MurphyA/hacker-news huggingface dataset:
by Tade0 | 2025-11-04 16:59:44+00:00
The whole point of this experiment was to show that if we don't know whether something is a mind, we shouldn't assume it is and that our intuition in this regard is weak.

I know I am a mind inside a body, but I'm not sure about anyone else. The easiest explanation is that most of the people are like that as well, considering we're the same species and I'm not special. You'll have to take my word on that, as my only proof for this is that I refuse to be seen as anything else.

In any case LLMs most likely are not minds due to the simple fact that most of their internal state is static. What looks like thoughtful replies is just the statistically most likely combination of words looking like language based on a function with a huge number of parameters. There's no way for this construct to grow as well as to wither - something we know minds definitely do. All they know is a sequence of symbols they've received and how that maps to an output. It cannot develop itself in any way and is taught using a wholly separate process.
by walterbell | 2025-11-04 17:00:11+00:00
https://www.reuters.com/world/china/chip-crunch-how-ai-boom-...

> spot prices of DRAM, used in various applications, nearly tripled in September from a year earlier.. improving profitability of non-HBM chips has helped fuel memory chipmakers' share price rally this year, with Samsung's stock up more than 80%, while SK Hynix and Micron shares have soared 170% and 140% respectively... industry is going through a classic shortage that usually lasts a year or two, and TechInsights is forecasting a chip industry downturn in 2027.

Micron has US memory semiconductor fab capacity coming online in 2027 through 2040s, based on $150B new construction.

Are some HBM chips idle due to lack of electrical power? https://www.datacenterdynamics.com/en/news/microsoft-has-ai-...

> Microsoft CEO Satya Nadella has said the company has AI GPUs sitting idle because it doesn’t have enough power to install them.

If the PC supply chain will be impacted by memory shortages until 2027, could Windows 10 security support be extended for 24 months to extend the life of millions of business PCs that cannot run Windows 11?
by observationist | 2025-11-04 17:00:35+00:00
A site can be a billboard for a product or service, or provide a social hub, without participating in the surveillance adtech industry. There are plenty of hobby forums, like those for craft brewing, which get supported by brewery suppliers, for example. There are luthier communities which get supported by toolmakers and professionals, and so on. The implicit community networking, reviews by community members, and other interactions reward quality and honesty, and penalize the shady shit.

It's just not scalable into the exploitative cash cows that VCs drool over.
by virgil_disgr4ce | 2025-11-04 17:01:04+00:00
Location: NY, NY Remote: Yes, open to hybrid Willing to relocate: No Technologies: TypeScript, JavaScript, HTML/CSS, Python, C, C++, C#, Go, Scheme, Artificial Intelligence, Generative AI, React.js, Next.js, TypeScript, TailwindCSS, HTML, Framer Motion, Radix, PostgreSQL, Playwright, Figma, React Flow, React Native, XBee, ZigBee, Bluetooth, CSS, styled-components, Expo, MongoDB, Node.js, Python, IoT, Angular.js, REST API, Algorithms, JavaScript, D3.js Résumé/CV: https://www.tedbot.com/developer Email: t, the number 3, db, the number 0, t @ gmail
by pgguru | 2025-11-04 17:01:26+00:00
Hi, one of the developers here. You define credentials that can access the S3 buckets and use those as DuckDB secrets, usually in an init script for pgduck_server. (You can see some examples of this in the testing framework.)

I'll see if we can improve the docs or highlight that part better, if it is already documented—we did move some things around prior to release.
by WorldMaker | 2025-11-04 17:01:52+00:00
Zod [0] isn't too bad for runtime types and runtime type evaluation. It even has JSON schema output now [1], though most of my API uses of Zod have been with Hono's "RPC" [2] which does a bunch of type magic to build a type-safe API client from your API types directly (in projects where you can share front-end and back-end types).

[0]: https://zod.dev/

[1]: https://zod.dev/json-schema

[2]: https://hono.dev/docs/guides/rpc
by layer8 | 2025-11-04 17:02:03+00:00
For some people, “pleasantries” are mentally taxing, and while you can force yourself to feign interest in someone’s random weekend activity, you can’t force yourself to actually find it interesting if in reality you find it dull. The “chore” isn’t that it consumes time, it’s that not everyone finds it a pleasant thing to do with any random person.
by 9rx | 2025-11-04 17:02:09+00:00
> I suspect they would rather face shortages then satisfy market demand.

Doubtful. A shortage is normally a scary prospect for a vendor. It means that buyers want to pay more, but something is getting in the way of the seller accepting that higher price. Satisfying market demand is the only way to maximize profitability.

Why do you think companies would prefer to make less profit here?
by pseudalopex | 2025-11-04 17:02:11+00:00
I want country codes not flags. And check marks do not require emoji.

Every emoji I saw in a terminal or Git commit message was worse than alternatives. This included emoji intended for information not fun. Color made them distracting when the wanted information was anything else. A monochrome font could not solve this because most emoji are too complex to display clearly at normal text sizes without color. They were cumbersome to grep. (Uncommon Unicode characters would have this problem also.) Many had unclear meanings.

Use emoji in your CLIs if you desire. But make them optional. Opt in ideally.
by Flashtoo | 2025-11-04 17:02:12+00:00
The notion that the brain uses less energy than an incandescent lightbulb and can store less data than YouTube does not mean we have had the compute and data needed to make AGI "for a very long time".

The human brain is not a 20-watt computer ("100 watts per day" is not right) that learns from scratch on 2 petabytes of data. State manipulations performed in the brain can be more efficient than what we do in silicon. More importantly, its internal workings are the result of billions of years of evolution, and continue to change over the course of our lives. The learning a human does over its lifetime is assisted greatly by the reality of the physical body and the ability to interact with the real world to the extent that our body allows. Even then, we do not learn from scratch. We go through a curriculum that has been refined over millennia, building on knowledge and skills that were cultivated by our ancestors.

An upper bound of compute needed to develop AGI that we can take from the human brain is not 20 watts and 2 petabytes of data, it is 4 billion years of evolution in a big and complex environment at molecular-level fidelity. Finding a tighter upper bound is left as an exercise for the reader.
by FloorEgg | 2025-11-04 17:03:07+00:00
LLMs embody the free-energy principle computationally. They maintain an internal generative model of language and continually minimize “surprise”, the difference between predicted and actual tokens, during both training and infeence. In Friston’s terms, their parameters encode beliefs about the causes of linguistic input; forward passes generate predictions, and backpropagation adjusts internal states to reduce prediction error, just as perception updates beliefs to minimize free energy. During inference, autoregressive generation can be viewed as active inference: each new token selection aims to bring predicted sensory input (the next word) into alignment with the model’s expectations. In a broader sense, LLMs exemplify how a self-organizing system stabilizes itself in a high-dimensional environment by constantly reducing uncertainty about its inputs, a synthetic analogue of biological systems minimizing free energy to preserve their structural and informational coherence.
by doctorpangloss | 2025-11-04 17:03:37+00:00
sometimes hacker news links are about doing free work for microsoft, like finding bugs in Windows and Office

sometimes hacker news links are about doing free work for microsoft, like rigorously defining AGI, because that triggers the OpenAI license-to-stock conversion now

maybe this is why microsoft makes so much fucking money. Even the New Yorker cannot stop fucking doing work for them for free.
by notepad0x90 | 2025-11-04 17:03:47+00:00
> That's the learning-part I was talking about. Which is mainly supported by humans at the moment, which why I called it proto-intelligence.

Maybe it's just semantics, but I don't think LLMs even come close to a fruit fly's intelligence. Why can't we recognize and accept them for what they are, really powerful classifiers of data.

> Commercial AIs like ChatGPT do have the ability to call programs and integrate the result in their processing. Those AIs are not really just LLMs. The results are still rough and poor, but the concept is there and growing.

Yeah RAG and all of that, but those programs use deterministic algorithms. Now, if LLMs generated programs they call on as tools, that would be much more like the proto-intelligence you're talking about.

Semantics are boring, but it's important that we're not content or celebrate early by calling it what it isn't.
Show HN: Tangent – Open‑source stream processor with native‑speed WASM plugins
by PublicEnemy111 | 2025-11-04 17:03:48+00:00
We built Tangent, a stream-processing engine with WASM at its core. In our benchmarks, end-to-end ingestion and transformations perform at native speed, with some workloads even running faster.

Hi HN, we’d like to share our open-source stream processing engine written in Rust, where WASM transformations/enrichments are first-class.

There have been several earlier attempts to bring WebAssembly into the streaming world (Arroyo, Vector, etc.) that faced toolchain or runtime-maturity issues. We felt now is the right time: thanks to recent performance improvements by the wasmtime team, we see ~230 MiB/s throughput ingesting from a socket and passing to a Go-WASM transform[1] on a 16 core machine. The same workload runs with slightly lower throughput in native Go.

WASM is not just a novel technology we wanted to play with; we have two core motivations:

1. We’ve been collaborating with the OCSF team, and discovered that sharing vendor->OCSF mappers is a big hurdle (vendor schema drift + OCSF updates). With WASM, we don’t need to agree on a DSL before we can share transformations.

2. LLMs are much better at writing code (Go, Python, etc.) than domain-specific languages. We wanted a stream processor where you can write plugins, test, and benchmark easily and locally. With Tangent we rewrote all the mappers in the OCSF examples repo in about an hour[2]

We’d love to hear your feedback!

[1] https://github.com/telophasehq/tangent/blob/main/examples/go...

[2] https://github.com/ocsf/examples
by tavavex | 2025-11-04 17:03:50+00:00
> So it is clearly a problem.

I didn't say there weren't rapists who were strangling their partners for their own pleasure. The "problem" you're describing is already illegal. I don't think there's a first-world country where you're allowed to nonconsensually choke someone. And "it was just my kink" isn't a good defense at all - just because it's used doesn't mean anything, the defense's whole point is to come up with the most tame interpretation possible for the crime, no matter how ridiculous.

The moral panic part is when the UK government decides that blanket banning everyone from doing it consensually is going to change anything about unrelated rapists who were already fine with breaking the law. And especially the fact that they think that the effects of this blanket ban are going to be large enough for it to be worth to criminalize consenting adults over.

And then then there's the choking porn part, where they seemingly have deduced that it was brainwashing men in such dangerous capacities that it's now worthwhile to brand someone a criminal for life if they dared to have that cognitohazard inscribed on their hard drive. It's okay, you may not have hurt anyone, you may have had a happy, consensual relationship, but we must simply punish you, don't you see. It's for the greater good, for we are fighting something which was already illegal.

Statistics don't matter here. When they come for the next "immoral" kink, they'll conjure up more statistics and conjecture to make it seem less insane. But statistics aren't what caused this. There is no choking porn crisis. They just wanted to go after it, and this was the best tool available.
by pgguru | 2025-11-04 17:04:54+00:00
What has been pointed out from the README; also:

- Separation of concerns, since with a single external process we can share object store caches without complicated locking dances between multiple processes. - Memory limits are easier to reason about with a single external process. - Postgres backends end up being more robust, as you can restart the pgduck_server process separately.
by yawaramin | 2025-11-04 17:05:07+00:00
You don't need an external library to print in OCaml. You just need it if you want to automate deriving a conversion function. OCaml erases types at compile time so the runtime doesn't know anything about types or how to print them. It's just how it works.

Re: better syntax frontend for OCaml. People really tried to, for many years. But it didn't work, there was never much adoption. And the funny thing was that as soon as people got comfortable with it they switched to the standard OCaml syntax because they understood it better and started preferring it. Ironic!
by Philadelphia | 2025-11-04 17:05:13+00:00
People have a very poor conception of what is easy to find on the internet. The author is impressed by the story about Chat GPT telling his friend how to enable the sprinkler system for his kids. But I decided to try just googling it — “how do i start up a children's park sprinkler system that is shut off” — and got a Youtube video that shows the same thing, plus a lot of posts with step by step directions. No AI needed. Certainly no evidence of advanced thinking.
by pfannkuchen | 2025-11-04 17:05:16+00:00
Did I say it was?

Christian morality includes “don’t be selfish” as a high ranking rule.

Being selfish is against the religion, therefore selfish Christians are not implementing Christianity properly, or in other words they are being “bad Christians”.

I don’t think of morality as one thing, I’m not claiming Christians or well functioning Christians are “more moral” because that is a nonsensical framing. It would be like saying that frogs are “more animal” than goats. No, they are just different animals.
by fragmede | 2025-11-04 17:05:49+00:00
This won't work for the sewing itself, but while Siri itself is still a hot mess, it can launch shortcuts into other apps. Aka can ask "Siri captains log" and I've configured my phone to launch voice recording so I can journal via voice. That isn't the same as actually sewing, but organizing my thoughts has value, especially if it's during time I otherwise would have burned.
by zahlman | 2025-11-04 17:06:23+00:00
I would have thought that the point is that you're supposed to be there continuously for some considerable duration (and having worked through other processes of legal immigration) before applying for citizenship.

So the idea of trying to figure out exactly which day five years in the past you have to mention seems odd to me. If there's really no care being paid to the intervening time... well if you're trying to exploit a loophole like that I think I'd prefer that it's difficult... ?
by mathgradthrow | 2025-11-04 17:06:41+00:00
What a terrible article. Can anyone who is not a mathematician tell me one thing they learned from this?

The naked term "manifold" in its modern usage, refers to a topological manifold, loosely a locally euclidean hausdorff topological space, which has no geometry intrinsic to it at all. The hyperbolic plane and the euclidean plane are different geometries you can put on the same topological manifold, and even does not depend on the smooth structure. In order to add a geometry to such a thing, you must actually add a geometry to it, and there are many inequivalent ways to do this systematically, none of which work for all topological manifolds.
by mapontosevenths | 2025-11-04 17:07:10+00:00
Is it untrue? You failed to address my point.

Children are being left to die. SOMETHING is more important than that to the proponents of these policies. What is it? If it's lower taxes... they aren't achieving that goal. Taxes are only decreasing for the top 0.1% of the population and tip earners.

If it's to lower the national debt that also isn't working. The national debt has increased at record rates.

Is there some other goal I'm not aware of? Why is it so important that these children not be fed?
by StillBored | 2025-11-04 17:07:13+00:00
While thats a sweet upgrade for people with an older desktop that can support a motherboard swap, its worthwhile to point out the ram is probably insufficient.

RAM usage for a lot of workloads scales with core/thread count, and my general rule of thumb is that 1G/thread is not enough, and 2G/thread will mostly work, and 4G/thread is probably too much, but your disk cache will be happy. Also, the same applies to VMs, so if your hosting a VM and give it 16 threads, you probably want at least 16G for the VM. The 4G/thread then starts to look pretty reasonable.

Just building a lot of opensource projects with `make -j32` your going to be swapping if you only have 1G/thread. This rule then becomes super noticeable when your on a machine with 512G of ram, and 300+ threads, because your builds will OOM.
by bigstrat2003 | 2025-11-04 17:07:29+00:00
Nano is by far the best terminal editor imo. The only situation where I'm using a terminal editor is when I'm ssh'ed into a server, and I need to quick edit a file (for serious code writing a GUI editor is far more capable). Nano is ideal for that use case: you get in, it tells you what all the relevant keybinds are right on the screen, and you get out without any fuss.
by klelatti | 2025-11-04 17:07:39+00:00
The same guys who couldn’t develop a sleep tracker?

https://open.substack.com/pub/foxchapelresearch/p/i-think-su...

Edit please note the comments in the linked post by SemiAnalysis below who have lots of reports that the tool is legit but who are skeptical. They have clearly progressed somewhat since the tracker project!
by joeyism | 2025-11-04 17:07:39+00:00
Adora AI [https://adora-ai.com] | Senior Fullstack Engineers (Frontend & Backend focus) | Seattle ONSITE Full-time | $170k-$200k

We're partnering with major brands (Alaska Airlines, Brooks Running) to solve marketing challenges with AI. Hit initial PMF, scaling 3x in 2026. Join our 16-person team (5 eng/product) as founding engineering team member.

Stack: Python, React, TypeScript, MySQL, AWS, BigQuery

Day 1: Ship code (we'll point you at something good)

Two roles:

- Backend-focused: Own platform architecture connecting AI/ML pipelines to user features. Design systems that scale 10x. Deep Python, integrations, robust APIs.

- Frontend-focused: Build interfaces that delight marketers. Strong React/TypeScript, jump into backend when needed.

Looking for: AI-native developers (Cursor user?), comfortable with ambiguity, ship iteratively, customer-focused over technical purity. Startup experience preferred.

Culture: Close-knit Seattle team, shared workspace, low ego/high ownership, direct customer collaboration.

Apply:

- https://jobs.lever.co/adora/eef89ae9-11fe-425d-bcf7-7aef53de... (Backend-focused)

- https://jobs.lever.co/adora/1dc43e89-aa80-497e-9da3-5ca7a521... (Frontend-focused)
Launch HN: Plexe (YC X25) – Build production-grade ML models from prompts
by vaibhavdubey97 | 2025-11-04 17:07:47+00:00
Hey HN! We're Vaibhav and Marcello, founders of Plexe (https://www.plexe.ai). We create production-ready ML models from natural language descriptions. Tell Plexe what ML problem you want to solve, point it at your data, and it handles the entire pipeline from feature engineering to deployment.

Here’s a walkthrough: https://www.youtube.com/watch?v=TbOfx6UPuX4.

ML teams waste too much time on generic heavy lifting. Every project follows the same pattern: 20% understanding objectives, 60% wrangling data and engineering features, 20% experimenting with models. Most of this is formulaic but burns months of engineering time. Throwing LLMs at it isn't the answer as that just trades engineering time for compute costs and worse accuracy. Plexe automates this repetitive 80%, so your team can work faster on what actually has value.

You describe your problem in plain English ("fraud detection model for transactions" or "product embedding model for search"), connect your data (Postgres, Snowflake, S3, direct upload, etc), and then Plexe: - Analyzes data and engineers features automatically - Runs experiments across multiple architectures (logistic regression to neural nets) - Generates comprehensive evaluation reports with error analysis, robustness testing, and prioritized recommendations to provide actionable guidance - Deploys the best model with monitoring and automatic retraining

We did a Show HN for our open-source library five months ago (https://news.ycombinator.com/item?id=43906346). Since then, we've launched our commercial platform with interactive refinement, production-grade model evaluations, retraining pipeline, data connectors, analytics dashboards, and deployment for online and batch inference.

We use a multi-agent architecture where specialized agents handle different pipeline stages. Each agent focuses on its domain: data analysis, feature engineering, model selection, deployment, and so on. The platform tracks all experiments and generates exportable Python code.

Our open-source core (https://github.com/plexe-ai/plexe, Apache 2.0) remains free for local development. For the paid product, our pricing is usage-based, with a minimum top up of $10. Enterprises can self-host the entire platform. You can sign up on https://console.plexe.ai. Use promo code `LAUNCHDAY20` to get $20 to try out the platform.

We’d love to hear your thoughts on the problem and feedback on the platform!
by michael_foundry | 2025-11-04 17:07:49+00:00
Mithril [https://mithril.ai/] | ONSITE in Palo Alto -or- San Francisco, CA (SF Bay Area) | Full Time

We’re building Mithril to be the cloud compute platform AI developers actually want—no more battling procurement, limited quotas, or clunky tooling. Our platform gives ML engineers frictionless access to high-performance GPUs, clean APIs, and modern infra primitives to train, fine-tune, and serve state-of-the-art models. Backed by Sequoia, Lightspeed, and founders of Databricks, Google Brain, and Scale.

We’re hiring:

>> General Software (SWE) / Infrastructure Engineers << Build our batch + streaming workload engine for ML. Think: GPU scheduling, fault-tolerant execution, rich job DAGs. 0→1 ownership. Apply here: https://job-boards.greenhouse.io/mithril/jobs/4199826007

>> SRE, Supply (Site Reliability Engineer) << Manage GPU provisioning, spot bidding, and node pool health across clouds and on-prem. Work on the systems behind our global GPU fleet. Apply here: https://job-boards.greenhouse.io/mithril/jobs/4651793007

>> Founding Product Manager << Define the roadmap for the most advanced ML infra users. Apply here: https://job-boards.greenhouse.io/mithril/jobs/4199830007

>> General Application - Exceptional Talent << If you are an experienced, high-impact individual who believes you can help us achieve our most ambitious goals, please use this general posting to introduce yourself: https://job-boards.greenhouse.io/mithril/jobs/4965590007

Looking for compute? We support distributed deep learning workloads, including long-running batch jobs, streaming inference, and GPU autoscaling for LLM training and fine-tuning. https://mithril.ai/contact-sales

discovery tags: gpu, kubernetes, hpc, terraform, helm, distributed, ml, training, inference, llm, deep learning, fine tuning, customer, product, api, on-demand, infrastructure, elastic, scalable, cloud, platform