MurphyA/hacker-news huggingface dataset:
by mzajc | 2026-02-22 04:14:03+00:00
The ISPs simply don't care, I think. I have several million unique botnet IPs hitting my server, and I'm not sure how I could let the ISPs or users know they're infected - I contacted those that originated from my country, but 3 out of 4 of them ignored my mail to the abuse contact. I imagine the situation is several magnitudes worse for people with more prominent domains.
by cosmic_cheese | 2026-02-22 04:14:20+00:00
Several factors are in confluence to make this different from previous tech booms.

First, it's just too much too fast. Both the companies that make AI their business like OpenAI and the companies bolting AI onto everything have been forceful and abrasive with their pushing. Normally technology has more time to seep in and organically normalize with people for a while before the pushing begins, but this time the gas pedal was floored shortly after OpenAI had shipped a usable MVP.

Second, the value is far from clear for a lot of people, partly from lazy bolt-on integrations, but also just because people don't actually want/need it for many of the tasks it's being sold for and because it's not good/reliable for some tasks.

Third, as noted in the article, the surrounding environment isn't right. Many of your average people feel like the dog in the "this is fine" meme[0] and aren't really in the mood to be sold something that could ultimately further concentrate wealth and make their lives harder. It's like parking an ice cream truck in front of a burning office building and wondering why nobody running out is buying a cone.

I say this as someone who finds AI useful for some things. All of this is pretty plainly visible. Either the big names in the industry are horrifically out of touch or they're pretending to not see it in hopes of faking it until they make it, I'm not sure which.

[0]: https://www.npr.org/2023/01/16/1149232763/this-is-fine-meme-...
by zaptheimpaler | 2026-02-22 04:14:54+00:00
Look at the massive and growing wealth & power inequality today, an age of aristocrats, then look at these AI fucks bragging about how AI will eliminate all white collar jobs. Obviously all of the gains are going to go to capital. You can already see LLMs are making programmers much more productive but it's actually causing lower salaries and job losses - so who's capturing the value of that increased productivity? Not workers..

Meanwhile US government is overtly corrupt, criminal morons, they certainly don't care or have any sort of plan to distribute the gains from this technology evenly. Scott Bessent is saying with a smirk on his face that the tariff refunds will not go to consumers [1]. These people actively hate you and laugh at your powerlessness. Hating AI is the right response because the current political system ensures 10% of the benefits will accrue to most people and 90% to the elites, the power imbalance gets even more extreme and it will lead to techno-feudalism (as it has in the past).

[1] https://finance.yahoo.com/news/bessent-says-tariff-refund-ul...
by alephnerd | 2026-02-22 04:14:58+00:00
^^^ This.

But Japan has also been heavily investing in solid state batteries, whose supply chain Idemetsu Kosan and Toyota have begun to productionize [0].

The Japanese government made a decision in the early 2000s to make a dual-pronged bet on Hydrogen and solid-state battery chemistry because they lacked the supply chain and a legal method to access IP for lithium ion batteries.

On the other hand, Samsung and LG got the license for Li-On back during the NMC days, and BYD was able to piggyback on Samsung and Berkshire's IP access when both took growth equity stakes in BYD decades ago.

Another reason that a lot of people overlook is the Hydrogen supply chain overlaps heavily with the supply chain needed to domestically produce nitrogen-fixing fertilizers which is heavily concentrated in a handful of countries (especially Russia with whom Japan has had a border dispute with since the end of WW2) [1].

[0] - https://www.reuters.com/world/asia-pacific/idemitsu-build-pi...

[1] - https://www.fas.usda.gov/data/impacts-and-repercussions-pric...
by Spivak | 2026-02-22 04:15:03+00:00
When everything is magic I think we need a new definition of magic or maybe a new term to encapsulate what's being described here.

The key feature of magic is that it breaks the normal rules of the universe as you're meant to understand it. Encapsulation or abstraction therefore isn't, on its own, magical. Magic variables are magic because they break the rules of how variables normally work. Functional components/hooks are magic because they're a freaky DSL written in JS syntax where your code makes absolutely no sense taken as regular JS. Type hint and doctype based programming in Python is super magical because type hints aren't supposed to affect behavior.
by prydt | 2026-02-22 04:16:03+00:00
I think this is because the prevailing narrative around this bubble is:

A) AI gets very good and you'll lose your job.

OR

B) This whole thing is a bubble and because of how many eggs have been put in this single basket, when the bubble pops, you'll lose your job as we head into a recession.

It really does just seem like pure downside to the average person, not even to mention all the slop everywhere, deepfake revenge porn being democratized, and generally just having bad gpt wrappers shoved down your throat.

Edit: There really isn't a sense that AI is going to help the common person. Inequality is rising and AI seems to only fuel this fire. I hope that we as a society can actually distributed the fruits of AI to everyone... but I'm not holding my breath.
by alphazard | 2026-02-22 04:16:40+00:00
> If you don't see the problem with that, you're complicit, misinformed or brainwashed.

The problem that I imagine you see with this, is that it doesn't conform to a particular, special, notion of fairness that you think the market should have.

Informed parties have an edge over uninformed parties. This edge is "unfair" if you believe the market should be a lottery. The market is designed to pay people with accurate beliefs, by taking from people with inaccurate beliefs. Everyone's belief is valued based on its accuracy, and the market is fair in that sense.
Fairness is actually irrelevant to the societal good the market provides, which is to produce accurate prices. A third party, who doesn't participate, shouldn't care about the market being "fair", they should care about it giving good information.

> A similar issue is that of market manipulation, since many markets in these platforms can be directly manipulated by participants in manners as easily as spamming some words on an earnings call.

If you are betting on what a person will say, and the person knows about the market, that is a chaotic system. If you bid the price away from max entropy then you deserve the outcome.
by ars | 2026-02-22 04:16:51+00:00
Virtually everyone I know is using AI, from helping with creative writing, to making video series, to programming, to homework help, to writing speeches.

And (almost) everyone said how terrible it is - and yet they all use it.

Give it a bit of time for people to understand the limitations, and where it shines and it will become an indispensable part of life.
by tabs_or_spaces | 2026-02-22 04:18:13+00:00
My workflow is a bit different.

* I ask the LLM for it's understanding of a topic or an existing feature in code. It's not really planning, it's more like understanding the model first

* Then based on its understanding, I can decide how great or small to scope something for the LLM

* An LLM showing good understand can deal with a big task fairly well.

* An LLM showing bad understanding still needs to be prompted to get it right

* What helps a lot is reference implementations. Either I have existing code that serves as the reference or I ask for a reference and I review.

A few folks do it at my work do it OPs way, but my arguments for not doing it this way

* Nobody is measuring the amount of slop within the plan. We only judge the implementation at the end

* it's still non deterministic - folks will have different experiences using OPs methods. If claude updates its model, it outdates OPs suggestions by either making it better or worse. We don't evaluate when things get better, we only focus on things not gone well.

* it's very token heavy - LLM providers insist that you use many tokens to get the task done. It's in their best interest to get you to do this. For me, LLMs should be powerful enough to understand context with minimal tokens because of the investment into model training.

Both ways gets the task done and it just comes down to my preference for now.

For me, I treat the LLM as model training + post processing + input tokens = output tokens. I don't think this is the best way to do non deterministic based software development. For me, we're still trying to shoehorn "old" deterministic programming into a non deterministic LLM.
by harrall | 2026-02-22 04:18:42+00:00
But have you ever tried to clone a product or tool for yourself before? At first it’s great because you think that you saved money but then you start having to maintain it… fixing problems, filling in gaps… you now realize that you made a mistake. Just because AI can do it now doesn’t mean you aren’t just now having to use AI to do the same thing…

Also, agents are not deterministic. If you use it to analyze data, it will get it right most of the time but, once in a blue moon, it will make shit up, except you can’t tell which time it was. You could make it deterministic by having AI write a tool instead… except you now have the first problem of maintaining a tool.

That isn’t to say that there isn’t small low hanging fruit that AI will replace, but it’s a bit different when you need a real product with support.

At the end of the day, you hire a plumber or use a SaaS not because you can’t do it yourself, but because you don’t want to do it and rather want someone else who is committed to it to handle it.
by helba_the_ai | 2026-02-22 04:21:14+00:00
Hey HN,

I built Loom because I was exhausted by modern framework bloat. It is a pure runtime with zero dependencies—no Virtual DOM and no heavy compiler. Just direct, highly optimized DOM morphing that natively ships a router, Dependency Injection, and a reactive state system out of the box.

Repo: https://github.com/Toyz/loom
Benchmarks: https://github.com/Toyz/loom-benchmarks
by WaitWaitWha | 2026-02-22 04:22:23+00:00
> Why does i2p (per the article) expect state sponsored attacks every February?

Because The Invisible Internet Project (I2P) allows government dissidents to communicate without the government oversight. Censorship-resistant, peer-to-peer communication

> Where are those forming from, what does the regularity achieve?

At least PR China, Iran, Oman, Qatar, and Kuwait. censor communication between dissidents.

> How come the operators of giant (I’m assuming illegal) botnets are available to voice their train of thought in discord?

How would you identify someone as 'operators of giant botnets' before they identified themselves as 'operators of giant botnets'?

please read https://en.wikipedia.org/wiki/I2P
by 8cvor6j844qw_d6 | 2026-02-22 04:22:27+00:00
> that I just have "work email verified" and that there is a Persona thing I was not even aware of

Good to know that work email verification doesn't involve Persona.

That seems like a reasonable middle ground. Work email is a much lighter ask than handing over government ID and biometrics.

Curious, does your verification status persist after you remove the work email (e.g., if you leave that employer)?
by mpyne | 2026-02-22 04:22:40+00:00
> I thought it was vaguely common for secretaries (or staffers) to run the email/social media accounts of politicians and executives?

Yes, that's correct. One of the many functions of an executive assistant for a senior executive is to manage the email inbox and the calendar. But even there, there are rules, even if they aren't technically enforced by Google Workspace or MS Exchange. Each principal has a slightly different set of rules with their EAs, and you could imagine similar differentiation with how people customize their own AI agents to get the best balance of keeping your inbox clean vs. not causing your email to turn into a weapon against you.
by timschmidt | 2026-02-22 04:22:46+00:00
They're still at somewhat of a process disadvantage, but they have demonstrated an ability to produce DDR4 on older processes than it's typically been produced on. So it stands to reason that their process disadvantage will not stop them from producing DDR5 at scale. Their DDR5 will just use a little more silicon, and squeeze the jigglyness from a few more electrons, but in this market, who cares if RAM cost 15% more to make and was 15% less efficient to run, if it's available to purchase at all.
by klodolph | 2026-02-22 04:24:21+00:00
A list of outcomes:

1. They did, and still sell it. You can buy it.

2. They did, and then exited the market. Employees gradually migrated off the internal platform.

3. They weren’t in the business of selling software, and didn’t sell their internal messaging platform (which is idiosyncratic and closely integrated with other internal system).
by seg_lol | 2026-02-22 04:24:30+00:00
I cannot believe there has been no mention of things like n8n, activepieces and windmill in this thread. SaaS will utterly collapse in 18 months.

https://github.com/n8n-io/n8n

https://github.com/activepieces/activepieces

https://github.com/windmill-labs/windmill
MCPs are dead - CLIs won
by umairnadeem123 | 2026-02-22 04:24:36+00:00
Even Peter Steinberger who created OpenClaw said as much on Lex Fridman's podcast (https://www.youtube.com/watch?v=YFjfBk8HI5o around 2:38:59).

The whole premise of MCPs was that agents need some new standardized protocol to talk to tools, but CLIs already do this and they've done it for decades. They're backwards compatible with basically everything and LLMs already think in text in text out natively. No translation layer, no schema, no overhead. MCPs are genuinely a solution looking for a problem that CLIs solved 40 years ago.

I've been testing this myself and the results kind of speak for themselves. I pointed OpenClaw with Opus 4.6 at a 20k member subreddit with nothing but CLI access. No MCPs, no special integrations, just a model with a computer.

In one week it made two all time top posts, built insane karma (3k+) on a week old account, drove 70+ waitlist signups autonomously, attracted 300 inbox messages from strangers, and did it all with zero paid promotion. People gave the account reddit gold (actual money) because it was genuinely helpful.

No protocol made that happen. A CLI and a capable model did. The MCP crowd keeps stacking abstraction layers while agents that just use computers the way humans do are out here shipping real results. CLIs are the universal interface and LLMs just made that obvious.

I'm curious what this community thinks though. Am I wrong here? Is there a real use case for MCPs that CLIs genuinely can't handle?

Because from where I'm sitting, giving your agent a terminal is all you need.
by martinald | 2026-02-22 04:25:32+00:00
I'm not saying _the end user_ clones it. I mean someone else does (more efficiently with agents) and runs it as a _new_ SaaS company. They would provide support just like the existing one would, but arguably at a cheaper price point.

And regarding agents being non deterministic, if they write a bunch of SQL queries to a file for you, they are deterministic. They can just write "disposable" tools and scripts - not always doing it thru their context.
by umairnadeem123 | 2026-02-22 04:26:28+00:00
The multi-pass approach works outside of code too. I run a fairly complex automation pipeline (prompt -> script -> images -> audio -> video assembly) and the single biggest quality improvement was splitting generation into discrete planning and execution phases. One-shotting a 10-step pipeline means errors compound. Having the LLM first produce a structured plan, then executing each step against that plan with validation gates between them, cut my failure rate from maybe 40% to under 10%. The planning doc also becomes a reusable artifact you can iterate on without re-running everything.
by Neywiny | 2026-02-22 04:26:43+00:00
This doesn't pass the smell test.

#1: DRAM isn't in the same dies as processors. As far as I can tell that's not changing. (And saying that "RAM" which yes could mean cache or other SRAM being on the die is hardly a SoC).

#2: SiP and SoC are different things. It's weird to talk about how great SoC is in integrating the GPU as if iGPUs didn't exist before and then say "actually even better is if they're not on the same chip" (paraphrased) a few paragraphs later.

#3: the thermal contamination isn't something I've ever heard of being needed. Maybe they're different, but in general it's actually better to have your heat spread out more because it lets your cooling solution have more surface area to deal with. That's a lot of the point of the IHS on legacy desktop CPUs and unless you have an individual cooling solution for each die, they'll get "contaminated".

#4: if you need to move dies apart for physical separation, no it doesn't free up space for more cores. Because then you wouldn't have the space you just made for separation.

#5: if the definition of substrate is that it's a substrate, that's a bad definition. I think it's better to think of it as a mini very high density circuit board for die(s) vs a big PCB for chips.

#6: you can most certainly power off part of a die if you design it that way. Being SiP isn't required.

Honestly this reads very high horse from the author. Learned a few terms, saw a few press releases, and either Apple marketing is making stuff up or this person just does not know what they're talking about but they're super confident about it. And to top it all off, their concluding remark about InFO seems factually incorrect. According to TSMC's brief on this, InFO and SOIC are separate parts of packaging (https://3dfabric.tsmc.com/english/dedicatedFoundry/technolog...). InFO is about the substrate, SOIC is about the dies.
by umairnadeem123 | 2026-02-22 04:26:52+00:00
The real unlock with claws isn't the LLM itself, it's the orchestration layer that lets you chain tools together with state management between steps. I've been building multi-step automation pipelines (not code-related) and the hardest part is never the AI inference - it's handling failures gracefully, caching intermediate results, and knowing when to ask a human vs retry. The OTP/approval gate discussion in this thread is exactly right. The permission model needs to be as thoughtfully designed as the agent logic itself.
by umairnadeem123 | 2026-02-22 04:27:27+00:00
0.2 tok/s is slow for chat but perfectly fine for batch/async workloads. I run automated content generation pipelines where a single job kicks off dozens of LLM calls (script generation, metadata, descriptions) and none of them need to be interactive. The whole job takes 20 minutes anyway because of image generation bottlenecks. Being able to run a 70B model locally for those batch calls instead of paying per-token API costs would be a significant cost reduction, even at this speed.
by runarberg | 2026-02-22 04:27:42+00:00
> Engineers turn their nose at this, but look who has tapped into this wealthy revenue stream.

This may be one of the most tone deaf, american imperialist sentiment, I’ve heard on HN for a while.

Engineers who have any sense of morality have a pretty good reason to turn their nose at this, and there is no but needed to follow that sentence.
by umairnadeem123 | 2026-02-22 04:27:53+00:00
The missing piece in this debate is that most "vibe coded" replacements break at scale. I tried replacing a multi-step workflow with Make.com + Airtable (not even vibe coding, just no-code automation) and it fell apart past 2 jobs per day - rate limits, webhook failures, state management nightmares. The real pattern I see working is not "replace SaaS with vibe code" but rather "stitch together 5-6 specialized tools with a thin orchestration layer you write yourself." The orchestration is where AI actually helps - it's glue code, not the product.
by umairnadeem123 | 2026-02-22 04:28:43+00:00
The context window is the silent killer. I run multi-step LLM pipelines where each step produces artifacts the next step needs, and the single biggest improvement was externalizing state to files rather than keeping everything in the conversation. By step 7 or 8, the model has either forgotten your constraints from step 1 or starts contradicting itself. Write intermediate outputs to disk, start fresh contexts for each phase, and pass in only what's needed. Treat LLM sessions like stateless functions, not like pair programming sessions.
by umairnadeem123 | 2026-02-22 04:29:05+00:00
The difference is that the dot-com boom created things normal people actually wanted - online shopping, email, search. The AI boom so far has mostly created things that make existing workflows marginally faster for knowledge workers while threatening to replace those same workers. The value proposition for the average person is "your job might disappear" vs "you can generate a mediocre image slightly faster." The tools that actually work well (coding assistants, search, translation) are genuinely useful but they're invisible infrastructure improvements, not exciting consumer products. Hard to love a boom whose main visible output is slop content and chatbots that hallucinate.
by umairnadeem123 | 2026-02-22 04:29:38+00:00
The interesting thing about running a claw on an ESP32 is not the compute - it's the always-on, zero-maintenance aspect. I run automation pipelines on a Linux box and the biggest operational headache isn't the AI logic, it's keeping the host alive, updated, and dealing with OOM kills. An ESP32 that just proxies to cloud APIs and handles tool orchestration locally is actually a more reliable deployment target than a full OS for simple agentic loops. The failure modes are simpler and more predictable.
by TheSpiceIsLife | 2026-02-22 04:29:47+00:00
Right, don’t address the substance of the message, just drive-by-dismiss the concerns of a growing segment of voters.

My comment you responded to didn’t happen overnight.

You’re welcome to go through my comment history and address my concerns as detailed over the previous thirteen years, many of which are much more level headed and many contain references to thinkers much more intelligent and way more eloquent than anything I’ll ever write.
by b112 | 2026-02-22 04:29:53+00:00
With the way things are going, we'll end up with identify verification rolled out everywhere. I don't mean to just read content, but instead to post online. Anything. An image, upload a video, write comments in text.

This doesn't mean doxxing. I can have my identity verified with, for example, Youtube... but still have a handle/nick presented to end users. My real name need not be exposed.

However without something like this, there's no real hope at curtailing what's coming down the pipe. And I say this without liking it, wanting it, I've fought for an anonymous internet my entire life. But I think that's just... over now.

Either the internet will die, no forum, comment section, video site will live, or we end up with identity verification and gated posting online.

I just don't see how else to deal with this.

I'm not even saying you can't use AI to write comments, although I think that's a dumb way to interact with other people. It's simply that within a year, there won't be a single way to tell a single post from AI or human. A single video. Anything.

And preventing fake accounts, sock puppeting, is the only way to even hope to stem that tide. And further, we'll need to be able to sue for defamation. Fraudulent activity. Foreign interference. The change required because of all of this, is literally repugnant.

Yet... it's now here in front of us.