MurphyA/hacker-news huggingface dataset:
by alxpopa | 2025-11-04 01:20:49+00:00
Poesis (https://poesis.ai), Founding Engineers (ML, Quant, Head of Eng), On-Site (Palo Alto, CA), Full Time

Poesis is the AI-native investment manager pioneering a new foundation model for investing in U.S. equities. We’re building AI systems to predict market movements and outperform legacy managers. This is frontier research with immediate real-world validation, your work directly shapes investment decisions and portfolio performance.

We’re hiring founding technical roles to build the first generation of our trading and ML systems:

Head of Engineering: own architecture, pipelines, and productization of research; define the technical backbone of the fund.

Founding ML Engineer: build end-to-end ML systems for data ingestion, training, backtesting, and signal generation.

Founding Quant Developer: turn research ideas into production-grade code, working closely with leadership on real trading systems.

We’re a small, deeply technical team based near Stanford, working several days a week on-site in Palo Alto. Relocation support available.

If you’re excited by the intersection of AI, finance, and first-principles design, we’d love to meet you.

Apply here: https://jobs.ashbyhq.com/poesis?utm_source=7B1zo0bVXD
by snypher | 2025-11-04 01:21:24+00:00
Reuters—OHCHR: weaponisation of food as potential war crime (June 24, 2025).

Reuters—UN adds IDF to list of grave violators against children (June 7, 2024).

Reuters—breakdown of verified Gaza deaths (women/children) from UN rights office (Nov 8, 2024).

Just allegations.
by freedomben | 2025-11-04 01:23:43+00:00
And notably, those phones and tablets are intentionally hobbled by the device owners (Apple, Google) who do everything they can to ensure they can't be treated like personal computing devices. Short of regulatory intervention, I don't see this trend changing anytime soon. We're going full on in the direction of more locked down now that Google is tightening the screws on Android.
by toast0 | 2025-11-04 01:25:10+00:00
> extra adrenaline to fully numb it,

That's not what they usually use... but people have different reactions to novacaine, and different innervation; for dental work, there's a couple typical options for where nerves are and which nerves cover which teeth, some of which need more shots in more places.

For the GP, most likely the anesthetist put a note in the chart that they need more or different drugs to go under.
by omnicognate | 2025-11-04 01:25:22+00:00
I have never claimed that only people/machines that can do frontier maths research can be intelligent. (Though someone always responds as if I did.)

I said that a machine doing frontier maths research would be sufficient evidence to convince me that it is intelligent. My prior is very strongly that LLM's do not think like humans so I require compelling evidence to conclude that they do. I defined one such possible piece of evidence, and didn't exclude the possibility of others.

If I were to encounter such evidence and be persuaded, I would have to also consider it likely that LLMs employ their intelligence when solving IMO questions and generating code. However, those tasks alone are not sufficient to persuade me of their intelligence because I think there are ways of performing those tasks without human-like insight (by interpolating/recombining from vast training data).

As I said elsewhere in this thread:

> The special thing about novel mathematical thinking is that it is verifiable, requires genuine insight and is a text generation task, not that you have to be able to do it to be considered intelligent.
by drewbug01 | 2025-11-04 01:26:49+00:00
> Because you didn't tell it to make a "professional analytics application" for a while and then switch to nonsensical "unicorns and rainbows" at the end. You forgot to trick it into the "gotcha!" situation that OP intentionally created to make fun of the stupid AI.

Even if the OP initially asked for a “professional” application, this is hardly a “gotcha” situation - our tools should do what we ask!

I’m sure we could come up with some realistic exceptions, but let’s not waste our words on them: this is a pretty benign thing and I cannot believe we are normalizing the use of tools which do not obey our whims.
by rick1290 | 2025-11-04 01:28:05+00:00
I like mikro orm - cool to see you use that. I do prefer django however.

I see express as the backend. Why not nestjs? And are you using openapi at all for generating your frontend client?

What i've discovered is - any backend + orm should expose an openapi spec'd backend... and your frontend can autogen your client for you. Allows you to move extremely quick with the help of ai.
by akbarnur | 2025-11-04 01:28:15+00:00
NVIDIA | vLLM + SGLang | Deep Learning Inference | Remote (North America preferred)

Hi everyone — I’m Akbar, Senior Manager of Deep Learning Inference Software at NVIDIA. I lead our engineering efforts around vLLM and SGLang, two of the most widely used open-source LLM inference frameworks.

We’re building teams focused on making LLM inference faster, more efficient, and more reliable at scale — from runtime and scheduling optimizations to kernel fusion, distributed serving, and continuous integration across new GPU architectures (Hopper, Blackwell, etc.).

We’re hiring for multiple roles:

• Senior Deep Learning Software Engineer, Inference (https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSit...)

• Engineering Manager, Deep Learning Inference (https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSit...)

• DL Performance Software Engineer - LLM Inference (https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCar...)

• DL Performance Software Engineer - LLM Inference (https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCar...)

These roles are remote-friendly (North America preferred) and fully focused on upstream open-source development — working directly with the maintainers and the wider AI community.

If you’re excited about large-scale inference, compiler/runtime performance, and pushing GPUs to their limits, we’d love to talk.
by l9o | 2025-11-04 01:28:15+00:00
I think specialized hardware will emerge for specific proven workloads (transformer inference, for example), but GPUs won't become obsolete. They'll remain the experimentation platform for new architectures. You need flexibility to discover what's worth building custom silicon for.

Think 3D printers versus injection molds: you prototype with flexibility, then mass-produce with purpose-built tooling. We've seen this pattern before too. CPUs didn't vanish when GPUs arrived for graphics. The canal analogy assumes wholesale replacement. Reality is likely more boring: specialization emerges and flexibility survives.
by dsr_ | 2025-11-04 01:28:28+00:00
Jellyfin and a domain name with a dynamic DNS update will do that for you, no problem.

In the house: NFS read-only for desktops and laptops; Owntone to send music to Wiim Mini or stereo receivers (Yamaha, Denon, Marantz, Onkyo -- all of them are compatible).

Outside the house, JellyAmp on phones.
by galaxyLogic | 2025-11-04 01:28:54+00:00
To me this seems kind of obvious. Intelligent people have the capacity to question "truths" the society around them tells them to believe, because they can think and examine the validity of such proposed ideas, and rules, and authority.

Whereas less intelligent people do not have the capacity to question ideas and come up with plausible alternatives, then examine those critically. Therefore they just accept what authoritites, like say their father, or their Dear Leader tells them to believe.
by chrysoprace | 2025-11-04 01:30:58+00:00
tmux fits my personal use case better so I'll tell you why I use tmux and then if that resonates with you, then you might get value from that as well.

- It's generally bundled on most distros, or available for install in most default repositories.

- tmux sessions are available over ssh, so if I can continue where I left off over ssh (this is probably my main use case).

- I can full screen my terminal instead of having multiple terminals, and split in tmux. I usually split vim buffers, but then keep a terminal split beside it or in another tmux window.

- It's keyboard-driven, and universal across different window managers. Even if I switch from MacOS to Windows or to an X11 distro, tmux will still have the same keybinds using the same configuration language. I can also use vim keys to navigate the scrollback history.

- Its config language is simple enough for the modifications I personally need. I haven't felt that I need to learn the syntax beyond the basics.

- Knowing tmux is also a helpful skill for managing servers, which I do from time to time (my raspberry pi is still running a tmux session from when I last rebooted it).
by hackinthebochs | 2025-11-04 01:31:19+00:00
This is an overly reductive view of a fully trained LLM. You have identified the pieces, but you miss the whole. The inference code is like a circuit builder, it represents the high level matmuls and the potential paths for dataflow. The data blob as the fully converged model configures this circuit builder in the sense of specifying the exact pathways information flows through the system. But this isn't some inert formalism, this is an active, potent causal structure realized by the base computational substrate that is influencing and being influenced by the world. If anything is conscious here, it would be this structure. If the computational theory of mind is true, then there are some specific information dynamics that realize consciousness. Whether or not LLM training finds these structures is an open question.
by filipelbc | 2025-11-04 01:31:40+00:00
Location: Brazil Remote: Yes (only) Willing to relocate: No Technologies: Python, Java, Javascript, C#, F#, Rust, Bash, Docker, PostgreSQL, DynamoDB, AWS (Cloud Formation, Lambda, Cognito, API Gateway, etc...) Résumé/CV: https://www.linkedin.com/in/filipelbc/ Email: filipelbc@gmail.com

I'm a generalist software engineer and tech lead with 9+ years of experience, mostly focuses on the backend (platform, APIs, integrations, dev-ops, and data pipelines).

I'm interested in working on a team that values craftsmanship and thoughtfulness.

You should hire me if you need a senior lead engineer to scale your team and system in a sustainable manner.
by com2kid | 2025-11-04 01:31:50+00:00
I am, yeah.

There is no guarantee that the site would have survived, but abandoning it's original indie artists user base to chase psuedo-piracy $$ was ridiculous.

Counter point is that given its insane valuation, something mass market had to be pursued. Selling 1 off burned CDs for indie artists wasn't ever going to pay the bills.

Still a shitty thing to do to their original user base.
by seec | 2025-11-04 01:31:58+00:00
They always start with a false equivalency anyway, comparing stuff like cane sugar with cow meat, that's just extra dumb.

I don't have proper calculation, but when you add up all the processing and extra requirement to grow high protein crops, you are actually not very far from meat cost.

Which makes sense because if meat was so inefficient, then vegetal protein replacement should be much cheaper, but they are not.
by cosmic_cheese | 2025-11-04 01:32:28+00:00
Mac terminals yield a similar benefit, with the systemwide copy/paste Cmd+C/V not overlapping with Ctrl+C/V.

Being used to that, Linux terminals become rather annoying. Yes there's other ways under Linux, but they don't have 25+ years of muscle memory associated with them, and so when the key shortcuts don't work as expected it's like nails on a chalkboard.
by sejin8642 | 2025-11-04 01:32:33+00:00
Location: Las Vegas, NV, USA Remote: Yes Willing to relocate: Yes

Technologies: Python, C/C++, MATLAB, Bash, SQL, LaTeX, TensorFlow, PyTorch, Keras, Scikit-Learn, Computer Vision, Git/GitHub, Linux, HPC (SLURM), Scientific Python libraries, image processing, signal processing, physics simulation, Fourier analysis, statistical analysis

Résumé/CV: https://drive.google.com/file/d/1S_KGlM-Xq1n3ou3Ellr-cwhW1jA... Email: sejin8642@gmail.com
by maddiedreese | 2025-11-04 01:32:57+00:00
My first ever Raspberry Pi project!

Send a message from my website directly to my receipt printer in San Diego, California.

Built using Cursor, a Raspberry Pi 4B, a generic thermal receipt printer, Convex database, and frontend deployed via Netlify.

Also some help from ChatGPT haha.

It was a really fun build, and my first project like it!

I’ve already received over 700 (mostly incredibly kind) messages from all around the world. It’s been amazing, and I can’t stop thinking of all the fun projects I could build in the future.

I'd be happy to answer questions if anyone would like to build something similar. I’ve also open sourced it at https://github.com/maddiedreese/ticket-printer-os (my first ever open source project, so please reach out if you run into any issues)
by dwohnitmok | 2025-11-04 01:34:08+00:00
> Want to write ML, probably best to use a language with functions as first class types (ie a FP language). You might say, most people doing ML use Python. This came to be because the language was picked based upon what people knew. But the big companies doing ML (successfully) don't use Python anymore and haven't for over a decade. ML researchers kept FP alive for several decades when nobody else cared because FP is the best tool for ML (or for writing a compiler).

I strongly disagree. The top AI companies are using a lot of Python (although sure they also use other languages too, but they're definitely using Python!). Even if by ML you mean old-school ML techniques, a ton of big companies also use Python for this (some might use MATLAB or R).

On the other hand I don't know of a single large company using an FP language for ML, unless you count something like Spark (which I would push back on: the Scala API of Spark is not really FP and almost all users of Spark that I know of program mainly in the more OO part of Scala rather than its FP part).

Even die-hard FP companies such as Jane Street use Python for their ML (see e.g. https://www.janestreet.com/join-jane-street/position/4276720... which notably mentions Python and does not mention OCaml).

Do you know of any company with a team of over 50 ML researchers (either old-school ML or modern AI) using an FP language as their primary workhorse for that team? Because I can't think of a single one.

More to the point, do you know of any ML researcher (and who is acknowledged as primarily an ML researcher by other ML researchers) who primarily programs in an FP language?

Even in the golden era of symbolic AI from the 70s and 80s they still weren't using FP languages (they basically didn't exist yet). The closest you could say is that they were using Lisps, but Lisps aren't FP languages by default. Some are (e.g. Clojure), but many aren't or at least aren't any more FP than any other multiparadigmatic language (e.g. Common Lisp). And again I don't know of any significant ML work being done in Lisps at this point (there's some scattered small teams and individuals doing work there, but nothing that I think could rise to the level of "big ML company").
by chobobro | 2025-11-04 01:34:27+00:00
Location: Philadelphia, PA

Remote: OK

Willing to relocate: Maybe

Technologies: GNU/Linux, Python, C/C++, Erlang, OpenGL, Docker, git

Résumé/CV: https://github.com/rkblake/Resume/blob/master/randallblake_r...

Email: blakerandall0@gmail.com

Strong C++ and Python developer with intermediate experience with Lua, C#, Javascript/TS, Rust, and Golang. My previous job experience was with networking and parsing packets on switches in data centers using C. I also did some QA testing and I am open to those jobs. I enjoy working on side projects like making games in Godot, or websites using Flask or React.
by tim333 | 2025-11-04 01:35:10+00:00
Google pretty much invented LLMs. The Attention is Attention Is All You Need paper which kicked it off was done by Google scientists and the top model in the LLMArena for text is from Google. They also made $28 bn profit last quarter as against large losses for OpenAI. I think they'll survive.

I'd be more worried about OpenAI surviving. Aside from the iffy finances, much of their top talent seems to leave after falling out with Altman.
by PaulDavisThe1st | 2025-11-04 01:35:14+00:00
Tell me more.

As a firefighter, the training I've had tells me that they're generally no big deal. You spray water on them to keep the overall temps down, and wait. Not a big deal. The main difference is that they don't tend to go out quickly, so you may be stuck nursing it as it burns itself out for a long time.
by jll29 | 2025-11-04 01:35:30+00:00
The parent article's point, though, is that choice of programming language is often NOT driven by justified choices, but is a foregone conclusion because it is part of the identity ("I am/want to be a XY developer.") of someone influential (e.g. tech lead, CTO, VP Eng).

One argument I would like to add to this original debate is that I have observed two types of developers: one type tries to stick to one programming language for everything (e.g. Java) and tries to write everythin in that language. They are specialist and they may accrue deep knowledge of the language versions, APIs and IDE(s). Another type of developer, in contrast, maintains active knowledge of a dozen programming languages (C/C++, Java/Kotlin, Python, bash, Rust, Go, PHP, JavaScript, ...), and is capable of delivering projects in each. They'd pick a language suitable for the task and stick with it for a project. They won't know any single language as intimately as the first type, but they benefit by virtue of their choice of language being more appropriate to the given project.
by necovek | 2025-11-04 01:36:19+00:00
I've used PHP early in my career (around the time PHP 5 came about), and I was never a fan, but to claim that you can't built successful products with it is simply crazy: look at Facebook, Wordpress just to name the two!

And similarly, "Python for scripting" (Instagram?)... It's the effectiveness you achieve with it that is perfect for many new projects, based on language itself (dynamism, introspectiveness, readability...) and rich standard library and ecosystem.

I'd say you are not looking objectively at language choices despite the evidence being there in plain sight to counter the claims you are making.
by Retric | 2025-11-04 01:37:31+00:00
I don’t think it’s an oversimplification as accuracy is what constrains LLMs across so many domains. If you’re a wealthy person asking ChatGPT to write a prenup or other contract to use would be an act of stupidity unless you vetted it with an actual lawyer. My most desired use case is closer, but LLMs are still more than an order of magnitude below what I am willing to tolerate.

IMO that’s what maturity means in AI systems. Self driving cars aren’t limited by the underlying mechanical complexity, it’s all about the long quest for a system to make reasonably correct decisions hundreds of times a second for years across widely varying regions and weather conditions. Individual cruse missiles on the other hand only needed to operate across a single short and pre-mapped flight in specific conditions, therefore they used visual navigation decades earlier.
by gizajob | 2025-11-04 01:38:45+00:00
Great analysis but one thing overlooked is that current gen advanced AI could in five or ten years (or less) be run from the smartphone or desktop, which could negate all the capex from the hyperscalers and also Nvidia, which presents a massive target for competitors right now. The self same AI revolution we’re seeing created right now could take itself down if AI tooling becomes widespread.
by Dylan16807 | 2025-11-04 01:38:48+00:00
> But also, I reject your attempt to reframe the discussion as strictly car focused. OP specifically mentioned flight. Which doesn't necessarily mean it was all about aircraft - the article is about cars after all. But it certainly doesn't mean that the conversation was strictly about cars, either.

OP mentioned flight. But the part that got argued back and forth over the next 7 comments was about EVs. Aurornis never said a word about anything but EVs.
by HubertChen | 2025-11-04 01:39:28+00:00
Dialogue AI | Founding Software Engineer | Full-Time | Onsite (Los Angeles, CA)

Dialogue AI is building the future of customer research. Our platform brings together AI agents to help create studies, conduct interviews, and extract meaningful insights -- enabling teams to understand their customers faster and more effectively than traditional methods.

As a founding engineer, you will work across product, infrastructure, and AI to deliver a customer-first product you can be proud of. You will collaborate directly with a founding team from leading tech companies and universities, shaping both the product and the culture as we scale.

- We're looking to hire 2-3 engineers to round out the founding team

- Seed funding secured ~month ago in partnership w/ a top VC

- Compensation: $125-200K USD + equity

If interested, you can email me directly at hubert [@] dialogueai.com or apply here: https://jobs.ashbyhq.com/dialogueai/687b6d39-cf6d-4767-bc83-...
by embedding-shape | 2025-11-04 01:39:51+00:00
Overall it seems to me like different living situations, different geographical locations and different cultures end up creating people with vastly different perspectives. Put all of these people in the same location and after a while they think a bit alike, or at least "a bit alike" within a spectrum which gets smaller, and very uncommon to find those "outside of the spectrum" when you're actually in a physical space, limited to talking person by person.

I feel like the pervasiveness of the internet makes it much easier to find those perspectives that exists outside the norm, and I guess those are more interesting to me as I don't find those around me always, only under certain circumstances or even just happenstance.

So I guess my mind didn't go to "large community around me where I am" because I'd fear they still wouldn't posses, even less gain, those "fresh" perspectives that I seek.

I didn't feel you being accusatory FWIW, and always appreciate when people think about and question what I think, so thank you.
by buggy6257 | 2025-11-04 01:40:13+00:00
I work at a company doing full-stack Elixir with most of our devs all heavily using AI as they please to augment their workflow, and our CTO was genuinely concerned that our main competitor, a Python shop, had a leg-up on us for this exact reason.

He spent time running benchmarks for 0-1 apps and all kinds of other metrics and found basically no appreciable difference in the speed or accuracy of AI at generating Elixir vs. Python. Maybe some difference, but honestly it just doesn't exist enough to matter.
by necovek | 2025-11-04 01:41:18+00:00
In the first example, they didn't and recruited a CTO who made a tool choice that arguably killed the business (maybe it still ends the same with PHP, minus the experience of building a nicely architected system in Perl: what-ifs all around).

Management does need to care to ensure they hire people who will make the right choices (which is a careful balancing act of investment vs returns) if they don't trust themselves to do it.
by fn-mote | 2025-11-04 01:42:28+00:00
The comments here are a case study in conflict drives engagement. And not in a good way.

Try not to drive more conflict if you respond.

Facts:

The target audience of this post is someone who does not know anything about the dot product. It provides a mechanical/computational introduction. It does not include any geometric interpretation of the dot product.

Critique:

After you read the post, you should have seen something to connect to a matrix-vector product (imo), but the example matrices need to be transposed to look like a traditional matrix-vector product. Maybe the author is intending to multiply on the left by the transpose of the weight vector. The weights don’t seem to consistently appear on either side.