used for integration testing (two minio instances and a postgres) then start kubernetes via k3d or nomad via -dev mode, build the docker image, ingest it, run it, and print out a handy list of urls for different dashboards/metrics/ui/etc. The grafana dashboard in the repo is automatically ingested by grafana in the two "-demo" modes so you can literally run one command to run it and immediately play with the ui, see visualizations of the metrics, and start playing with it in a safe sandboxed environment.

For people that aren't just trying to get as much free storage as possible the storage and api/ingress/egress quotas can still be super useful in cost management since you can cap yourself.

The other cool use is if you needed data replicated across two different clouds for [reasons] this will do all that work for you if you set a replication factor and your application doesn't have to know anything about it...just point it at this instead of the actual s3 backend.

Also the ability to drain a backend could be super useful if you are trying to get off a certain cloud without taking downtime.

This is engineered to be highly durable...instead of failing it degrades and returns to healthy when conditions improve and the postgres is back...and it stops all writes when postgres is down since no usage would be tracked.

also, if you have an existing bucket that you want to bring under management by the s3-orchestrator it has sync functionality...the only thing it can't import is the monthly api-calls/ingress/egress from before the sync.

I'm open to all advice and comments. Pretty nervous sharing this.
by JojoFatsani | 2026-03-04 02:09:39+00:00
His defense minister is an absolute lunatic media personality in way over his head who really thinks war is a video game. They’re using pew pews to try and drum up patriotism, all it’s going to do is drive up our gas prices.

If there is a plan, it is to drive up gas prices to make fracked shale petroleum profitable again.
by vicchenai | 2026-03-04 02:09:39+00:00
The verification problem scales poorly with AI complexity. Current approaches rely on test suites, but AI-generated code tends to optimize for passing existing tests rather than correctness in the general case.

What's interesting is this might be the forcing function that finally brings formal verification into mainstream use. Tools like Lean and Coq have been technically impressive but adoption-starved. If unverified AI code is too risky to deploy in critical systems, organizations may have no choice but to invest in formal specs. AI writes the software, proof assistants verify it.

The irony: AI-generated code may be what makes formal methods economically viable.
Show HN: Mouse Polling Rate Test – A Chrome extension that measures your mouse
by zylics | 2026-03-04 02:10:07+00:00
I built a Chrome extension that measures your mouse polling rate directly from the browser toolbar.

Move your mouse over the popup for 8 seconds and it gives you:
- Average polling rate (Hz)
- Peak Hz and low 5% threshold
- Jitter percentage and stability score
- Performance grade (S/A/B/C)

No permissions required, no data collected, all processing happens locally in JS using performance.now() to measure mousemove event intervals.

Chrome Web Store: https://chromewebstore.google.com/detail/mouse-polling-rate-...

Full browser-based test also available at mousepollingratetest.com
by rayiner | 2026-03-04 02:10:51+00:00
> I think that developing (in case of desktop) for 3 different platforms all with own complication of what is native UI is a nightmare. macos has swiftui (incomplete), uikit and appkit, linux in practice gtk/qt, windows winui 3 (fundamentally broken) with WPF and WinForms still hanging around .

Wouldn’t it be a good use of AI to port the same app to several native platforms?
by watcher1776 | 2026-03-04 02:11:15+00:00
’ve spent a lot of time talking to freelancers who are excellent at their craft but overwhelmed by the plumbing of running a business. They’re juggling QuickBooks for invoicing, DocuSign for contracts, and manual trackers for lead research.

I built Solo to unify those operations into a single platform. It’s not just a CRM; it includes an AI rate advisor based on industry data, automated invoice delivery, and background agents that handle prospect research (Lead Scout).

The tech stack is focused on speed: it’s a PWA that works like a native app on mobile, integrated with Stripe for payments and Google Calendar for project sync. There's a three-tier model, including a free starter tier, because I want this to be accessible to someone just starting their first day of consulting.

I'm the sole founder building this and would love your feedback on the AI credits system and the utility of the business insights engine.
by jlongo78 | 2026-03-04 02:11:25+00:00
fair point on nesting - it can spiral fast. my workflow is basically flat groups by domain (infra, research, debug) with hard limits. 6-7 is actually a sweet spot, agree. beyond that youre not orchestrating, youre babysitting.

the session persistence angle is waht changes it tho - if context survives agent death, you can actually scale without losing your mind. keeps the mental overhead low even with more sessions running.
by bayarearefugee | 2026-03-04 02:11:37+00:00
Obviously I don't speak for Gary Marcus, but I'd say the chances of an AI financial crash aren't really directly linked to whether or not LLMs amount to anything or nothing.

From my perspective, it is basically guaranteed that LLMs will increasingly be seen as essential work tools for just about anyone doing knowledge work. So they won't amount to nothing.

But it is not at all guaranteed that the frontier model companies who are currently burning billions of dollars chasing that will capture significant percentages of that value.
by osigurdson | 2026-03-04 02:11:56+00:00
Hi all. I'll maybe try to see if I can get this added to the list of search tools above but here is a tool that allows you to search (text and semantic / tags) as well as chat. Some people found this useful in previous months so posting again.

Basic search: https://nthesis.ai/public/hn-who-is-hiring

Chat: Click the "Chat" button or use the following link (https://nthesis.ai/public/b28f0eb9-f5ac-4152-9a4c-152253d698...)
by aziaziazi | 2026-03-04 02:12:37+00:00
Young people take note too: build habits that support a healthy body and mind for the long run:

- Sleep well

- Stay active, spend time outside

- Maintain social connections

- Avoid excess (or all) sugar from non-whole food especially in drink

- Eat a LOT of vegetables: roots, leafs, fruits, seeds (<- nature's protein concentrate for future plants)

Nutrition matters, but it’s not the center of health. Sleep, movement, and relationships do more for long-term health than nutrient optimization ever will.

Not medical advice. Just a sleep-deprived person preaching what they fail to practice
Infected by GTA 5 Cheats: An Infostealer Infection Unmasked a North Korean Agent
by f0000x | 2026-03-04 02:12:40+00:00
We unmasked a highly skilled North Korean operative, part of a global billion-dollar fraud empire. Ironically their facilitator infected himself with an Infostealer when downloading GTA 5 cheats

By downloading a "Mod Menu" infected with the LummaC2 infostealer, the operator’s local facilitator inadvertently handed us the keys to their entire operation. Through the exfiltrated logs, we saw the operative's entire browsing history, every raw search query, and their active session cookies.

This research by Hudson Rock serves as a perfect technical compliment to the foundational work by our customer, Kudelski Security, and their "DPRK Fake IT Workers Fraud Playbook." While they mapped the recruitment networks, our telemetry provides the "smoking gun" look at their daily operations.

Read the full investigation here: https://www.infostealers.com/article/infected-by-gta-5-cheats-how-an-infostealer-infection-unmasked-a-north-korean-agent/

Notable Findings from the Operative's Machine:

Deepfake Orchestration: Active use of ElevenLabs and AI voice generators to pass live video interviews with Western HR departments.

Exchange Cloning: Procurement of "Steal-U" malicious smart contracts and clones of major exchange interfaces like Binance and OKX.

Behavioral Mimicry: A tactic called "IP Seasoning," where the operative mixed sophisticated Mandarin coding sessions with localized Indonesian searches for football and prayer times to trick fraud filters.

This discovery proves that identity is the new corporate perimeter. By analyzing cybercrime telemetry, we can pull back the curtain on even the most disciplined state-backed actors.