MurphyA/hacker-news huggingface dataset:
by cyberax | 2026-02-22 08:07:01+00:00
> Phonetic spelling would perhaps make the language easier to learn for native speakers, but it would make it harder to learn for foreigners, at least those of us who come from Europe.

BS. Phonetic alphabets are _much_ easier to learn for everyone. In Russia and Ukraine pretty much every child can read by the time they enter the first grade. It's _that_ easy because both alphabets are phonetic (although it's only one-way in case of Russian).

Meanwhile, when I was learning English there basically was one spelling rule: memorize. It was not at all helpful. I also ended up learning English as a mostly written language, so after moving to the US, I kept getting surprised by how familiar written words are actually pronounced.

E.g. it took me a while to explain to a nurse over the phone that I may have pneumonia and need an appointment. Why the heck that leading "p" is completely silent?!?
by dmurray | 2026-02-22 08:08:16+00:00
The only product they've announced at the moment [0] is a PCI-e card. It's more like a small power bank than a big thumb drive.

But sure, the next generation could be much smaller. It doesn't require battery cells, (much) heat management, or ruggedization, all of which put hard limits on how much you can miniaturise power banks.

[0] https://taalas.com/the-path-to-ubiquitous-ai/
by pests | 2026-02-22 08:10:40+00:00
This is so odd. I tried to verify your claim and I give up. It might be but I really hate how information is becoming like this. There is other reporting out there on "Starkiller" (the phishing kit in kerbs most recent post) and I can find other articles on it, but sources seem to be circular. The source mentions Jinkusu forums, which do seem to be real, but any links I find aren't loading for me and still no conclusive findings of Starkiller.
by jaen | 2026-02-22 08:12:24+00:00
You're getting more and more irrational.

> it's OK for you to insult a person.

I made an analogy which just means that it's hard to understand what the different styles and paradigms are when those are the things you constantly use.

You're apparently taking that as an insult...

> But you apparently missed that the "twisty" part

I didn't miss anything. You just didn't explain it. "twisty" does not mean "ambiguous" or "hard to parse". Can't miss what you don't write.
by overfeed | 2026-02-22 08:12:47+00:00
I don't know why you prefixed with "Yet" when I clearly spelt out the trade-offs and contrasts in distribution between H2 and electricity.

The Mirai goes from empty to full in 5 minutes or less - which compares very well with fossil-fuel burners. Now that every OEM has abandoned battery-swapping, how fast can EV batteries be safely charged with the said 3 phases? How long were the charging time when the Mirai was debuted? That was the trade-off Toyota was hoping to fall on the good side of, nevermind the Japanese government bet on hydrogen and whatever incentives are available for Toyota.
How do telehealth platforms handle provider license verification at scale?
by Nirvahana | 2026-02-22 08:13:35+00:00
I’m researching how Telehealth platforms and credentialing software handle medical license verification across multiple states.

From what I can tell, verifying a provider typically involves:

Checking NPI (NPPES)

Screening against the OIG exclusion list

Verifying active status with individual state medical boards

NPPES and OIG data are relatively structured, but state board data appears fragmented. Some states provide bulk downloads, others expose search portals, and some have terms that restrict commercial aggregation.

In one conversation with a Telehealth founder, I heard the pattern was “start manual, outsource at scale.” Most of the solutions I’ve found seem to be service-heavy credentialing vendors rather than API-first infrastructure.

I’m trying to understand:

Is license verification generally treated as a solved problem via enterprise vendors?

Do teams build internal tooling for this?

Is there meaningful demand for an API layer, or is the market too small / too service-oriented?

If you’ve built or operated Telehealth or credentialing systems, I’d appreciate your perspective.
by Ray20 | 2026-02-22 08:14:01+00:00
> Round trip efficiency of hydrogen is at best 50%

In fact, even this level of efficiency may be sufficient. Solar panels are so cheap that if we had affordable, long-term energy storage options, even with such efficiency, we would have completely abandoned fossil fuels. But, unfortunately, storing hydrogen is difficult and dangerous. It is not like natural gas.

> It's not nearly as stupid as making ethanol from corn (which is an energy-negative process) but it's close.

Ethanol is produced from corn not for energy purposes, but for food security. It's like a placeholder for real corn so that if there's a crop failure for a couple of years, the low-iq idiots who think it's stupid to make ethanol from corn don't starve to death.
by Tade0 | 2026-02-22 08:14:34+00:00
> EVs take forever to charge, rendering long trips unrealistic.

You'll find EVs that will go 700km+ with just one, 15min stop, as they charge at over 350kW in this day and age:

https://ev-database.org/#group=vehicle-group&av-1=1&rs-pr=10...

You'd want to make that 15min stop at least once on such a trip. Or fly instead.

> It's only through trillions of research dollars, that current battery tech is where it is.

Problem is that while batteries only needed scale and improvements in manufacturing processes to become cheaper, there's no such path with hydrogen.

The tank and the fuel cell are inherently expensive. The fueling station costs literally 10x that of a fast charger and in this day and age doesn't even charge faster as while the first customer will be done in less than 15min, the next needs to wait for the system to repressurize and that takes time. Also it goes kaboom if it fails, which is something we know, because it already happened. The fuel itself cannot be cheaper than electricity unless you want to make it from natural gas, in which case you better just use that instead.

> (batteries are terrible, environmentally)

The sheer energy that's wasted by a hydrogen car vs EV over its life cycle is enough to produce and safely dispose of a battery.

And this is what it really boils down to: hydrogen is not energetically efficient, therefore you can't make it cheaper unless you use fossil fuels. We already have fossil fuel cars.
by bigfudge | 2026-02-22 08:14:41+00:00
You write as though the selection of information by algorithmic feeds is a politically neutral act, which comes about by free actions of the people. But this is demonstrably not the case. Selecting hard for misinformation which enrages (because it increases engagement) means that social media are pushing populations further and further to the right. And this serves the interest of the literal handful of billionaires who control those sites. This is the unhealthy concentration of power the OP writes about, and it is a threat to democracy as we've known it.
by writingdna | 2026-02-22 08:15:43+00:00
The article frames this as "semantic ablation" but the underlying mechanism is more specific: it is distributional averaging. RLHF and DPO reward policies optimize for the modal response given a prompt distribution. That is not a bug in the training process, it is the objective function working as designed. The model learns to produce the response that the median annotator would rate highest, and that response is, almost by definition, the least distinctive one.

What is underappreciated is how much stylistic signal lives in what information retrieval people call "burstiness" -- the tendency for distinctive words to cluster rather than distribute evenly. Hemingway's short declarative stacking, DFW's recursive parentheticals, legal writing's formulaic precision -- these are all bursty patterns that a model trained to maximize expected reward will sand down. You can partially recover it with few-shot prompting, but the model is fighting its own reward gradient the entire time.

The practical question is whether you can encode a style prior that survives the decoding process. The research on authorship attribution (stylometry) suggests the feature set is well-understood -- function word frequencies, sentence length distributions, type-token ratios, syntactic complexity metrics. But nobody has built a production system that uses those features as a constraint during generation rather than just detection.
by noosphr | 2026-02-22 08:15:51+00:00
You suffer from the typical brain damage caused by using a language without an alphabet.

There is no such thing as spelling in phonetic writing systems because they render what is said, not some random collection of glyphs that approximated how a word was pronounced 500 years ago, in the best case.

If two people with different accents can speak to each other, they can also write to each other under a phonetic writing system.
by taneq | 2026-02-22 08:17:01+00:00
How did you vet the quality of the documentation? I have no doubt that an LLM could produce a great deal of plausible-sounding documentation in short order. Even assuming you’re already completely familiar with the code base, reading through that documentation and fact checking it would take a great deal of effort.

What’s the quality like? I’d expect it to be riddled with subtly wrong explanations. Is Claude really that much better than older models (eg. GPT-4)?

Edit: Oops, just saw your other comment saying you’d verified it manually.
by pests | 2026-02-22 08:17:02+00:00
For comparison I wanted to write on how Google handles MoE archs with its TPUv4 arch.

They use Optical Circuit Switches, operating via MEMS mirrors, to create highly reconfigurable, high-bandwidth 3D torus topologies. The OCS fabric allows 4,096 chips to be connected in a single pod, with the ability to dynamically rewire the cluster to match the communication patterns of specific MoE models.

The 3D torus connects 64-chip cubes with 6 neighbors each. TPUv4 also contains 2 SpareCores which specialize handling high-bandwidth, non-contiguous memory accesses.

Of course this is a DC level system, not something on a chip for your pc, but just want to express the scale here.
by silisili | 2026-02-22 08:17:51+00:00
Same.

This will never change until CEO pay is tied to long term performance. Why not make it 5 year lagging?

The whole problem is that CEOs have zero incentive to care about the longevity of the company. They want share price to go up now, make their money, then cash out.

It's easy to blame the CEOs, but they're just doing what's smart for them. We need to change the definition of what that is.
by generuso | 2026-02-22 08:18:05+00:00
LSI Logic and VLSI Systems used to do such things in 1980s -- they produced a quantity of "universal" base chips, and then relatively inexpensively and quickly customized them for different uses and customers, by adding a few interconnect layers on top. Like hardwired FPGAs. Such semi-custom ASICs were much less expensive than full custom designs, and one could order them in relatively small lots.

Taalas of course builds base chips that are already closely tailored for a particular type of models. They aim to generate the final chips with the model weights baked into ROMs in two months after the weights become available. They hope that the hardware will be profitable for at least some customers, even if the model is only good enough for a year. Assuming they do get superior speed and energy efficiency, this may be a good idea.
by Strilanc | 2026-02-22 08:18:19+00:00
For each chick they do 24 trials divided into 4 blocks with retraining on the ambiguous shape and actual rewards after each block. During the actual tests they didn't give rewards. In figure 1 they show the data bucketed by trial index. It's a bit surprising it doesn't show any apparent effect vs trial number, e.g. the first trial after retraining being slightly different.

I have to admit I'm super skeptical there's not some stupid mistake here. Definitely thought provoking. But I wish they'd kept iteratively removing elements until the correlation stopped happening, so they could nail down causation more precisely.
by clot27 | 2026-02-22 08:19:41+00:00
CIA meddles in elections of practically all 3 of those countries and none of them are openly anti America. If you are liberal bourgeoise democracy you cant be anti america, thats the standard set by epstienite empire, doesnt seem much freedom of choice is given to them? When was the last time america did a coup in those countries and killed their leader?

No one wants their country to be controlled by child eating pedophiles. Its funny when those funding genocide in gaza lecture other cultures about agency
by CodeBit26 | 2026-02-22 08:19:52+00:00
I really like your analogy of LLMs as 'unreliable interns'. The shift from being a 'coder' to a 'software manager' who enforces documentation and grounding is the only way to scale these tools. Without an architecture.md or similar grounding, the context drift eventually makes the AI-generated code a liability rather than an asset. It's about moving the complexity from the syntax to the specification.
by writingdna | 2026-02-22 08:20:31+00:00
The Yegge claim about manual code review being outdated conflates two things: reviewing for correctness vs. reviewing for design coherence. Agents are getting decent at the first (does this function do what the spec says?) but remain weak at the second (does this abstraction fit the existing architecture? will this pattern scale when the next feature lands?).

What actually works for me is treating agents less like autonomous developers and more like very fast typists who need clear architectural guardrails. The heavy lifting is writing the context documents -- architecture decision records, module boundary descriptions, naming conventions -- that constrain the generation. Ironically, the better your documentation, the less you need an orchestrator, because a single agent with good context produces coherent code on the first pass.

The git worktree pattern multiple people mention is underrated. Having each agent work on an isolated branch with automated test gates before merge catches the drift problem at the integration point rather than trying to prevent it during generation.
by FreakLegion | 2026-02-22 08:21:02+00:00
It works because the original filter has suboptimal settings. An optimal filter of that size and number of items would set 5 bits per item and have about a quarter of the false positive rate. The 2 bits per item in the blocked filter is still suboptimal, but it's also saving them from saturating a bunch of 32-bit blocks, at the cost of a much higher overall false positive rate.
by w10-1 | 2026-02-22 08:22:00+00:00
I try these staging-document patterns, but suspect they have 2 fundamental flaws that stem mostly from our own biases.

First, Claude evolves. The original post work pattern evolved over 9 months, before claude's recent step changes. It's likely claude's present plan mode is better than this workaround, but if you stick to the workaround, you'd never know.

Second, the staging docs that represent some context - whether a library skills or current session design and implementation plans - are not the model Claude works with. At best they are shaping it, but I've found it does ignore and forget even what's written (even when I shout with emphasis), and the overall session influences the code. (Most often this happens when a peripheral adjustment ends up populating half the context.)

Indeed the biggest benefit from the OP might be to squeeze within 1 session, omitting peripheral features and investigations at the plan stage. So the mechanism of action might be the combination of getting our own plan clear and avoiding confusing excursions. (A test for that would be to redo the session with the final plan and implementation, to see if the iteration process itself is shaping the model.)

Our bias is to believe that we're getting better at managing this thing, and that we can control and direct it. It's uncomfortable to realize you can only really influence it - much like giving direction to a junior, but they can still go off track. And even if you found a pattern that works, it might work for reasons you're not understanding -- and thus fail you eventually. So, yes, try some patterns, but always hang on to the newbie senses of wonder and terror that make you curious, alert, and experimental.
by qsera | 2026-02-22 08:22:33+00:00
>"Parse, Don't Validate,"

Ah, that pretentious little blog post that was taken up by many as gospel, for some mysterious reason...

This tells me that any idea, even if stupid (or obvious in this case) ones, can go mainstream, if you rhyme it right.

That blog post is like a "modern art" painting by some famous author that totally look a child has flingned some paint to a wall, but every person who looks at it tries so hard to find some meaning that every one end up finding "something"..

In fact the top comment right now express that their interpretation of blog post is different from the author's...

Amusing!
by pjmlp | 2026-02-22 08:22:37+00:00
That is the difference between the US mentality of the winner takes it all that has given us late stage capitalism, entshitification and Trump, and most of the world.

Quality of life and health matters more than anything else.

After a certain point, more money doesn't bring any of that, one is not taking the money into the grave, other than build a mausoleum.
by riffraff | 2026-02-22 08:23:53+00:00
Yeah but the spelling is part of how the language feels :)

Also, you say spelling but e.g. "speken" feels more a grammatical than orthographic difference.

By comparison, Dante's incipit to the Divine Comedy is 100% the same spelling and grammar as modern Italian (nel mezzo del cammin di nostra vita/mi ritrovai per una selva oscura/che la diritta via era smarrita)
by JumpCrisscross | 2026-02-22 08:25:36+00:00
> a clearer way of saying this, as you do, is the West imposed crippling sanctions

The world doesn't revolve around the West. Nobody in America caused the IRGC to engineer a water crisis. Nobody asked for them to murder students in an internet-connected age, like the single thing you do not do if you want to calm things down.

Sanctions have made Iranians poorer. But so has their gerontocratic theocracy pursuing autarky and misguided nuclear ambitions at any cost. Khamenei can't hold open elections because he knows he'd lose.
by JumpCrisscross | 2026-02-22 08:26:41+00:00
> gives the regime a chance to say "see, these people are puppets of the monarchy"

Regime isn't the messaging target. Foreign actors are. And rightly or wrongly, desperate people will choose the icons they have, and the set to choose from is generally those that are helping and those the current regime despises. The first set is scarce. So we're left with the second.
by arcticbull | 2026-02-22 08:26:51+00:00
Deaths in the Great Leap Forward were heavily concentrated as compared to the Industrial Revolution but the death tolls from IR-related famines weren't really all that far off. Industrialization was messy everywhere.

The Irish Potato Famine alone killed 15% of Ireland vs the GLF killing 5% of China.

That's not a reason not to plan 5 years in advance... is it? Any more than the Potato Famine is a reason we should't have capitalism.

I can't say that I've ever heard the argument that a plan led to a famine therefore we should never make plans, when we have great counterexamples that not planning also led to famine. Feels like learning the wrong lesson here.

[edit] I also think it's worth pointing out that America's response to the Dust Bowl was the Farm Bill, which it could be argued is one of the largest-scale examples of central planning in history. It continues to this day, and is part of the reason Americans pay less as a share of their spending on food than any other country on earth.
by appsoftware | 2026-02-22 08:27:56+00:00
This is the flow I've found myself working towards. Essentially maintaining more and more layered documentation for the LLM produces better and more consistent results. What is great here is the emphasis on the use of such documents in the planning phase. I'm feeling much more motivated to write solid documentation recently, because I know someone (the LLM) is actually going to read it! I've noticed my efforts and skill acquisition have moved sharply from app developer towards DevOps and architecture / management, but I think I'll always be grateful for the application engineering experience that I think the next wave of devs might miss out on.

I've also noted such a huge gulf between some developers describing 'prompting things into existence' and the approach described in this article. Both types seem to report success, though my experience is that the latter seems more realistic, and much more likely to produce robust code that's likely to be maintainable for long term or project critical goals.
by Jweb_Guru | 2026-02-22 08:28:36+00:00
> But the aha moment for me was what’s maintainable by AI vs by me by hand are on different realms

I don't find that LLMs are any more likely than humans to remember to update all of the places it wrote redundant functions. Generally far less likely, actually. So forgive me for treating this claim with a massive grain of salt.
by john01dav | 2026-02-22 08:28:41+00:00
In response to the seeing like a bank article, one thing which can make this a lot better is to use asynchronous ticketing or messaging systems instead of phone trees.

At my bank, I can just send a message in the app, even when it's closed, about whatever I want. Then, when the bank opens, someone reads it, and then either handles it, or transfers it. Then, if its transferreed, that person either handles it or forwards again.

The same triaging of basic issues exists, the same tiers described in the article, but the user interfece is wildly
superior. I take 1 minute to write what I need to write, and then a few business hours later, its solved. I don't need to waste my time on hold. I don't need to be instantly available for an undetermined period for a call back. I don't need to explain the same issue repeatedly. If I'm asked a question, I can answer it, and the answer is then attached to the full log that every escalation or transfer has full access to.

This is so much better that I refuse to do business with most businesses that don't offer something like this. I was extremely pissed when a data broker leaked my SSN and I was forced to deal with such institutions to clean up that mess.
by homeboxer26 | 2026-02-22 08:29:18+00:00
The hardware deployment angle is worth thinking about here. A "claw" by definition needs to be persistent - always-on, always-connected. That changes the deployment target compared to a typical web app.

Most people run these on cloud VMs, which works but has a cost and privacy ceiling. The natural alternative is a low-power always-on device at home (think: the RPi homelab crowd, but for AI agents). 15W idle draws running 24/7 cost less than $20/year in electricity.

The naming actually clarifies the hardware requirement in a way "agent" didn't - an agent can be stateless and batch-triggered, but a claw needs to be persistently reachable. That's a different design constraint. Would be curious if anyone's run into issues with consumer ISPs blocking inbound connections for claw-style setups.
by rdiddly | 2026-02-22 08:29:24+00:00
You're probably right but I no longer try to guess what's AI-written. LLMs learned all their bad habits from humans in the first place after all. But for sure I can still tell good writing from shit, so that's how I still look at it. I'd venture very little truly good writing is AI-written, and a lot of shit writing is. So maybe I'm rejecting roughly the same set of things, but just the fact that a thing intrinsically sucks, is enough information for me to act on. I dunno if I'm making sense or why I'm even commenting. Thanks for reading.