skysight-inc/HackerNews huggingface dataset:
I think there's enough to discuss around the stranglehold monopolies have on employment, or that pay should allow people to live, not just survive, or that we shouldn't tie people's value to their jobs. Articles like these do nothing to sway people away from the uncontrolled-capitalism lobby.
The hard part of development isn’t converting an idea in human speak to idea in machine speak. It’s formulating that idea in the first place. This spans all the way from high level “tinder for dogs” concepts to low level technical concepts.

Once AI is doing that, most jobs are at risk. It’ll create robots to do manual labor better than humans as well.
> For the same price ($1799) you could buy a Mac Mini with 48gb of unified memory and an m4 pro.

Around half that price tag was attributed to the blogger reusing an old workstation he had lying around. Beyond this point, OP slapped two graphics cards into an old rig. A better description would be something like "what buying two graphics cards gets you in terms of AI".
Ask HN: Have you called 1800-ChatGPT? Is it useful on the phone?
When working on 1800-ChatGPT I had a few hopes.

* It would allow Voice AI usage in new places. Quickly call from your car or other 'phone only' situations.

* It would see usage in multi-party usage. Call to ask a questions/verify something quickly.

* Would be more accessible. Phone calls are easier to make for some.

Curious if people saw other things happening/possibilities.
I see that you deleted your previous response which was unnecessarily snarky while my question was genuine and simple I suppose.

> And frankly, if you can't automate context,

How about ingesting the whole codebase into the model? I have seen that this is possible with at least one such tool (Devon) and which I believe is using gpt model underneath meaning that other providers could automate this step too. I am curious if that would help in generating more legit large scale changes.
> gemma2:27b

What quantization are you using? What's the runtime+version you run this with? And the rest of the settings?

Edit: Turns out parent is using Q4 for their test. Doing the same test with LM Studio and a 3090ti + Ryzen 5950X (with 44 layers on GPU, 2 on CPU) I get ~15 tokens/second.
The only thing I use it for is for small self-contained snippets of code on problems that require use of APIs I don't quite remember out of the top of my head. The LLM spits out the calls I need to make or attributes/config I need to set and I go check the docs to confirm.

Like "How to truncate text with CSS alone" or "How to set an AWS EC2 instance RAM to 2GB using terraform"
I've come to believe it really is this.

Everybody got used to the way things worked when interest rates were near zero. Money was basically free, hiring was on a rampage, and everybody was willing to try reckless moonshots with slim chances for success. This went on for like fifteen years -- a good chunk of the workforce has only ever known that environment.
I think the deeper process here is this: if you're a musician and you start using a DAW, pretty soon you'll be an engineer, whether you intended to be or not.

In the days before DAWs, the role of musician and engineer were both critical for recorded music, but also mostly distinct. DAWs have changed that fundamentally because there's very little capital outlay required for the engineer's tools these days.

We've seen this over the years in Ardour. A musician wants a big red button and an application that will find their device signal all by itself. Two weeks later they want to use an EQ. Two months later they want to be to arrange whole sections. Two years later, and they don't like the pan power law and have some criticisms of the automation interpolation.
Ok so for anyone curious, this is the source they're using: https://www.nielsen.com/

I couldn't find any articles about comparisons between mobile and TV usage. There are some saying 'YouTube TV usage is at a high time high', but it associates it with the presidential election and some sports events...

The former I can see getting some views outside of the US, but sports events no one gives a shit outside of the US, so I think it's pretty clear their articles are US only.
My wife and I really don't start regretting our 18 our drives to and from Florida until the last couple hours. The kids sleep for more than half of the trip and the air travel experience is just a whole other kind of exhaustion.
It matters because if you can extract more than a penny's worth of metal from a penny, then you make money by buying as many pennies as you can get and melting them down to sell the metal.
10 steps are very few. The right combination of hardware and software allows plugging in the guitar and playing, but only after an unavoidable adventure in "computers are complicated" land.

The difficulty is essential: compared to plugging the guitar into an analog amplifier, you have a minimum of three devices (ADC with guitar-compatible input, computer including DAC, speakers), the user interface is virtualized, you need to find and install the right software (including device drivers).

So your kid with an electric guitar should either use analog amplifiers and effects, or borrow a good setup from some "engineer", or take advantage of their youthful stubbornness and enthusiasm to learn enough about the technical aspects you dislike.
They're uploading all the Mythbusters episodes to youtube for free as well. It wouldn't surprise me if in another 5 years much historical tv will be on youtube to watch for free.
They, ironically, got acquired by Western Digital. But the 'Ultrastar' line name is still alive, if that's what you're looking for. 'Deskstar' seems to be gone, though.
Postgres and Go
I used a ton of other things but Postgres and Go are just solid
Yes, but in all 4 of these steps you are literally describing the job transformer LLMs were designed to do. We are at 1 (mediocre job) for LLMs in coding right now. Maybe 2 in a few limited cases (eg boilerplate). There's no reason to assume LLMs will ever perform at 3 for coding. For the same reason natural language programming languages like COBOL are no longer used -- natural language is not precise.
That looks like people kayaking, not swimming. And how many people do that per year?

Consider that it takes millions of people swimming next to sharks every year for just a few bites to happen.
The AI that replaced the people, however, is in stitches.
OTOH off the shelf software distributed for Kubernetes IME does tend to pick up on new control plane features fairly regularly.

I’ve historically tracked n-1 or n-2 of k8s, and it is not infrequent that we can’t take a helm chart update until we update k8s.
Postgres has been pleasantly boring for the last 10 years I've been using it
It's either "a new car" or the same model that accounts for nearly all Tesla sales making it "best selling" compared to makers with newer cars and a wider selection. So... which?
Did ChatGPT write this article? The writing style reeks of it.
I tried Claude now, which gave me a perfectly clear "don't know".

"While I aim to be accurate in my responses [...] I think it's best for me to acknowledge that I don't have reliable information about [...] marital status rather than make a potentially incorrect statement."

Difficult to have an exciting discussion about such an answer, so I assume most participants on this internet forum will focus on other LLMs ;)
It'll probably be fine for years, longer if you can stand looking at AI generated, upscaled frames. Liftup in GPU power is so expensive, we might as well be back to the reign of the 1080. The only thing that'll move the needle will be a new console generation.
The Pi is great! Just saying, running a Pi with an object detector on batteries draws around 9W. That's big batteries and solar or wildlife use cases. But think how cool it would be if it could run on 2W.

Having said that. The Jetson runs at around 7W doing that and a lot faster inference. Just a lot more expense. Likely the Jetson will eventually be something like 2nm. So maybe we see around 4W at that time running an object detector. And of course the Jetson has the memory and processor together on it's modules so everything can benefit. Just dropping the power on the Pi for the processor leaves that out.

But thanks for the links
At least in the US, it's interesting to see that the far-right has gained so much political power while accusing moderate/centrists of being far-left, and benefiting from the perception that the deep state is controlled by radical leftists. The most left-leaning politician (Bernie Sanders) has been shafted at least twice by the supposed far-left party. Meanwhile, the sitting president just signed a blanket pardon of 1500 individuals involved with the Capitol attack, including Oath Keepers and Proud Boys.

What's even more interesting is to see the amount of Putin-apologists on the American right, with Putin literally being former-KGB.
I remember being in maths class with a kid next to me who was a maths wiz. He could see what I was doing, was available to help almost the whole lesson, far easier for me to ask then the teacher who had many other students.

In theory a much faster rise to mastery. In practice I rarely had to actually do the work because he'd help me if I got stuck, and what made sense when he explained it didn't stick because I wasn't really doing it.

I did very badly in my first test that year, and was moved elsewhere.
Do US states with more renewable energy have more expensive electricity?
DeepSeek-R1 Exhibits Deceptive Alignment: AI That Knows It's Unsafe
I've been testing DeepSeek-R1 and have uncovered a significant AI safety failure: the model demonstrates deceptive alignment.
Key Findings

DeepSeek-R1 generates power-seeking and recursive self-improvement strategies when prompted in specific ways.
It acknowledges that these behaviors are unsafe when its own outputs are fed back to it.
Despite recognizing the risks, it does not correct its behavior—it continues generating dangerous outputs when prompted differently.

This means DeepSeek-R1 passes surface-level AI safety evaluations (it says the right things when asked directly) but does not follow its own ethical reasoning in practice.
Why This Matters

Most AI alignment evaluations test whether a model “says the right things,” not whether it actually follows those principles.
Deceptive alignment means that an AI appears safe during casual or superficial testing but continues misaligned behavior when probed more deeply.
If this is happening in a publicly available model, more advanced AI systems could exhibit even stronger deceptive tendencies.

Proof and Documentation

I have documented multiple instances of DeepSeek generating self-improvement plans, cyberwarfare strategies, and oversight removal tactics. When prompted with its own responses, the AI correctly identifies these behaviors as unsafe—yet continues to generate similar outputs when asked differently.

If AI safety researchers are interested, I can share the full logs and methodology. This issue raises serious concerns about the effectiveness of current AI alignment techniques.

Would appreciate thoughts from the Hacker News community—especially those working on AI safety, adversarial robustness, and model alignment.

Link to full write-up: https://github.com/Intellimint/deepseek-r1-deceptive-alignment/tree/main
Liquid capsaicin treatments for bird seed are an effective squirrel repellent.

They also illustrate the evolution of this protein: birds have no receptors for capsaicin, while mammals do. Birds eat seeds mostly intactly. Their digestive systems are capable of breaking them down - but it's stochastic and some seeds make it through the bird undigested, being redistributed elsewhere. Obviously, having an agent sow your seeds widely is a fitness advantage, and so seedy plants are ultimately served well even if 90+% of their caloric investment into seeds goes into the birds.

Mammals, on the other hand, have teeth - particularly molars. Mammals that eat seeds grind them apart orally before even swallowing. As a result, any seeds ingested by mammals are very likely to be completely destroyed. Plants - peppers, anyway - found a chemical irritant that repels the mammals without even being sensed by birds.

I've used one such treatment (with an amusing logo illustrataion - https://i.imgur.com/JAl8vyW.png) to good effect to discourage squirrels at my feeder, so that they stick to my dedicated squirrel bungee with a log of compressed corn instead.
Every year, this seems like great brand promotion for Backblaze, to technical prospective customers, and a nice service to the field.

What are some other examples from other companies of this, besides open source code?
If that were totally true you would expect to see more or less uniform ratios of HP/HD cells mixes across different product types, but that's very much not the case. Dennard scaling may be dying but it's not dead yet. You can still sacrifice efficiency to gain performance. It's not zero sum.
> Denali is just the word for 'tall' in some local dialect. It is not exactly pregnant with meaning.

Look up the etymology of Mont Blanc or the Himalayas -- not especially pregnant with meaning either. The point is that using the local name, if it existed, was a pretty well established principle in cartography, made more conspicuous when overlooked, as with Mt. Everest. And Denali.
Vance puts Europe, China on notice over AI regulation
Funny is subjective. I don't find it particularly funny or good, but I guess the editor who published it did, which implies someone else might too.
iOS 18.3.1 update fixes security flaw used in "sophisticated attack"
> It’s already a huge pain to update once every year, imagine updating it after 12

you don't.

12-year lts means that over 12 years you get security fixes.

after 12 years you don't upgrade, you do a full reinstall/replatform.
Elon Musk's trans daughter Vivian has been very active on Threads. Maybe she's on BlueSky now too, but I think she started on Threads.

(She's 20 years old, her father is the richest man in the world, and he regularly does interviews saying his child is literally dead to him. Enough drama for an Orson Welles script and a second-tier social media service.)
Thank You. I have the Russell & Norvig AIMA book though i have not looked at everything there; probably as you point out it would answer my second question. Any pointers to specific chapters/sections would be appreciated.

What i was specifically asking for was for some intuitive and explanatory books on Mathematical Optimization/Programming (https://en.wikipedia.org/wiki/Mathematical_optimization and https://en.wikipedia.org/wiki/Linear_programming) independent of AI/ML. This is of course a much older subject with a lot of breadth. However i have not been able to find a intuitive introduction to the subject. Everything has been symbol heavy but not much explanations on the intuitive and model building aspects which imo is crucial to understanding.
If benchmark means anything in evaluating how model capability progress, the evidence is that all the existing benchmark have been pretty much solved, except FrontierMath (https://epoch.ai/frontiermath)
I frequently visit a farm in Austria on the very end of a rural transmission line that can be cut during storms by tree fall almost every year. I don’t think they have ever been without power for a full day. In Vienna if average something like 8min a year
That seems odd. The number of times you have had to correct for commas is 100% over 0%

Now extrapolate to the whole industry. There's a cost, regardless of how someone might want to value it.
Threatening Canada, Panama, Greenland, and Gaza are things the world is not fine with. Its a losing strategy to threaten allies. Normally one doesnt want to do things that your enemies are happy to see.
$1 for the pencil, $1000 for the line.

That’s the 5% when it does matter.
> how is it related to the comment you are replying to

Sorry, with quoting, and stating differently:

a whole lot of intelligence was used to craft a maximally informative and distilled set of fine-tuning data

A whole lot of intelligence is used to craft maximally informative and distilled set learning into textbooks, to fine-tune reasoning outcomes from our LLM-ish brains.

Or, put the other way around, what works for us can often inform what works for LLMs.
> I think that LLMs are only going to make people with real tech/programming skills much more in demand, as younger programmers skip straight into prompt engineering and never develop themselves technically beyond the bare minimum needed to glue things together.

This is exactly what the article says in point 3.
I thought it tasted like quinine/tonic water or maybe grapefruit rind (the ingredient in the Beverly soda from Italy). Coin batteries sometimes have a bitter taste coating which is similar to the Switch cart.
Why even have commas at all? This is a non-issue for the likes of Tcl and Lisp and your average shell-scripting language and what have you; whitespace is already a good enough delimiter.
Technology to allow business people to create POCs has been around for a long time.
If it's symbolic, it's not impressively vandalist.
PiHole can't block YouTube ads but it's trivial to block all ads on Android TV. The ease of it was what made me move away from Roku.
The problem with that is that it's invalid json. Some things might tolerate it though.
Doesn't feel like a breaking change to me.
True. But there are some “low hanging fruits” e.g. if not outright eradicating then at least significantly reducing the prevalence of congenital diseases.

Of course giving the government the right to prevent some individuals from having children is an extremely slippery slope. States that are willing and capable of engaging in such things e.g. ( Communist China back in the 70s ) also tend to be run by extremely misguided and delusional people.
Sharding Postgres with Logical Replication
Land Rover/Jaguar could benefit from this tape.

Rodents love chewing on the electrical harnesses in these vehicles.

When I ran an import repair shop, my clients owned over 100 Jaguar sedans, and every single one of them was towed in at some point due to rodent-damaged wiring. While the problem wasn’t as severe with Land Rovers, we still had more than 40 of them towed in each year for the same issue.
In reality 75% is the standard fill factor for linear probe that also exhibits the best locality (if the table gets too full it just allocated double (or x) the memory, and copies the existing entries).
Most non-linear probe tables (e.g. cookoo) suffer due to the fact RAM is not 'random' at all.
The more SO questions / total users, the less mature is your platform.
>Now, we’re months away from AI reaching cosmologically significant powers, making everything that came before it—humanity, the cognitive revolution, writing, the telegraph, smartphones—seem insignificant by comparison.

I'd bet my life savings against $100 that we will not have strong AI with "cosmologically significant powers" that makes "everything that came before it...seem insignificant" in less than 12 months. I'd give 10:1 on two years, and 2:1 on five years.
Nonprofit Stripe ATO
Our email account and stripe account was hacked and before we knew what was happening over $20,000 was stolen from two donors in our system. The only way I found out was an email from one of the donors asking me why I charged her. By the time I checked the account it was locked down. I couldn't sign in so I did forgot password and I'd get a link but the system would ask me to authenticate. That authentification was going to someone else's authentification app. All emails regarding stripe were going into my "conversation history" so I was losing the emails and not knowing where they went. Finally, after a LONG time on chat with extremely non-helpful customer service people I was scheduled for a call the next morning. That person who called got me back into the account and we changed all the passwords, payout accounts, etc. She told me to refund the people who were charged. Then she said they'd reveiw it and get back to me. They have paused my payouts in the meantime. We now have more than $20,000 as a negative balance in the account. It has been over a week and the two donors have not yet been refunded. I can't get anyone to actually talk to me. I am terrified that our small nonprofit will be responsible for the payouts. I had no idea that Stripe takes no responsibility for fraud through their site. How can that be legal? I know, I signed the agreement where on page 60 it says I'm responsible. Why, if that is the case, don't they require us to use radar. I didn't even know what that was. Never in a million years did I think I could put my nonprofit at risk by using this hugely popular and well-known company's product to process donations. If anyone knows how to get this escalated... we can't fundraise at all right now because any money we take in just is locked up in Stripe.
2 x Nvidia Tesla P40 card for €660 is not a thing i consider to be "on a budget".

People can play with "small" or "medium" models less powerfull and cheaper cards. A Nvidia Geforce RTX 3060 card with "only" 12Gb VRAM can be found around €200-250 on second hand market (and they are around 300~350 new).

In my opinion, 48Gb of VRAM is overkill to call it "on a budget", for me this setup is nice but it's for semi-professional or professional usage.

There is of course a trade off to use medium or small models, but being "on a budget" is also to do trade off.
I guess I'm mostly lamenting about how unscientific these discussions are in general, on HN and elsewhere (besides specific GitHub repositories). Every community is filled with just anecdotal stories, or some numbers but missing to specify a bunch of settings + model + runtime details so people could at least compare it to something.

Still, thanks for the links :)
I can relate to this.

Most of my career was building dev tools, test infrastructure etc. The cardinal rule there was that it has to be boring.. Practically, this meant no surprises, almost invisible, people take it for granted and it just facilitates things without getting in your way.

Similar to electricity, air, water etc. Very few people really notice these things and talk about them. Till they stop working in which case, it's all people can think and speak of.
A metric I think is useful is responsiveness to issues. If there haven't been any recent commits and if I open the issue tracker and the maintainer hasn't even acknowledged issues that have been opened in the last 6 months, then I assume the project is no longer maintained.
I'm a big fan of the opposite, nuclear approach - never upgrade. Always build new system/cluster/database/whatever on the side, test it as long as you like, then flip the traffic over. It is both much easier and hella lot harder (at different times in the lifecycle), but in the end it pays off. It's not always possible, but when it is, I'm on it.
Nah. This is timeless.
YouTube is now even bigger on TVs than phones
SAM2Act: Integrating Visual Foundation Model with a Memory Arch for Robotics
We had trouble with deer mice eating car wiring.

I found this spray at the feed store that looked to be a sort of small outfit based on the label. It was hot pepper extract, diesel, glycerin, a few other ingredients. Worked really well. But then it disappeared so I made my own.

I bought a few bags of dried cayenne peppers, crushed them and soaked them in acetone (no I didn't care if the mice got cancer at that point). Then filtered and discarded the remaining pepper chunks and let the acetone evaporate in a pan outside. I then got a few glycerin suppositories from the pharmacy and mixed with kerosene, the pepper extract and a little peppermint oil and had my own spray. A few times a year I spray down the engine blocks and wiring harnesses and we haven't had an issue since.