MurphyA/hacker-news huggingface dataset:
by troad | 2026-02-16 23:49:05+00:00
> The presumption of good faith is wasted on them.

That's just assholery masquerading as enlightenment.

> That's incorrect. Just take a look at the housing situation in the US: what's best for society is to build, but a majority of the people (the current owners) are blocking that because it suits them.

Maybe if you call the majority stupid some more, that's famously convincing in a democracy. You'll definitely build sustainable coalitions for the policies you want this way.

Capital loves this kind of left wing politics. Off-putting and impotent.
by CuriouslyC | 2026-02-16 23:51:33+00:00
The problem is that the model doesn't know what you mean by "bad code" a priori. If you list specific issues you care about (e.g. separation of concerns, don't repeat yourself, single responsibility, prefer pure functions, etc) it's pretty good at picking them out. Humans have this problem as well, we're just more opinionated.
by kristopolous | 2026-02-16 23:51:37+00:00
In the late 1990s there were a number of working groups for the w3c who were very familiar with the MVC paradigms.

Out of those multi-year-long working groups came cascading style sheets and their revisions along with JavaScript features like dom access.

The dominant paradigm is to let their work go unread and call it a flex.

I've frequently been belittled and mocked in online negging when I encourage people to take a deep dive and learn something new.

I'm not here to debate people who think mockery and dunking on people that have done hard work is good faith behavior
by JumpCrisscross | 2026-02-16 23:51:39+00:00
> it might not be on purpose, but you are signalling that you have status

Not really. I’m relying on another signal, the recognizance of my person in a small town. If a tourist walked in wearing what I’m wearing they wouldn’t get that treatment. The signal is my face. Not the dress. (I could dress up for the evening and the same thing would happen.)

> to signal like a regular person, you would be doing all the same stuff other people do to get the table

Sure. That’s the point. I’m not signaling “like a regular person.” I’m just not sending a signal with dress. I’m dressing ordinarily.

If I were actually trying to camouflage I’d do other things. And that would constitute false signaling. (And sure, with my friends, I am signaling something. But it’s still not a counter signal unless we expand the terms signal and counter signal to mean literally anything, information and noise alike.)
by belisarius222 | 2026-02-16 23:52:21+00:00
Hi, I'm the other author on this paper. You've asked a good question. I had originally planned on writing an agentic_reduce operator to complement the agentic_map operator, but the more I thought about it, the more I realized I couldn't come up with a use case for it that wasn't contrived. Instead, having the main agent write scripts that perform aggregations on the result of an agentic_map or llm_map call made a lot more sense.

It's quite possible that's wrong. If so, I would write llm_reduce like this: it would spawn a sub-task for every pair of elements in the list, which would call an LLM with a prompt telling it how to combine the two elements into one. The output type of the reduce operation would need to be the same as the input type, just like in normal map/reduce. This allows for a tree of operations to be performed, where the reduction is run log(n) times, resulting in a single value.

That value should probably be loaded into the LCM database by default, rather than putting it directly into the model's context, to protect the invariant that the model should be able to string together arbitrarily long sequences of maps and reduces without filling up its own context.

I don't think this would be hard to write. It would reuse the same database and parallelism machinery that llm_map and agentic_map use.
by cracki | 2026-02-16 23:52:48+00:00
North America. It's such a cramped little island, 50 meters is all but crossing it. You should be glad you can even go that far without having to revisit your starting position!

50 meters is probably not even the distance I walk to the nearest bus stop that's right up the street... unless they have an issue again, prompting me to abandon all hope and just walk a few miles to wherever I need to get to.
by 0bytematt | 2026-02-16 23:53:16+00:00
Thank you so much. Really appreciate the thoughtful feedback!

I've watched many intros. Somehow they always end with 90%+ accuracy and that was just not my experience while learning on datasets I picked myself. I remember spending hours tuning different parameters and not quite understanding why I was getting way worse accuracy. I showed this intentionally, and I'm glad you commented on this!

The XGBoost comparison is a great idea.
by nickysielicki | 2026-02-16 23:53:23+00:00
> Imagine being a vim or emacs user and have those replaced by something you have to type entire sentences for functionality.

This has already happened for a non-negligible amount of people on this site. I still use magit to prepare commits and review diffs. Everything else is English and Claude code or opencode.

Ironically, part of the reason I like emacs and formerly liked vim was because it reduced the amount of time my hands had to leave the keyboard. I simply look where I want to type, press the chord to jump with avy, and then begin typing. New tools are spiritually aligned with this goal. I look at the screen, I think about what I don’t like, and now instead of translating the criticism into code changes, I just stream my thoughts directly into the tool.
by lmeyerov | 2026-02-16 23:53:34+00:00
We had a measurable shift when we started doing ai-coding loops driven by evals. By definition, the additions make the numbers go up-and-to-the-right. It's the epitomy of "you get what you measure" :)

Chaos Congress talk on this from a couple months ago, jump to the coding loops part: https://media.ccc.de/v/39c3-breaking-bots-cheating-at-blue-t... . The talk focuses mostly on MCPs, but we now use the same flow for Skills.

This kind of experience makes me more hesitant to take on plugin and skill repos lacking evals or equivalent proving measurable quality over what the LLM knows and harness can handle. Generally a small number of things end up mattering majorly, but they end up being pivotal to get right, and the rest is a death by a thousand cuts.
by islamaskar | 2026-02-16 23:54:17+00:00
I've been building Fokus for the past year — it's a productivity app that puts tasks, calendar, notes, and goals in one workspace, with AI that actually schedules your day.

Not "AI-powered" in the "we slapped GPT on a to-do list" sense. It uses a constraint solver to build a real time-blocked plan based on your priorities, deadlines, energy levels, and calendar conflicts. There's also a Graph RAG pipeline so the AI assistant understands how your tasks relate to your projects and goals.

Some highlights:

Connects to Google Calendar, Outlook, Gmail, Slack, Notion, Jira, Trello
Desktop app (Electron)
Privacy-first — GDPR-compliant, no data sold, anonymous analytics only
The AI assistant (Captain Fokus) supports voice and image input
Day view, kanban, calendar views, time-blocking, QuickCapture
NestJS + MongoDB + Neo4j + Redis backend, Next.js frontend
Currently in beta: https://www.getfokus.com

I'm a solo dev, been shipping roughly every week. Happy to answer any questions about the architecture, the scheduling engine, or anything else. And yes, roast the landing page — I can take it.
by kshacker | 2026-02-16 23:55:07+00:00
We built Windows and DOS and got Viruses.

We built phone lines and got Spam and "Do Not Call" registries.

We built the Internet and got Ads, Scams, and Spoofing.

We built Google Search and got SEO gaming.

We built Facebook and it was Hijacked to influence elections.

We built AirTags to track our keys, and people used them for Stalking.

We built High-Frequency Trading and got Flash Crashes.

We built Encryption to protect data and got Ransomware.

We built Engagement Algorithms and got a Mental Health Crisis.

We built Planes, and people flew them into buildings. We only stay in the air today because of Rigorous Debugging: maintenance, reinforced doors, and intense security.

We got Globalization and got Offshore Scammers calling to "unblock" our Social Security numbers

Are we going to speed run the age of AI without someone trying to hijack it especially with the move fast and break things mentality?

I am sure teams are working on it. State actors and non state actors. Let's check the headlines in 2028.

AI will need "analyze plan" and "analyze query" levels of detail as safeguards—similar to voter-verified paper ballots—but with millions of queries running every minute, how do we keep up?
by rriley | 2026-02-16 23:55:57+00:00
The biggest gap in this paper is the condition they didn't test: Skills built through human-AI collaboration. They found fully self-generated Skills are useless (-1.3pp) and human-curated ones help a lot (+16.2pp), but that's a false dichotomy. In practice, especially in tools like OpenClaw, skills will emerge iteratively: the AI drafts procedural knowledge while solving a real problem, the human refines it with domain expertise. Neither produces the same artifact alone. The +16.2pp from curated Skills is likely the floor for this approach, not the ceiling. Would love to see a fourth condition.
by dogline | 2026-02-16 23:56:39+00:00
Also, just to clarify, I scanned all 7488 pages in personally (Fujitsu ScanSnap ix500). With Claude's help, I found some undocumented SANE features to auto crop and fix the scans, then had a Python script in Linux auto scan them and put them into a Postgres database as I went. Other scripts would add transcription, summaries, and auto index everything.

"mistral-ocr-latest" did really good handwriting transcription, considering how tight and small some of the handwriting is. Then back to Claude API calls to summarize by month and collect people and places from all of the entires.

Claude then created static html pages from what started as a Flask app. Published on Dreamhost.
by nerdsniper | 2026-02-16 23:56:49+00:00
Yes, I’m very aligned with “minimal dependencies, live off the land, roll your own” to avoid lock-in and vendor bullshit. Shit I’d rather rent baremetal from Hetzner than VPS from EC2/GCP/etc if I have enough workload to justify it.

But for my startup I still use a ton of SaaS services for things that I could probably do just fine myself. (Clerk/StackAuth, Supabase/PlanetScale, Cloudflare STUN/TURN, Clickhouse, Vercel, Calendly, Google Workspace, ngrok, Tailscale).

Spiritually, I hate using these. Any one of these would be dead-simple to replace. But my time is genuinely better spent on my startup’s particular value-add. Maybe I’ll replace these some day when we can hire someone to manage internal replacement services - some of which are as easy as “a postgres database” or “wireguard on some VPS instances”. But it’s just not worth my time right now when I’m focused on building revenue.

Even if they all cost $300/mo in total, and we’re bootstrapped, it’s a lot easier to cut back on UberEats or shiny nerdy toys than it is to replace all of these SaaS offerings. I recognize there’s a lot of ”I don’t know what I don’t know” and I’m liable to subtly misconfigure something in a potentially disastrous way.
by veyh | 2026-02-16 23:57:26+00:00
97 Twitch streams (and Youtube VOD uploads) + 32 shorts on Youtube, TikTok and Instagram. Best short got 5k views on YT, most got about 1k.

I didn't say I quit completely, I still stream when I play games because it doesn't cost me anything to do that since I was going to play the game anyway.

I no longer go through the VODs and try to cut them into shorts though, as it's such a huge time sink (and I don't think I'm very entertaining).

I made a couple of shorts directly related to my products too but as neither of them are really visual (one deals with micprohone audio, the other deal with mouse sensitivity), it's a bit difficult.
by tverbeure | 2026-02-16 23:57:56+00:00
My experience with Tcl is 30 years of using EDA tools, all of them equipped with this language from hell. Luckily, I've been to restrict the scripting part to the minimum. I'm sure that if you know the language well, you can see the foundational model that's behind it, but for occasional users, there's nothing predictable about it.

I couldn't tell you exactly all the thing that are wrong with it. Let's just say that a language where this is ok:

puts "Hello"

But this is not:

puts "Hello" # A comment

shouldn't exist.
by kianN | 2026-02-16 23:58:17+00:00
The code provided is to reproduce the analytical results from the annotated data; my impression is that you're more interested in the details of the annotation process than running into an issue with that code?

My company's core technology extends topic models to enable arbitrary hierarchical graphs, with additional branches beyond the topic and word branch. We expose those annotations in a SQL interface. It's an alternative/complementary approach to embeddings/LLMs for working with text data. In this case, the hierarchy broke submissions down into paragraphs added a layer to pool them into submissions, and added one more layer to pool them by year (on the topic branch).

Our word branch is a bit more complicated, but we have some extended documentation on our website if you are interested in digging a bit deeper. Always happy to chat more about the technical details of our topic models if you have any questions!

Overview of Our Technology: https://blog.sturdystatistics.com/posts/technology/
Technical Docs: https://docs.sturdystatistics.com/examples/quickstart/1.html
by kristjank | 2026-02-16 23:59:37+00:00
My experience is that in most of small companies, the revenue extraction cycle from big SaaS suites has gone far enough that people are moving to self-hosted (or rather colocated with a local-ish provider that installs and provides unofficial support) software, like they used to do before the great plague.

Considering how Zipf's law works, there might be a huge discrepancy coming on as we see the products deteriorating from all the AI and H1B spaghetti code to the point where LibreOffice appears quite competent by comparison. Most of the people I worked with just want to sell lamps or furniture or trumpets or whatever they do, and the inventions of modern SaaS make this a lot harder to do. Once enough small businesses stop paying their 5-user subscriptions, I think this whole thing will pivot heavily into the favor of those that just maintained their product well and didn't ensloppify it in the mantime.
by scotty79 | 2026-02-16 23:59:49+00:00
I think self-generation of skills might be useful if it's based on model doing websearches, experiments in a sandboxed environment and putting into skill what it found out.

Also generating skills using top of the line model to keep using them later in cheap open weights model seems like a good use of resources.

Online sharing of skills generated in such manner also seems like a wonderful idea.
by ASalazarMX | 2026-02-17 00:00:53+00:00
In my country, Mexico, the law doesn't recognize euthanasia, just suicide/homicide. Suicide of course is not a crime, because what are they going to do, jail you? Assisting suicide in any way is murder, though.

There are still repercussions for the people you leave behind. I can recall these:

- Any insurance is void

- Inheritance can be complicated if you can argue that the suicide was encouraged. It becomes premeditated murder.

- I think debt, specially if it's considerable, is handled different that natural death, that voids any debt.
by Zetaphor | 2026-02-17 00:01:13+00:00
> We should equally see such persistent questioning when American models are released, especially when frontier model companies are getting in bed with the Pentagon.

Yes, we should! And yet we don't, and that is exactly why I am so tired of seeing the exact same comment against one nation state and no others. If you're going to call out bullshit, make sure you're capable of smelling your own shit as well, otherwise you just come across as a moral tourist.

We all know the model is going to include censorship. Repeating the exact same line that was under every other model release adds nothing to the conversation, and over time starts to sound like a dog whistle. If you're going to create a top level comment to discuss this, actually have an original thought instead of informing everyone that water is wet, the sky is blue, and the CCP has influence over Chinese AI companies.
by slopinthebag | 2026-02-17 00:03:07+00:00
Not in practice, because these UI libraries usually have many intertwined interdependencies. <Button /> probably still imports all of the context providers, which also import their own dependencies, etc. So you end up including half of the library if not more just for a button, but if you use multiple components from the library the cost is amortised.

And typically if you're just using a single component it's one that is more complex than a button, like a popover or colour picker. Which then pulls in other components, etc.
by zozbot234 | 2026-02-17 00:04:21+00:00
Spinning HDDs will eventually be at risk of failing for purely mechanical reasons, so beyond handling them with care you can't really do all that much. Keeping them always-on may be a viable strategy for drives that are already mostly on, otherwise, just spin them up once in a while, but don't expect this to lower risk significantly. An old drive should simply have its contents transferred to new media, and then be treated as something ephemeral that may fail at any time without warning.
by verdverm | 2026-02-17 00:06:18+00:00
There is certainly different camps on this, two for demonstration purposes

1. Language catering to Ai

2. Ai had lots of training

I'm in camp 2 because (1) I need to read and understand (2) it seems better to push that level into the weights. I don't want to pollute my context with basics about how to use a language

The same applies more generally, to all sorts of tools, frameworks, and platforms.
Show HN: Andrej Karpathy's microgpt.py to C99 microgpt.c – 4,600x faster
by Ajay__soni | 2026-02-17 00:06:20+00:00
Andrej Karpathy showed us the GPT algorithm. I wanted to see the hardware limit.

The Punchline: I made it go 4,600x faster in pure C code, no dependencies and using a compiler with SIMD auto-vectorisation!!!

Andrej recently released microgpt.py - a brilliant, atomic look at the core of a GPT. As a low-latency developer, I couldn't resist seeing how fast it could go when you get closer to the metal.

So just for funzies, I spent a few hours building microgpt-c, a zero-dependency and pure C99 implementation featuring:

- 4,600x Faster training vs the Python reference (Tested on MacBook Pro M2 Max). On Windows, it is 2,300x faster.
- SIMD Auto-vectorisation for high-speed matrix operations.
- INT8 Quantisation (reducing weight storage by ~8x). Training is slightly slower, but the storage reduction is significant.

- Zero Dependencies - just pure logic.

The amalgamation image below is just for fun (and to show off the density!), but the GitHub repo contains the fully commented, structured code for anyone who wants to play with on-device AI.

I have started to build something useful, like a simple C code static analyser - I will do a follow-up post.

Everything else is just efficiency... but efficiency is where the magic happens
by runarberg | 2026-02-17 00:06:26+00:00
Seems very unlikely. My parent said the effects have already started (but provided no evidence), so I assume you mean by less then a generation. I am not a linguist but I would like to see evidence of such rapid shifts ever occurring in anywhere the history of languages before I believe either of you.

I have a feeling you only have a feeling, but not any credible mechanism in which such language shifts can occur.
by netsharc | 2026-02-17 00:07:19+00:00
> [Zuck] emphasized that such systems should require the person’s consent, saying it “should ultimately be your call.”

I'd find it morbidly hilarious (I'd be outraged too, but the lack of tact and the ensuing outrage would be hilarious) if it's enabled by default and users have to opt-out.

Using the simulation of dead people for content engagement in the attention-economy and Zuck-enrichment... If anyone is capable of that, it'd be him.

"Becky [Your highschool crush, FB knows how many hours you lurked her profile] liked your latest 5 Instagram posts... would you like to reach out?"
by belisarius222 | 2026-02-17 00:07:21+00:00
Did somebody say 'global namespace'? I spent years working on one of those as part of Urbit... In general, I think you're right. Each conversation is an append-only log at the lowest layer, and I see no reason not to expose that fact as a global namespace, as long as permissions are handled gracefully.

Of course getting permissions to work well might be easier said than done, but I like this direction.
by WalterBright | 2026-02-17 00:08:29+00:00
Yes, I hear that a lot. Might as well push on a rope, though.

In my early career years, a fellow employee came to work in track shorts and flip flops. He was a very, very good programmer. But he never got raises, and never got promoted, and complained to me about it. I suggested it was the way he dressed. He said the same things you wrote.

A couple decades later, I ran into him again at a conference. He ran his own quite successful company. He also was dressed sharply.

Things that make you go hmmm....
by CuriouslyC | 2026-02-17 00:08:31+00:00
They are making legit architectural and training advances in their releases. They don't have the huge data caches that the american labs built up before people started locking down their data, and they don't (yet) have the huge budgets the American labs have for post training, so it's only natural to do data augmentation. Now that capital allocation is being accelerated for AI labs in China, I expect Chinese models to start leapfrogging to #2 overall regularly. #1 will likely always be OpenAI or Anthropic (for the next 2-3 years at least), but well timed releases from Z.AI or Moonshot have a very good chance to hold second place for a month or two.
by bee_rider | 2026-02-17 00:08:34+00:00
In general terms, we get these kinds of results that seem to indicate that LLMs can’t really “create” new information using inference. LLM generated skills don’t help. Training on content that was generated by LLMs causes models to collapse or something. It seems like it is accepted as really intuitive.

But it seems pretty surprising to me. The training corpus contains so much information and the models operate at the level of… a bright novice. It seems like there obviously ought to be more insights to derive from looking harder at aspects of the corpus.

Why isn’t this considered astonishing?
by saghm | 2026-02-17 00:09:16+00:00
At least for me, the signal I'm sending is "I care more about how comfortable I am in my clothes than I do about what other people are inferring about them". The point isn't that people aren't receiving some sort of signal about me based on that, it's that the signal that they might receive is entirely irrelevant to my motivations. That itself might be a signal, but it's incidental to the actual choice I'm making, which is entirely personal.
by 627467 | 2026-02-17 00:09:25+00:00
Is Mastodon really hard to use for most people? I guess there's some very specific scenarios it may be.

Also the article presents a false dichotomy in my view: protocols need services to be useful to virtually 99.9999% of humans (or at least they do in the architecture we have built since... email?).

Who uses email without relying on servers? Where is your selfhosted email box sitting on if not in a hosting service?

Even IRC relies on servers for people to talk to. I love to experiment with protocols that do not rely on servers - secure scuttlebut? - but even ssb relied on some seed peer that provides a service to initialize the peering