MurphyA/hacker-news huggingface dataset:
by csh0 | 2025-07-01 22:15:10+00:00
The “AI Software Engineers” at my company, whose applications and workflows I often support as an SRE, by and large build things with LLMs rather than train or create them.

What they build ranges from product features to internal tools. They make heavy use of LLM vendor inference APIs, vector databases, etc. They end up writing a lot of glue code and software to manage the context of the LLM, query for data, integrate with other systems and so on. They also develop front-end interfaces for their applications.

Only recently have they started to, lightly, explore the idea of training LLMs with managed services like AWS SageMaker.

All this is to say that, the “AI Engineer/SWE” title will probably represent vastly different things depending on the technical sophistication of the organization.

If someone told me they were an AI Engineer at OpenAI I’d be more inclined to expect their role to be more fundamental, elsewhere, not so much.
by YZF | 2025-07-01 22:15:21+00:00
Maybe the real webpage also needs a better stack and designers need to worry less about things they can't control and think more about usability and simplicity.

I work on a large web based application, with designers, who use Figma. It's just too easy to lose the plot and come up with things that don't work well. Not because of Figma. Something about the balance between the software stack(s), the domain, the focus of designers today, the front end engineering, and product management is broken. It's interesting that Figma did (IMO) a great job at addressing the stack so they can build a product that does what they want it and then is used by so many to build products that don't always do what their customers want. Asking Figma to use the wrong stack for their product (which is what I'm reading between the lines) is not really the right answer...
by ClawsOnPaws | 2025-07-01 22:15:44+00:00
I keep coming to the same conclusion, which basically is: if I had an LLM write it for me, I just don't care about it. There are 2 projects out of the maybe 50 or so that are LLM generated, and even for those two I cared enough to make changes myself without an LLM. The rest just sit there because one day I thought huh wouldn't it be neat if, and then realized actually I cared more about having that thought than having the result of that thought. Then you end up fighting with different models and implementation details and then it messes up something and you go back and forth about how you actually want it to work, and somehow this is so much more draining and exhausting than just getting the work done manually with some slight completion help perhaps, maybe a little bit of boilerplate fill-in. And yes, this is after writing extensive design docs, then having some reasoning LLM figure out the tasks that need to be completed, then having some models talk back and forth about what needs to happen and while it's happening, and then I spent a whole lot of money on what exactly? Questionably working software that kinda sorta does what I wanted it to do? If I have a clear idea, or an existing codebase, if I end up guiding it along, agents and stuff are pretty cool I guess. But vibe coding? Maybe I'm in the minority here but as soon as it's a non trivial app, not just a random small script or bespoke app kind of deal, it's not fun, I often don't get the results I actually wanted out of it even if I tried to be as specific as I wanted with my prompting and design docs and example data and all that, it's expensive, code is still messy as heck, and at the end I feel like I just spent a whole lot of time actually literally arguing with my computer. Why would I want to do that?
by logsr | 2025-07-01 22:16:15+00:00
The biggest problem OAI has is that they don't own a data source. Meta, Google, and X all have existing platforms for sourcing real time data at global scale. OAI has ChatGPT, which gives them some unique data, but it is tiny and very limited compared to what their competitors have.

LLMs trained on open data will regress because there is too much LLM generated slop polluting the corpus now. In order for models to improve and adapt to current events they need fresh human created data, which requires a mechanism to separate human from AI content, which requires owning a platform where content is created, so that you can deploy surveillance tools to correctly identify human created content.
by Kon5ole | 2025-07-01 22:16:51+00:00
I assure you I have no relentless focus on anything but trying to understand what's going on! There are many problems for sure but I don't understand how they can be solved with faulty explanations!

Many people seem convinced that the problems in society are caused by billionaires hoarding money, when they clearly aren't hoarding any relevant amounts of money. The problems with housing, healthcare and such are very obviously caused by other things (Home mortgages being a huge cornerstone of the entire economy for one, millions are placed in a situation where cheaper housing would be a catastrophe - including banks).

Maybe our parents, who were able to buy a house for like 5 years of a worker's salary, were just the luckiest generation? It sure hasn't been that easy to get a home before or after at any time in history.

Right now is one of the runner ups though, but we're comparing the situation with the best ever.
by Karrot_Kream | 2025-07-01 22:17:03+00:00
It's hard to have an informed opinion on Algebraic Geometry (requires expertise) and not many people are going to upvote and engage with you about it either. It's a lot easier to have an opinion on tech execs, current events, and tech gossip. Moreover you're much more likely to get replies, upvotes, and other engagement for posting about it.

There's a reason politics and tech gossip are where most HN comments go these days. This is a pretty mainstream site.
by homefree | 2025-07-01 22:18:58+00:00
I hope xAI wins. I think Sam's self-portrayal as a missionary has a lot of irony - I see him as the ultimate mercenary.

It's always challenging to judge based entirely on public perceptions, but at some point public evidence adds up. The board firing, getting maybe fired from YC (disputed), people leaving to start anthropic because of him, people stating they don't want him in charge of AGI. All the other execs leaving. His lying in congress, his lying to the board, his general affect just seems off - not in an aspie way, but in some dishonest way. Yeah it's subjective, but it's a point and it's different from Zuckerberg, Musk etc. who come across as earnest. Even PG said if dropped on an island of cannibals you'd come back and Sam would be king.

I'm rooting for basically any of the other (American) players in the game to win.

At least Zuck is paying something close to the value these people might generate instead of having them sign hostile agreements to claw back their equity and then feigning ignorance. If NBA all stars get 100M$+ contracts, it's not crazy for a John Carmack type to command the same or more - the hard part is being able to identify the talent, not justify the value created by the leverage of the correct talent (which is huge).
by SilasX | 2025-07-01 22:21:12+00:00
Separate comment so you can separately downvote/flag me:

Why, OP, why? How much self-awareness does it really take to realize JBR is a non-standard acronym people won't recognize? It almost feels like a superpower that I take an extra half-second to think about what jargon the average person needs to have defined.
Show HN: Country Guessing Game
by kamakaya | 2025-07-01 22:22:03+00:00
Hi HN!

I created this simple two-person country guessing game to play with your friends. No login required.

You can either play a private match against a friend, or you can create or join a public match against a stranger.

My wife and I have been playing the game IRL during dinner time, so I decided to create an app to share it with more people. I have a few features that I still want to implement, and would love to hear your feedback as well!
by daxfohl | 2025-07-01 22:25:05+00:00
Or maybe it's that each of these things is pretty simple in itself. Clipping context is one line of code, summarizing could be a couple lines to have an LLM summarize it for you, etc. So not substantial enough for a formal library. Whereas the combinations of these techniques is very application dependent, so not reusable enough to warrant separating as an independent library.

Or maybe it just hasn't matured yet and we'll see more of it in the future. We'll see.
by YZF | 2025-07-01 22:25:20+00:00
Is this alignment the issue with your application? Are there design alternatives that would be impacted less by some rendering engine differences?

What about other browsers? Versions? Platforms? OS? Resolution/screen size? My huge frontend team can't handle this, even before we used Figma.

Isn't the problem trying to get this "web platform" do something it was never meant to do? How would this be solved by Figma using a rendering engine that would grind their product to a halt?

I'm old enough to have done a lot of native platform UI work, the web stack in many ways was a step backwards. It has obviously a lot of advantages (run anywhere) but in some ways it's more like IBM terminals on a mainframe vs. a native UI where you have full control. I (obviously) use and make web apps all the time, but they often suck, and this isn't Figma's fault.
by gregjor | 2025-07-01 22:25:35+00:00
As much as I’d like to continue debating with you I think we will just continue talking past each other.

I didn’t address the possibility of AGI, the consensus or “delta” of smart people, the utility of LLMs, or the prospect of OpenAI et al. someday making a profit in my original comment. You raised those issues and then put words in my mouth.

My original comment amounted to an Occam’s Razor argument: we can explain layoffs in terms of tax changes, economic and political uncertainty, over-hiring during COVID, and management incompetence. The impact of AI remains to be seen. The hype and fear-mongering serves the AI companies in a blatantly obvious way, so we should take their claims skeptically. Maybe it will all come true, but even if we get AGI next week that won’t explain the layoffs in tech and other sectors that started several years ago.

In a few years we will have more evidence to support (or not) AGI, whatever it means. And we will have more evidence of the real economic impact of AI. Right now no one can claim expertise, just opinions.
by edreispi | 2025-07-01 22:26:24+00:00
Location: Colombia Remote: yes Willing to relocate: yes Technologies: Python, Airflow, Airbyte, Snowflake, Databricks, AWS, GCP Résumé/CV: available upon request or contact me on LinkedIn https://www.linkedin.com/in/erikdreispiel Email: <name>.<lastname>@hey.com

I am a Data Engineer with 7+ years of experience in multiple industries. Have performed multiple data migrations and pipeline development. Background in backend software engineering. Currently interested in data quality, data observability and efficient LLM serving.
by 3cats-in-a-coat | 2025-07-01 22:26:32+00:00
That's an interesting question and it's quite possible the medium matters about gravitational transmission speed. I.e. the question is how is gravity transmitted. We'd need to know a lot more about the structure of subatomic matter & interactions to answer this one. As it stands, we have no theory of gravity at all at the quantum level.

I'm firmly of the opinion there's no "spooky action at a distance". All waves propagate gradually (if rapidly) through a medium, even if we decide to call that medium "vacuum" and define it as empty. Or more modernly, a "field". Waves don't propagate in nothing by definition.
by wongarsu | 2025-07-01 22:27:30+00:00
If I search for "best mlops tool" (granted, generic and uninspired query) on google, in the first 5 results I get three blogs of course platforms, one reddit thread, one github "awesome list" and 5 "top X" lists made by mlops tools, usually with that exact tool as the number one recommendation.

Of those 10 results, only one is ad-financed (reddit). And at least the five mlops tools won't mind being crawled and regurgitated algorithmically. If an AI uses their biased list to form opinions and recommendations that's exactly what they want
by EGreg | 2025-07-01 22:28:19+00:00
If your task fails, yet you sent an email that it succeeded, that is bad. You should wait until all your subtasks finish before sending the email.

Async subtasks typically ARE i/o, whether over a network or not.

The email shouldn't be sent if the DB update fails. The whole point is you wait until everything succeeds, before sending the email.

If your subtasks cause you to write some rows as if they succeeded, but subsequent subtasks fail, that is bad. You have to rollback your changes and not commit them.

If you charge a user even though they didn't get the thing they paid for, that's bad. Yes you can refund them after a dispute, but it's better not to have charged them in the first place.

The point is this: any subtasks that can cause your main task to fail should be processed BEFORE any subtasks that cannot cause your main task to fail.
by veryfastfourier | 2025-07-01 22:28:34+00:00
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by JadeNB | 2025-07-01 22:28:51+00:00
I've always enjoyed the to-me graceful experience of coupling each link to a footnote with a return anchor, so that you get the (to olds like me) familiar experience of footnotes without the pain of navigating to the bottom and then forgetting where you came from. My memory is that Daring Fireball, among many other sites, does this. (I just checked, and it does. Here's the most recent article that uses a footnote: https://daringfireball.net/2025/06/apple_app_store_policy_up.... Here's the reference to the footnote: https://daringfireball.net/2025/06/apple_app_store_policy_up.... And here's the footnote itself: https://daringfireball.net/2025/06/apple_app_store_policy_up.... This does require some special handling if you refer to the same footnote multiple times, but, if you really need to do that, the solution could be as simple as having the second reference be to a new footnote that immediately refers to the old one.)
by 3cats-in-a-coat | 2025-07-01 22:30:40+00:00
That's a very good question.

If light speed was infinite. If sound speed was infinite. Or even if water waves were infinite, we'd never feel or see anything waving.

We feel a wave by seeing the differential effect of it propagating. Which requires speed with a detectable progression. Compression, decompression. Excitation, de-excitation.

So when everything is quaking, we detect it by neighboring regions not being in sync as to the direction, amplitude, phase etc. of where they're quaking at any given moment.

Just like with normal earthquakes. The ground is shaking. If everything atop shook in perfect sync, you'd miss the earthquake. But otherwise, you feel it, you're destabilized. Not in sync with the ground.

For gravitational waves, it's much harder for us to feel it without special, very sensitive equipment. Normally. But if it was strong enough, we would.
by logsr | 2025-07-01 22:30:44+00:00
> “I have never been more confident in our research roadmap,” he wrote. “We are making an unprecedented bet on compute, but I love that we are doing it and I'm confident we will make good use of it. Most importantly of all, I think we have the most special team and culture in the world. We have work to do to improve our culture for sure; we have been through insane hypergrowth. But we have the core right in a way that I don't think anyone else quite does, and I'm confident we can fix the problems.”

tldr. knife fights in the hallways over the remaining life boats.
by sparacha | 2025-07-01 22:31:34+00:00
Arch is developer friendly, but designed for enterprise-grade customers in mind. The core contributors of Envoy redesigned the proxy substrate to handle prompts - offering something that is battle tested in terms of resiliency, speed, and deployments. Second, OpenRouter offers choice of models, but dynamically routing to LLMs based on user-defined usage policies is uniquely available in Arch. Hope that helps
by Syzygies | 2025-07-01 22:32:29+00:00
.claude/settings.local.json fragment:

"hooks": { "PostToolUse": [ { "matcher": "Edit|MultiEdit|Write", "hooks": [ { "type": "command", "command": "jq -r '.tool_input.file_path' | xargs bin/save-hook.sh" } ] } ] }

I jumped at this HN post, because Claude Code Opus 4 has this stupid habit of never terminating files with a return.

To test a new hook one needs to restart claude. Better to run the actual processing through a script one can continually edit in one session. This script uses formatters on C files and shell scripts, and just fixes missing returns on other files.

As usual claude and other AI is poor at breaking problems into small steps, and makes up ways to do things. The above hook receives a json file, which I first saved to disk, then extracted the file path and saved that to disk, then instead called save-hook.sh on that path. Now we're home after a couple of edits to save-hook.sh

This was all ten minutes. I wasted far more time letting it flail attempting bigger steps at once.
by ianbicking | 2025-07-01 22:32:41+00:00
I've been building a memory system myself, so I have some thoughts...

Why use a knowledge graph/triples? I have not been able to come up with any use for the predicate or reason to make these associations. Simple flat statements seem entirely sufficient and more accurate to the source material.

... OK, looking a little more, I'm guessing it is a way to see when a memory should be updated; you can match on the first two items of the predicate. In a sense you are normalizing the input and hoping that shows an update or duplicate memory.

I would be curious how well this works in practice. I've spent a fair amount of effort trying to merge and deduplicate memories in a more ad hoc way, generally using the LLM for this process (giving it a new memory and a list of old memories). It would feel much more deterministic and understandable to do this in a structured way. On the other hand I'm not sure how stable these triples would be. Would they all end up attached to the user? And will the predicate be helpful to establish meaningful relationships, or could the memories simply be attached to an entity?

For instance I could list a bunch of facts related to my house: the address, which room I sleep in, upcoming and past repairs, observations on the yard, etc. Many (but not all) of these could be best represented as one "about my house" memory, with all the details embedded in one string of natural language text. It would be great to structure repairs... but how will that work? (my house, needs repair, attic bath)? Or (my house, has room, attic bathroom) and (attic bathroom, needs repair, bath)? Will the system pick one somewhat arbitrarily then, being able to see that past memory, replicate its structure?

Another representation that occurs to for detecting duplicates and updates is simply "is related to entities". This creates a flatter database where there's less ambiguity in how memories are represented.

Anyway, that's one area that stuck out to me. It wasn't clear to me where the schema for memories is in the codebase, I think that would be very useful to understanding the system.
by benreesman | 2025-07-01 22:33:16+00:00
I think you'll be surprised if you see the lift karpathy demonstrates from `fineweb.edu` vs `webtext` (he went back later and changed the `nanogpt` repository to use `openwebtext` because it was different enough that it wasn't a good replication of GPT-2).

But from an architecture point of view, you might be surprised at how little has changed. Rotary and/or alibi embeddings are useful, and there's a ton on the inference efficiency side (GQA -> MHA -> MLA), but you can fundamentally take a llama and start it tractably small, and then make it bigger.

You can also get checkpoint weights for tons of models that are trivially competitive, and tune heads on them for a fraction of the cost.

This leaked Google memo is a pretty good summary (and remarkably prescient in terms of how it's played out): https://semianalysis.com/2023/05/04/google-we-have-no-moat-a...

I hope I didn't inadvertently say or imply that you can make GPT-4 in a weekend, that's not true. But you can make models with highly comparable characteristics based on open software, weights, training sets, and other resources that are basically all on HuggingFace: you can know how it works.

GPT-2 is the one you can do completely by yourself starting from knowing a little Python in one day.
by amy214 | 2025-07-01 22:33:20+00:00
>The right way to fund national needs is taxation.

No absolutes. Sometimes this is true, sometimes not. It feels great, amazing, to give back, to change someone's life with your money. It can feel even better for some people, to give back, to change someone's life, with your NEIGHBOR's money. So you can get people whose existence is to enforce that their neighbor, Peter, shall pay their other neighbor, Paul, and have Paul give them a solid pat on the back for doing them a solid. Peter is unhappy about it. Thusly is the cornerstone of politics.

Sometimes this thinking makes sense, sometimes not, usually not in the extremes, of which such people exist.
by philip1209 | 2025-07-01 22:34:33+00:00
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by amy214 | 2025-07-01 22:36:39+00:00
>So, in other words, he has no backbone.

Pretty fair if you take Eli Musk as a counterexample. Eli stood with the government and the whole left groaned that he sold out. Then he backed off due to his principles and the whole right groaned that he's not a team player, also the left still hates him too for some reason. Basically, in this hyper-polarized political environment, apparently all sides agree that they don't like Eli Musk, ironically the power commander of the Twitter propaganda network node.
by benreesman | 2025-07-01 22:36:43+00:00
Well what you said is:

"On the contrary, I believe in every verifiable domain RL must drive the agent to be the most intelligent (relative to RL award) it can be under the constraints--and often it must become more intelligent than humans in that environment."

And I said it's not that simple, in no way demonstrated, unlikely with current technology, and basically, nope.