MurphyA/hacker-news huggingface dataset:
by izyda | 2025-06-03 00:10:37+00:00
New Hedge fund | Sr/Staff Frontend Engineer | On-site (NYC)

We are a new discretionary, tech industry focused hedge fund, founded by a portfolio manager with 15+ years of experience at a Tiger Cub. I lead the data/technology team here and previously spent ~6 years in a similar role at a well known Tiger Cub.

We are hiring for a frontend senior/staff engineer for our internal research management web application.

Our tech stack: * Frontend: Typescript, Vue3 * Backend: Cloudflare, Supabase/Postgresql, Typescript *

Obviously, we are not the only ones trying to figure out how to use AI in investing but in a world where there are lots of people trying to build picks & shovels, this is an opportunity to be one of the goldminers at a greenfield, new firm. This role makes sense for people who are interested in finance/investing (although you do not necessarily have to have experience in the industry).

We're in full-time in office in NYC, so that's a requirement for FTE. We are potentially open to exceptional contractors located remotely.

We work very hard, hours are long, and people are very dedicated to the mission. It is not for everyone, but for those interested in competing in financial markets, love startup atmosphere without near-term existential risk, and want to work with super smart colleagues (both technical and investors!), this could be a great fit.

Target salary 180-250K, depending on experience + Bonus/Carry (hedge fund equity equivalent)

Contact: ai@nx1.com , I'm Alex.
by nsonha | 2025-06-03 00:10:46+00:00
Why focus on the 6 months or however long you think the cycle is. The milestones of AI coding are self-explanatory: autocomplete (shit) -> multi-files edit (useful for simple cases) -> agent (feedback loop with rag & tool use), this is where we are.

Really think about it and ask yourself if it's possible that AI can make any, ANY work a little more efficient?
by jvanderbot | 2025-06-03 00:10:46+00:00
This is the thing that gets me about LLM usage. They can be amazing revolutionary tech and yes they can also be nearly impossible to use right. The claim that they are going to replace this or that is hampered by the fact that there is very real skill required (at best) or just won't work most the time (at worst). Yes there are examples of amazing things, but the majority of things from the majority of users seems to be junk and the messaging designed around FUD and FOMO
by jasonfarnon | 2025-06-03 00:10:50+00:00
I don't really get this argument. Technology can be improving can't it? You're just saying that people saying it's improving, isn't a great signal. Maybe not, but you still don't conclude that the tech isn't improving, right? If you're old enough, remember the internet was very much hyped. Al gore was involved. But it's probably been every bit as transformative as promised.
by simonw | 2025-06-03 00:11:09+00:00
"they can't be aware of the latest changes in the frameworks I use, and so force me to use older features, sometimes less efficient"

That's mostly solved by the most recent ones that can run searches. I've had great results from o4-mini for this, since it can search for the latest updates - example here: https://simonwillison.net/2025/Apr/21/ai-assisted-search/#la...

Or for a lot of libraries you can dump the ENTIRE latest version into the prompt - I do this a lot with the Google Gemini 2.5 models since those can handle up to 1m tokens of input.

"they fail at doing clean DRY practices" - tell them to DRY in your prompt.

"they bait me into inexisting apis, or hallucinate solutions or issues" - really not an issue if you're actually testing your code! I wrote about that one here: https://simonwillison.net/2025/Mar/2/hallucinations-in-code/ - and if you're using one of the systems that runs your code for you (as promoted in tptacek's post) it will spot and fix these without you even needing to intervene.

"they cannot properly pick the context and the files to read in a mid-size app" - try Claude Code. It has a whole mechanism dedicated to doing just that, I reverse-engineered it this morning: https://simonwillison.net/2025/Jun/2/claude-trace/

"they suggest to download some random packages, sometimes low quality ones, or unmaintained ones" - yes, they absolutely do that. You need to maintain editorial control over what dependencies you add.
by stouset | 2025-06-03 00:11:10+00:00
I saw this article and thought, now's the time to try again!

Using Claude Sonnet 4, I attempted to add some better configuration to my golang project. An hour later, I was unable to get it to produce a usable configuration, apparently due to a recent v1-to-v2 config format migration. It took less time to hand-edit one based on reading the docs.

I keep getting told that this time agents are ready. Every time I decide to use them they fall flat on their face. Guess I'll try again in six months.
by cesarb | 2025-06-03 00:11:20+00:00
> Is there a term for “skeptics just haven’t used it enough” argument?

It's not an exact match to what you want, but "you're holding it wrong" is the closest I've found. (For those too young to have heard of it, it was an infamous rebuttal to criticism of a particular model of the iPhone: https://en.wikipedia.org/wiki/iPhone_4#Antenna)
by _wire_ | 2025-06-03 00:11:39+00:00
Why Not Mars - Maciej Cegłowski

https://idlewords.com/2023/1/why_not_mars.htm

//The goal of this essay is to persuade you that we shouldn’t send human beings to Mars, at least not anytime soon. Landing on Mars with existing technology would be a destructive, wasteful stunt whose only legacy would be to ruin the greatest natural history experiment in the Solar System. It would no more open a new era of spaceflight than a Phoenician sailor crossing the Atlantic in 500 B.C. would have opened up the New World. And it wouldn’t even be that much fun.//

continue reading above
by haiku2077 | 2025-06-03 00:12:00+00:00
You can run the agents on your own infrastructure (all the way down to a Mac Mini sitting on your desk), or Microsoft, OpenAI and I'm pretty sure Anthropic can sell you an Enterprise service that guarantees a certain level of confidentiality. I work in aerospace, one of the most paranoid industries, and even we got a Copilot subscription that met our needs...
by rednafi | 2025-06-03 00:14:08+00:00
A lot of people who are wary of LLMs aren’t against the technology itself, but rather the narrative surrounding it. You can take advantage of the tool while turning a blind eye to the discourse.

This 16-minute, expletive-filled, edgy-old-man-trying-too-hard-to-be-cool article could easily be dismissed as yet another AI creed that somehow found its way to the top of the HN front page.
by simonw | 2025-06-03 00:14:21+00:00
I've never heard of Ghidra before but, in case you're interested, I ran that prompt through OpenAI's o3 and Anthropic's Claude Opus 4 for you just now (both of them the latest/greatest models from those vendors and new as of less than six months ago) - results here: https://chatgpt.com/share/683e3e38-cfd0-8006-9e49-2aa799dac4... and https://claude.ai/share/7a076ca1-0dee-4b32-9c82-8a5fd3beb967

I have no way of evaluating these myself so they might just be garbage slop.
by fmstephe | 2025-06-03 00:14:55+00:00
Location: New Zealand, Manawatu Remote: Yes Willing to relocate: No Technologies: Go, Java, Git, Erlang, Postgres, Linux Resume: https://www.linkedin.com/in/francis-stephens/ Email: francisstephens@gmail.com

I work primarily on backend systems, with a strong focus on performance and system stability/resilience. I worked as a performance engineer at the mobile add-attribution company Adjust.

Some interesting open-source projects include

https://github.com/fmstephe/memorymanager An exploratory manual memory allocator for building large in-memory data structures with near zero GC cost.

https://github.com/fmstephe/matching_engine A financial trading matching engine with a somewhat novel red+black tree implementation.

https://github.com/fmstephe/flib A set of packages primarily in support of a lock-free single-producer single-consumer queue.

My ideal position would be working on backend systems primarily in Go.
by ElectricalUnion | 2025-06-03 00:15:21+00:00
Ok, but those sources or methods will not reproducibly build the artifact that are the weights of DeepSeek R1 671B, that you claimed are "opensource". Because you can't see what they actually used to build it.

DeepSeek didn't publish the exact dataset required to create it. How is having zero visibility over "the source" used to create something considered "opensource"?

That extended definition of "opensource" is useless as almost anything that isn't unique in the universe can then be declared "opensource".
by andrey_utkin | 2025-06-03 00:15:42+00:00
Location: Cambridge, UK Remote: Yes Willing to relocate: "Maybe" within Europe, elsewhere "depends" Technologies: C, C++, Python, SQL, kernel drivers, ffmpeg, TensorFlow, reverse debugging Résumé/CV: https://autkin.net/merit Github: https://github.com/andrey-utkin/ Email: hn@autkin.net
by andrey_utkin | 2025-06-03 00:15:45+00:00
SEEKING WORK | UK, REMOTE

18 yoe developing software systems with FOSS and contributing back.

In the past I got my bits of fame for WHDD https://whdd.github.io/demo/ and the analysis of energy consumption by mobile chat apps: https://decentim.grafana.net/public-dashboards/92602d3a4aa84...

I've worked in many areas, notably back end, multimedia streaming and communication services (IPTV, CCTV, VVoIP), Linux kernel drivers, debugger development. My contributions to FOSS include the kernel, FFmpeg, GStreamer and Gentoo.

Github: https://github.com/andrey-utkin/ Website: https://autkin.net Email: hn@autkin.net
by someothherguyy | 2025-06-03 00:16:17+00:00
Also, professional programmers have varying needs. These people are coding in different languages, with varying complexity, domains, existing code bases and so on.

People making arguments based on sweeping generalizations to a wide audience are often going to be perceived as delusional, as their statements do not apply universally to everyone.

To me, thinking LLMs can code generally because you have success with them and then telling others they are wrong in how they use them is making a gigantic assumptive leap.
by AdobiWanKenobi | 2025-06-03 00:16:22+00:00
Don't do a degree or two like I did. Just build shit, get yourself a 3D printer and some electronics, and again just build shit.

The only maths you'll need at the beginning is basic control engineering (PID Loops), forward/inverse kinematics and Extended Kalman Filtering. The only other thing is maybe V=IR, anything else and you're just placating some professor's ego.
by simonw | 2025-06-03 00:17:32+00:00
Part of being on Hacker News is learning that there are people in this community - like tptacek - who are worth listening to.

In general, part of being an effective member of human society is getting good at evaluating who you should listen to and who is just hot air. I collect people who I consider to be credible and who have provided me with useful information in the past. If they start spouting junk I quietly drop them from my "pay attention to these people" list.
by Xss3 | 2025-06-03 00:17:35+00:00
Source available sounds like you gotta buy it.

Think of it this way, if you were going to an event and saw 'buffet available' you'd enquire how to access it. If you saw 'open buffet' you'd know it's just there for the taking.

Open source sounds like it's free to view. It's open.

An open house isn't free to own. You view it.

Open source not meaning the source code is free to view but instead having a meaning related to licensing is silly.

Call it an open license, or just name the license. The code/source isn't the license. I'll die on this hill. Christine was cool but that doesn't make her infallible. Open source meaning open license was a mistake.
by 33Mastermind | 2025-06-03 00:17:49+00:00
automotiveMastermind is hiring multiple NY based hybrid positions! We help dealerships sell more cars by predicting and targeting likely buyers. All roles are full time with benefits:

- Full Stack Software Engineer | NY | https://spgi.wd5.myworkdayjobs.com/en-US/aM_Careers/details/...

- Data Engineer | NY | https://spgi.wd5.myworkdayjobs.com/en-US/aM_Careers/details/...

- Software Engineer | NY | https://spgi.wd5.myworkdayjobs.com/en-US/aM_Careers/details/...

- Associate Software Engineer | NY | https://spgi.wd5.myworkdayjobs.com/en-US/aM_Careers/details/...

- Quality Engineer | NY | https://spgi.wd5.myworkdayjobs.com/en-US/aM_Careers/details/...

Tech Stack - We have a cloud-native architecture, and we use Google Cloud Platform extensively. We regularly evaluate new technologies to see which ones we want to adopt.

Languages/frameworks & databases - C#, Python, Typescript, React b) Databases - PostgreSQL, MongoDB, Redis, ElasticSearch.

Also,

- Our scrum teams own the entire software development life cycle, including design, development, testing, and maintenance. - We prioritize speed and flexibility. New code is deployed to production every single day.
by chucknthem | 2025-06-03 00:18:29+00:00
How are you writing your prompts? I usually break a feature down to smaller task level before I prompt an agent (claude code in my case) to do anything. Feature level is often too hard to prompt and specify in enough detail for it to get right.

So I'd say claude 4 agents today are at smart but fresh intern level of autonomy. You still have to do the high level planning and task break down, but it can execute on tasks (say requiring 10 - 200 lines of code excluding tests). Any asking it to write much more code (200+ lines) often require a lot of follow ups and disappointment.
by esjeon | 2025-06-03 00:18:34+00:00
Anecdotally, ChatGPT still struggles with its own API. It keeps juggling between different versions of its API and hallucinates API parameters, even when I force-feed official documents into the context (to be fair, the documentation is straight awful). Sometimes it totally refuses to change its basic assumptions, so I have to blow up the context just to make it use the up-to-date API correctly.

LLMs are stupid - nothing magic, nothing great. They’re just tools. The problem with the recent LLM craze is that people make too many obviously partially true statements.
by keeda | 2025-06-03 00:18:46+00:00
A lot of the doubters are basically saying: "If it's so great, show me proof." While that is usually the right stance, I think it is short-sighted in times of revolutionary change.

To be sure, you definitely should not blindly trust the people who have a stake in selling AI products. However, you probably should trust the people who have no stake in selling AI, but are using it to accelerate themselves. The problem is, these people are probably too busy building things to spare any time convincing you. And in fact, it is a competitive advantage for them if others don't figure it out.

Here's my take: Everyone needs to figure out how AI works for them. The thing with AI is that it is a technology that behaves like people. It has the speed, efficiency and scale of computers but the fallibility and quirks of humans. This is why it's so confusing to discuss, and why folks have such varying experiences. The right approach to working with AI is like working with people: understand what they're good at and where they are weak, and then work with them to achieve your goals.

This will require using it "in anger" on many non-trivial tasks over a significant period of time, which will take persistence and patience. Yes, the hype is so over-the-top that you might not want to invest your valuable time on it. But you owe it to yourself to ensure you can fully capitalize on the sea change that is happening.

If it helps, I (like the OP) have no stake in selling AI and I posted this comment about my experiences on the other thread about the AI coding -- https://news.ycombinator.com/item?id=44163543 -- The upshot is, AI has enabled me to produce innovative (probably cutting edge) work in domains I had little prior background in. And I've not even used agents yet!
by munificent | 2025-06-03 00:19:23+00:00
> as 7-10 year old child, they were into SOLVING PRACTICAL PROBLEMS FOR PEOPLE.

Some of my fondest childhood memories are sitting in my school's resource center in front of a TRS-80, laboriously typing in some mimeographed BASIC code while wondering, "Is this the most efficient way I can increase shareholder value for the corporation?"
by ryandrake | 2025-06-03 00:19:58+00:00
I hate how the discourse around LLM-assisted programing is so polarized. It's either detractors saying it's "a fad that's useless and going nowhere, wasting billions of megawatts every year" or it's true believers calling it "the most miraculous sea change technological advancement in my lifetime" or "more important than fire and electricity[1]." There just doesn't seem to be any room in the middle.

I tried out Copilot a few months back to see what all the fuss was about and so that I could credibly engage with discussions having actually used the technology. I'd rate it as "kind of neat-o" but not earth shattering. It was like the first time I used an IDE with auto-complete. Oh, cool, nice feature. Would I pay monthly for it? No way. Would I integrate it into my development workflow if it were free? Maybe, I guess? Probably wouldn't bother unless it came literally set up for me out of the box like autocomplete does nowadays.

Don't get me wrong--it's cool technology. Well done, AI people. Is it "the 2nd most important thing to happen over the course of my career" as OP wrote? Come on, let's come down to earth a little.

1: https://www.cnbc.com/2018/02/01/google-ceo-sundar-pichai-ai-...
by rudimentary_phy | 2025-06-03 00:20:10+00:00
I learned to type playing the MMO Everquest. You used to have to type out the dialog for quests. I started playing that game in grade 3 and have been a fast typer ever since (I used to be about 140 wpm, but as I've aged, it has dropped to around 100-120, depending on how often I type).

I knew to place my two fingers on the f and j keys when I started, so I sort-of have proper typing skills (things like g, h, t, and y are usually tapped by whichever finger is closest, but otherwise I type correctly). One of my friends in school also played that game, and he has the same typing skills (and that exact bad habit). I did not know him when I first started playing. I find that to be a mighty coincidence, so I expected to encounter more people that learned that way, and I'm a little disappointed I haven't seen anyone else who learned that way yet.
by simonw | 2025-06-03 00:20:19+00:00
Yeah, definitely both.

New models come out all the time. One of the most interesting signals to look out for is when they tip over the quality boundary from "not useful at task X" to "useful at task X". It happened for coding about a year ago. It happened for search-based research assistants just two months ago, in my opinion - I wrote about that here: https://simonwillison.net/2025/Apr/21/ai-assisted-search/
by tines | 2025-06-03 00:20:20+00:00
I mean, just to steelman the argument, the "market" hasn't had time to react to what LLMs are good at, so your rebuttal falls flat. I think the original statement is more a prediction than a statement of current affairs.

Also, the author didn't say that "ease of use with LLMs" is the _only_ factor that matters. Julia could have other things wrong with it that prevent it from being adopted.
by FridgeSeal | 2025-06-03 00:20:38+00:00
Does it take months _now_ or did it take months, months/a year ago?

I’m still not entirely sure why it’s supposed to take months. I usually retry every few weeks whenever a new model comes out, and they get marginally better at something, but using them isn’t a massive shift? Maybe I’m missing something? I have some code, I pop open the pane, ask it, accept/reject the code and go on. What else is everyone even doing?

Edit: I’ve seen the prompt configs people at work have been throwing around, and I’m pretty glad I don’t bother with cursor-and-friends when I see that. Some people get LLM’s to write git commits? Lazygit has made most of my git workflow friction disappear and the 1 minute it takes me to write commits and pr’s is less effort than having to police a novel writing incorrect ones.
by orionblastar | 2025-06-03 00:20:41+00:00
The Atari ST was nicknamed the Jackintosh. It used TOS/GEM for the OS/GUI and used IBM PC-DOS formatted 720K DD/DS 3.5 floppy disks. I almost bought one but got a good deal on an Amiga 1000 with the 1200 baud modem and 1020 5.25 inch floppy drive with the PC-Transformer to run PC-DOS programs in an emulator.
by cyberax | 2025-06-03 00:20:52+00:00
> Currently mostly animal hemoglobin

Nope. They're making _plant_ hemoglobin ( https://en.wikipedia.org/wiki/Leghemoglobin ) to stay vegan.

Yes, I was also surprised that freaking plants have hemoglobin. But apparently, legume plants use it to create the oxygen-depleted environment for nitrogen fixing bacteria to work.
by sfRattan | 2025-06-03 00:20:52+00:00
> The author has some valid points, but dismissing this entire class of arguments so flippantly is intellectually lazy.

Agree 100%. And generally programmers have a poor understanding of the law, especially common law as it applies in America (the country whose legal system most software licenses have been written to integrate with, especially copyleft principles).

American Common Law is an institution and continuity of practice dating back centuries. Everything written by jurists within that tradition, while highly technical, is nonetheless targeted at human readers who are expected to apply common sense and good faith in reading. Where programmers declare something in law insufficiently specified or technically a loophole, the answer is largely: this was written for humans to interpret using human reason, not for computers to compile using limited, literal algorithms.

Codes of law are not computer code and do not behave like computer code.

And following the latest AI boom, here is what the bust will look like:

1. Corporations and the state use AI models and tools in a collective attempt to obfuscate, diffuse, and avoid accountability. This responsibility two-step is happening now.

2. When bad things happen (e.g. a self-driving car kills someone, predictive algorithms result in discriminatory policy, vibe coding results in data leaks and/or cyberattacks), there will be litigation that follows the bad things.

3. The judges overseeing the litigation will not accept that AI has somehow magically diffused and obfuscated all liability out of existence. They will look at the parties at hand, look at relevant precedents, pick out accountable humans, and fine them or---if the bad is bad enough---throw them in cages.

4. Other companies will then look at the fines and the caged humans, and will roll back their AI tools in a panic while they re-discover the humans they need to make accountable, and in so doing fill those humans back in on all the details they pawned off on AI tools.

The AI tools will survive, but in a role that is circumscribed by human accountability. This is how common law has worked for centuries. Most of the strange technicalities of our legal system are in fact immune reactions to attempts made by humans across the centuries to avoid accountability or exploit the system. The law may not be fast, but it will grow an immune response to AI tools and life will go on.