MurphyA/hacker-news huggingface dataset:
by verdverm | 2026-02-08 21:34:51+00:00
fyi, why do you find this noteworthy? It is the expected outcome based on my understanding of the trends globally around wealth inequality over more than a decade. That "last place" defines much of rural MAGA, but a lot of them and many more talk about it without race. The elites / oligarchs (though not the words they necessarily use) are more often the cause (maybe as portrayed by the govt and globalists?)

> First, we think it is noteworthy that a very simi-
lar “last place” subjective status profile
emerged at all. This replication, even years
later, suggests that the feeling among some
White Americans that they are “last place,”
even if tied for it, has been a persistent under-
current in U.S. politics
by kinow | 2026-02-08 21:35:45+00:00
I remember learning about IIIE (triple-I-efe) years ago while working with a computer vision researcher that used it to serve images generated with Jenkins pipelines.

Glad to see the project of server I used is still running well. The maintainer was a really nice person to work with too: https://cantaloupe-project.github.io/

It helped me that I was already familiar with some OGC & GIS tiling technologies, as what IIIF is doing is not too different. The image processing layer is different though, as you can zoom in, out, rotate, scale, etc..

There were several JavaScript clients, the one I used was one adopted by a museum, but I cannot recall the name now.
by stavros | 2026-02-08 21:36:47+00:00
This is an educated guess, but I think it becomes less efficient, so it heats up, and then performs better as it heats. I assume this to be the case because I charge my RC plane LiPos the same way every time, and they take the same amount of energy, but flying in the winter gives much shorter flight times. Since the battery is warm after a flight, even in the cold, I don't think the energy is still there the battery is still discharged when I take it home), so it must just be much less efficient and wasting a lot of energy as heat.

I assume it's just that its internal resistance rises when it's cold, but I might be wrong.
by SilverElfin | 2026-02-08 21:37:12+00:00
I am an outsider too but I think there’s a mix of things like:

1. People being richer already due to Silicon Valley pay, think they’re immune to harm. It’s easy to be in a bubble in SF, where life is good, without truly knowing what it’s like to see ICE kidnapping children in black SUVs on the streets of Minneapolis.

2. If someone is fitting to the dominant demographic group (white, male, straight, born in America to citizens, etc.) then there is little empathy or understanding of what others are going through and what risks they face from the current administration and the far right shift in general.

3. Many people genuinely think they will belong to an ultra rich class in the future. They want to get into that same group through startups or whatever. And they don’t want that opportunity to go away.

4. People in tech skew younger. And the young often lack the maturity to understand how the world truly works. Sure the top 1% pays most of the income taxes. But they are also hoarding most of the capital and profits to begin with, so of course they would be paying most of the taxes. Those in this article view the rich as generous for paying the taxes they do, instead of realizing that everyone else is not competing with the super rich in a fair way, because they have to live paycheck to paycheck and any risk is existential.
by kyboren | 2026-02-08 21:37:38+00:00
And from which perfect utopia held back only by the evil West do you hail?

Given your apparent desire to put us in chains to experience pain and suffering, perhaps that's the next place we ought to suppress through threats and force.

It must be great to issue declamations from your holier-than-thou victimhood. It's much easier, too, as you never have to defend anything, because it's always someone else's fault.

PS: Food, medicine, and medical equipment--the essentials--are exempt from the embargo.
by watwut | 2026-02-08 21:37:41+00:00
Streaming killed theater because experience of streaming is just overall better then experience of going to the theater. There I said it.

I have noise control. I can pause it. If I am watching alone I can rewind a scene. I watch when I want and I dont have to go to the mall for it. And it is massively cheaper.

If more of us watch, we can talk to esch other or comment things. Or be silent and not disturbed by somebody else making noise.
by otterley | 2026-02-08 21:38:08+00:00
I'm reminded of the old Usenet responses to people claiming to solve the spam problem, so I can't help myself:

Your solution advocates a
( ) technical (X) social ( ) policy-based ( ) forge-based
approach to solving AI-generated pull requests to open source projects. Your idea will not work. Here is why it won't work. (One or more of the following may apply to your particular idea, and it may have other flaws.)

( ) PR spammers can easily use AI to adapt to detection methods
( ) Legitimate non-native English speakers' contributions would be affected
( ) Legitimate users of AI coding assistants would be affected
( ) It is defenseless against determined bad actors
( ) It will stop AI slop for two weeks and then we'll be stuck with it
(X) Project maintainers don't have time to implement it
(X) Requires immediate total cooperation from maintainers at once
(X) False positives would drive away genuine new contributors

Specifically, your plan fails to account for
(X) Ease of creating new GitHub accounts
(X) Script kiddies and reputation farmers
( ) Armies of LLM-assisted coding tools in legitimate use
(X) Eternal arms race involved in all detection approaches
( ) Extreme pressure on developers to use AI tools
(X) Maintainer burnout that is unaffected by automated filtering
( ) Graduate students trying to pad their CVs
( ) The fact that AI will only get better at mimicking humans

and the following philosophical objections may also apply:
(X) Ideas similar to yours are easy to come up with, yet none have ever
been shown practical
(X) Allowlists exclude new contributors
(X) Blocklists are circumvented in minutes
( ) We should be able to use AI tools without being censored
(X) Countermeasures must work if phased in gradually across projects
( ) Contributing to open source should be free and open
(X) Feel-good measures do nothing to solve the problem
(X) This will just make maintainer burnout worse

Furthermore, this is what I think about you:
(X) Sorry dude, but I don't think it would work.
( ) This is a stupid idea, and you're a stupid person for suggesting it.
( ) Nice try, assh0le! I'm going to find out what project you maintain and
send you 50 AI-generated PRs!
by op-collective | 2026-02-08 21:38:24+00:00
Hey HN,

I've been running AI as a de facto team member in my business for the past 6 months — not the "ask ChatGPT a question" variety, but with actual job descriptions, SOPs, onboarding docs, and defined deliverables.

The core insight is boring: most AI underperformance is a management problem, not a technology problem. When you give an LLM the same structured context you'd give a new hire (role definition, brand docs, quality checklists, feedback loops), output quality and consistency improve significantly.

The playbook covers:
- Writing an AI job description (what it owns, what it doesn't)
- Onboarding documents and context management
- SOPs for recurring workflows
- Quality control and feedback loops
- When to use AI vs. when you still need a human

Would love feedback from anyone who's done something similar — curious how others are handling context persistence across sessions and quality degradation over time.
by D-Machine | 2026-02-08 21:39:41+00:00
> It has little to do with the reality of that language or the correctness of your model of it, but rather with the need to train realtime circuits to do some work.

To the contrary, this is purely speculative and almost certainly wrong, riding a bike is co-ordinating the realtime circuits in the right way, and language and a linguistic model fundamentally cannot get you there.

There are plenty of other domains like this, where semantic reasoning (e.g. unquantified syllogistic reasoning) just doesn't get you anywhere useful. I gave an example from cooking later in this thread.

You are falling IMO into exactly the trap of the linguistic reductionist, thinking that language is the be-all and end-all of cognition. Talk to e.g. actual mathematicians, and they will generally tell you they may broadly recruit visualization, imagined tactile and proprioceptive senses, and hard-to-vocalize "intuition". One has to claim this is all epiphenomenal, or that e.g. all unconscious thought is secretly using language, to think that all modeling is fundamentally linguistic (or more broadly, token manipulation). This is not a particularly credible or plausible claim given the ubiquity of cognition across animals or from direct human experiences, so the linguistic boundedness of LLMs is very important and relevant.
by bananaflag | 2026-02-08 21:40:19+00:00
I discovered Nancy Drew last week. I knew about it vaguely for years, but now I watched They Cloned Tyrone, which has a character who is a big fan, which I found endearing, so I read the first 4 books (which are now in the public domain).

I am not going to read more because I don't like that she never ages. If you want a normally-aging female detective series, check out Judy Bolton.
by alibarber | 2026-02-08 21:40:27+00:00
Quite a lot of interesting stuff - for example there are mesh networks setup worldwide that attempt to run IP over RF using these - and then use the internet to forward packets from one to another.

They also offer simpler ‘turn-key’ wireguard tunnels too for things like Web SDR setups.

For BGP direct announce in practice it seems to be in the spirt of non-commercial ‘self learning and experimentation’ which is what a lot of legislatures around the world do use as their base definition for the ‘amateur’ in amateur radio. So I guess much like having slices of radio frequencies reserved for it, we’re lucky there are slices of address space reserved for this.
by mikenew | 2026-02-08 21:40:29+00:00
Pretty much every software engineer I've talked to sees it more or less like you do, with some amount of variance on exactly where you draw the line of "this is where the value prop of an LLM falls off". I think we're just awash in corporate propaganda and the output of social networks, and "it's good for certain things, mixed for others" is just not very memetic.
by computomatic | 2026-02-08 21:41:04+00:00
> merely matching the cost and harms of the existing system is far from enough

The new system needs to be better but that doesn’t necessarily mean safer.

For delivery, that could mean cheaper and faster and more convenient.

Autonomous vehicles are a special case because those accidents tend to cause death and serious injury. As long as delivery drones can avoid killing multiple people per year, they are probably fine to compete on other metrics.
by td3rl | 2026-02-08 21:41:11+00:00
ByteDance recently shared a preview of its Doubao mobile assistant. While still early-stage, the demos highlight several workflows that current phone assistants struggle with, such as multi-step price comparison across sellers, real-world interactions and trip-planning flows.

Stepping back, this is NOT an incremental upgrade to a “voice helper” and more like an early signal toward an OS-level agent paradigm. However, ByteDance positioned this as a technical preview with limited access, which seems consistent with two possibilities (not mutually exclusive):
(1) The underlying capability may be ahead of broader ecosystem readiness.
(2) The system itself may still struggle with the long tail of real-world tasks, especially given the complexity and heterogeneity of existing apps and services.

Expanding on the second point: once an agent interacts with a wider set of previously unseen apps, it likely runs into recurring challenges such as:

- app policy constraints
- rapidly changing UIs
- security boundaries
- inconsistent execution reliability
- tasks requiring constantly performing the "right" actions over 1 hour. (long-horizon tasks)

If that’s the case, it seems plausible that these constraints eventually need to be reflected directly in training and evaluation, including the ability to replay and stress-test complex, failure-prone tasks.

Two questions jumping into my mind:

1. Over the next 6–12 months, do we expect more companies to build reinforcement-learning-style environments specifically for phone or app interaction? We've witnessed the early saturation of env companies in the browser and coding space, is this gonna happen again in the phone space?

2. From the app side, do you anticipate more openness toward agent access (e.g., standardised interfaces or MCP-like abstractions), or a shift toward tighter, more restricted integrations?
by csense | 2026-02-08 21:41:11+00:00
There needs to be a legal means for property owners to keep drones off their property -- maybe some kind of "no trespassing" beacon that acts a machine readable "no trespassing" sign? -- and recourse to deal with unwelcome drones.

I was watching a YouTube bodycam video showing police interaction with a guy who got upset that a Walmart delivery drone test was being performed on his property without permission. He shot the drone with a shotgun. I forget if he was arrested on the spot, but I think he got in huge legal trouble -- apparently in the US, shooting at a drone is treated the same as shooting at a manned aircraft, and he might have ended up getting multiple years in prison.

Shooting a human trespasser has a pretty high legal bar, and rightfully so. Shooting a robotic trespasser seems like it shouldn't carry prison time, even if unjustified it should only carry financial penalties. Especially if the law doesn't specify any peaceful recourse to get rid of unwanted robots trespassing on your property.
by D-Machine | 2026-02-08 21:41:30+00:00
> In practice it would make heavy use of RL, as humans do.

Oh, so you mean, it would be in a harness of some sort that lets it connect to sensors that tell it things about its position, speed, balance and etc? Well, yes, but then it isn't an LLM anymore, because it has more than language to model things!
by bryanlarsen | 2026-02-08 21:41:41+00:00
I don't imagine the difference is very significant on long drives. If the car is cold soaked at -30, it uses about 10kW for the first 3km. Then everything is warmed up, and the ~25% difference is increased consumption, not decreased battery capacity.

As long as you have a heat pump harvesting the waste heat to keep the battery up to temp.

But might be significant on short drives, 10kW for the first 3 km is massive.
by threecheese | 2026-02-08 21:41:51+00:00
For the first, I think maintaining package-add instructions is table stakes, we need to be opinionated here. Agents are typically good at following them, if not you can fall over to a Makefile that does everything.

For the second, I totally agree. I continue to hope that agents will get better at refactoring, and I think using LSPs effectively would make this happen. Claude took dozens of minutes to perform a rename which Jetbrains would have executed perfectly in like five seconds. Its approach was to make a change, run the tests, do it again. Nuts.
by BobbyTables2 | 2026-02-08 21:41:59+00:00
It’s the externalized costs that bite society in the end.

The short life boots are great for everyone (boot makers, suppliers) except the end user.

A slightly higher quality boot could reduce their expenditure (monetary and time) and collectively allow society to devote the time and resources saved to higher goals.

However the wants of the few outweigh the needs of the many.
by adrian_b | 2026-02-08 21:42:30+00:00
The maximum deliverable power depends on electrode area, through the maximum current density.

The capacity of storing energy does not depend at all on area, but only on the mass of sodium contained in the battery and on the efficiency of using it (i.e. between full discharge and full charge not 100% of the sodium or lithium is cycled between the 2 oxidation states, but a fraction, e.g. 90%).

Any battery has both an energy density and a power density, which are weakly correlated and the correlation may have opposite signs, i.e. for some batteries it may be possible to increase the power density if the energy density is lowered and vice-versa.

For a given stored energy in kWh, the required mass of sodium is several times greater than the corresponding mass of lithium, by a factor that is the product of the atomic mass ratio with the ratio between the battery voltages. The voltages are similar, with a slight advantage for sodium, so the required mass of sodium is about 3 times the corresponding mass of lithium.

If the complete batteries have about the same mass, that means that other components of the sodium-ion battery are smaller and/or lighter.
by alephnerd | 2026-02-08 21:42:33+00:00
This is a dumb article that ignores the shift in terms and structuring of early stage deals à la the Rich vs King tradeoff [0].

Investors and Employees both have an incentive for an exit. Founders on the other hand have an incentive to remain in control of a company as long as possible.

Enough funds and employees are pissed that the 2018-23 era vintage of late stage/growth equity rounds like Stripe, Databricks, etc led to terms that were extremely founder friendly but negated both early stage investors and employees ability to exit.

The era of the rockstar CEO founder like Zuckerberg is dead becuase no investor or employee wants to put capital in an organization which the founder has structured so that they may remain in control in perpetuity with no interest to exit - thus leaving investors and employees with stock options essentially holding the bag.

This is also why there have been a large amount of board changes and litigation over the past 2-3 years as funds are now starting to hit their 10 year vintage, fund IRR metrics need to be hit, and continuation funds can only go so far.

[0] - https://www.hbs.edu/faculty/Pages/item.aspx?num=38550
by tzs | 2026-02-08 21:42:42+00:00
Then be careful to never do anything that is interesting enough or important enough that it will become newsworthy, or write any books or articles on interesting or important topics, or even posting helpful things on social media.

There are a lot of people in Epstein's email history who are there because the above kinds of things caught his interest, and he wanted to discuss or recommend them to others.
by sdoering | 2026-02-08 21:43:05+00:00
I can mightily relate. The would pay my bill. I just value my time higher than 190€ for navigating a shitty XLS file and the unnecessary comms afterwards. Yes, abso-f*ing-ly a position from privilege. That's why at the next opportunity, me having to travel in 2 weeks, I will use the time and my trusted LLM accomplice to engineer a solution that afterwards will probably be used by a few more people.
by RealityVoid | 2026-02-08 21:43:25+00:00
You're not going crazy. That is what I see as well. But, I do think there is value in:

- driving the LLM instead of doing it yourself. - sometimes I just can't get the activation energy and the LLM is always ready to go so it gives me a kickstart

- doing things you normally don't know. I learned a lot of command like tools and trucks by seeing what Claude does. Doing short scripts for stuff is super useful. Of course, the catch here is if you don't know stuff you can't drive it very well. So you need to use the things in isolation.

- exploring alternative solutions. Stuff that by definition you don't know. Of course, some will not work, but it widens your horizon

- exploring unfamiliar codebases. It can ingest huge amounts of data so exploration will be faster. (But less comprehensive than if you do it yourself fully)

- maintaining change consistency. This I think it's just better than humans. If you have stuff you need to change at 2 or 3 places, you will probably forget. LLM's are better at keeping consistency at details (but not at big picture stuff, interestingly.)
by SpecialistK | 2026-02-08 21:43:49+00:00
I've been thinking about this recently and I disagree. Keep biometrics and know how to disable them quickly (usually 5x power button)

I think the most likely case where you'll be compelled to hand over your device is an airport immigration desk / room. And what do airports have? Lots and lots of CCTV. From the moment you step off the plane or jetway into the terminal there are cameras everywhere. Enter your PIN once in view of those cameras and it's on record for forensics to pick up.

I actually hate when my phone requires me to enter my PIN on public because I have to angle it away from cameras and eyes like I'm looking at smut.
by famouswaffles | 2026-02-08 21:43:55+00:00
>LLMs are language models, something being a transformer or next-state predictors does not make it a language model. You can also have e.g. convolutional language models or LSTM-based language models. This is a basic point that anyone with any proper understanding of these models would know.

'Language Model' has no inherent meaning beyond 'predicts natural language sequences'. You are trying to make it mean more than that. You can certainly make something you'd call a language model with convolution or LSTMs, but that's just a semantics game. In practice, they would not work like transformers and would in fact perform much worse than them with the same compute budget.

>Even if you disagree with these semantics, the major LLMs today are primarily trained on natural language.

The major LLMs today are trained on trillions of tokens of text, much of which has nothing to do with language beyond the means of communication, millions of images and million(s) of hours of audio.

The problem as I tried to explain is that you're packing more meaning into 'Language Model' than you should. Being trained on text does not mean all your responses are modelled via language as you seem to imply. Even for a model trained on text, only the first and last few layers of a LLM concerns language.
by lelandbatey | 2026-02-08 21:44:33+00:00
The idea is that sustained and recurring communication would have a cost that quickly drops to zero. But establishing a new line of communication would have a slight cost, but which would quickly drop to zero.

A poorly thought out hypothetical, just to illustrate: Make a connection at a dinner party? Sure, technically it costs 10¢ make that initial text message/phone call, then the next 5 messages are 1¢ each, but thereafter all the messages are free. Existing relationships: free. New relationships, extremely cheap. Spamming at scale: more expensive.

I have no idea if that's a good idea or not, but I think that's an ok representation of the idea.
by selesphy | 2026-02-08 21:44:44+00:00
Both OpenAI and Sam stated they had no plans for Sunset 4o, yet it was suddenly removed from ChatGPT app. It's noteworthy that 5 and 5.1 were given three months to prepare, while 4o was only given two weeks. This raises serious questions about OpenAI's motives. Should a company that treats users this way have any regard for its business reputation?
by codexon | 2026-02-08 21:45:15+00:00
I think some of it might be genuine. For people that don't code (like management), going from 0 to being able to create a landing page that looks like it came from a big corporation is a miracle.

They are not able to comprehend that for anything more complicated than that, the code might compile, but the logical errors and failure to implement the specs start piling up.