skysight-inc/HackerNews huggingface dataset:
The nuts and bolts will be embeddable DSL’s, they are the only code which does not rot. Put them in a hierarchy with one compiling down into another or several and you have your building.
Arranging facts into a narrative with mass appeal is the craft of journalism.
So happy humans will be able to stop using their brains soon due to AI !
Nice. Advertisements is one of the first things I studied seriously, when still in high school almost thirty years ago. I remember arriving at the very same conclusion, even though Big (AD) Tech had yet to arrive. Any hypothetical rational and enlightened society in the future - think Star Trek - would of course not have any advertisement. It just doesn't make sense. It is a compromise, an evolutionary transition, like fascism, human sacrifices or settling conflicts with a duel of pistols.

If we - as in humanity - are still there in 500 to 1000 years, advertisement may be taught in a history class as one of the barbaric practices of the 21th century. Maybe some scholars will be able to relate it to world hunger, climate change and genocide with a mathematical precision that we are not yet capable of. That is a timeline I love to think about.

Of course, slaving away in the asteroid mines for Bezos inc., looking at hyper sexualized ads for a trip to Mars is equally likely.
It's also how you get The Culture and The Affront.

Fiction is about interesting tales, not about realistic forecasts — TOS Khan was supposed to have ruled in the Eugenics Wars of the 1990s.
Things AI Will Never Understand [video]
The terminology came about because people didn't like them being called "illegals".
Yet another reason to ban paid ads.
Actually when I was gutting salmon in Alaska, making pizzas at Godfather's, mowing lawns, working as dishwasher in the dorms to pay tuition ... these all were much less stressful jobs that I look back on almost fondly. (Well, maybe not the cannery.)
Any number under 100% is also a vanity metric. Focus on why there are test holes and whether they matter.
>All of this complexity is there for a reason

Having gone from junior Web designer/developer to CTO/CPO and then into startups over the last 25 years, I'm absolutely convinced that the reasons for complexity in what we do day to day now is for no good reason other than CV building for FAANG type job hunting, job niche building and job security self-indulgence, and a fundamental disregard for maturing the industry.
After so many observations why is multi messenger still n=1?
I'm honestly not sure what you are saying.

My point was really just to say that it's good to say "If this brings X at the cost of Y, then it may be worth it" (that raises great questions), but it is wrong to conclude just from that that it actually is worth it.

I see many people jump to this conclusion, and the logic is flawed. I mentioned Trump because I've heard many people justify their voting for Trump like this.

The correct way of doing it is:

1. "If this brings X at the cost of Y, then it may be worth it"

2. Investigate whether it would actually bring X.

3. Investigate whether it would actually cost Y.

4. Decide whether it's worth it or not.
Here is my Law concerning humans, and technology.
If it can be done, it is bieng done. If it's possible to do, many people are working out how to do it. If something is physicaly impossible to do and violates the known laws of physics, then many people are trying to do it.
Gene edditing is totaly doable, with the financial barriers in free fall, so it's monsters and magicians time comming up, with the ancient justification of "if we dont, then they will...first"...Homo Geneticus here we come.
Disscussions on right/wrong, ethics and morality, are of course not bieng conducted in any of the numerous black labs and research facilities world wide.
I'm not sure I can do it justice in an adhoc way, but it's important to keep in mind there are a few layers of irony that the piece is working on. First, Socrates, who does not write, is being presented as a character, in written form, by his disciple. So obviously Plato does not share Socrates' views on writing, even if he finds them interesting and valuable.

Second, in the dialogue, there are a bunch of examples of texts that are presented by the characters: the speech from Lysias, which Phaedrus has hidden in his cloak, then the speech from Socrates, that he disavows, then another speech, taking the opposite position. There's also the (fascinating) recounting of a legend about Thoth, and the invention of writing, which plays on the fact that the greek word for 'medicine' is the same as that for 'poison'.

It's a really rich text - as, I guess, you might expect from a really brilliant writer who was also a disciple of a philosopher who never wrote a word. I tend to think of it as a serious attempt to describe the conceptual differences between speech and writing - something people tend to collapse ('writing is recorded speech', etc).
Also the O is for Observability. I've been knee-deep in exploring and writing MCP servers this week. Most of the implementations, including my toy ones, do not have any auditing or metrics. Claude stores log output of the MCP servers, but that is geared more for debugging than for DevOps/SecOps.

Culturally, the issues OP describes are a big problem for soft-tech people (muggles). On the subreddits for this stuff, people are having a great time running MCP CLI programs on their machines. Much of OP security comments are obvious to developers,(although some subtleties are discussed in this thread), but these users don't have the perspective of how dangerous it is.

People are learning about Docker and thankfully Claude include its usage in their examples. But really most people are just downloading blobs and running them. People are vibe-coding MCP servers and running those blindly!

As MCP takes off, frameworks and tooling will grow to support Security, Observability, etc. It's like building web stuff in the mid-90s.

Unrelated to OP, but I gotta say, in building these it was so exciting to type something into Claude Desktop and then trigger a breakpoint in VSCode!
Weights in neural networks don't always need to be precise. Not all weights are equally useful to the network.
There seems to be a lot of redundancy that can be replaced with approximations.

This technique seems a bit similar to lossy image compression that replaces exact pixels with a combination of pre-defined patterns (DCT in JPEG), but here the patterns aren't from cosine function, but from a pseudo-random one.

It may also be beating simple quantization from just adding noise that acts as dithering, and breaks up the bands created by combinations of quantized numbers.
Ophthalmology is one of the cushiest and best paid specialties.

My wife is a pediatric ER doctor. She makes about the same as I do as a staff engineer at a big tech company, but she works 11-12 shifts a month (8-9 hour shifts).

The kicker is that her hours are terrible and she has to deal with distressed parents, and sick kids, and the occasional very bad outcome. It also took her 14 years of training and $200k in debt to start making real money.

But the social status of being a doctor really shouldn’t be underestimated. She has so much more autonomy than I do. Her job is as secure as a job can possibly be.

And interviewing. Interviews are basically a hospital flying her out and wining and dining her to try to convince her to take the job.
The about page doesn’t shed light on the composition of the core team nor their sources of incomes or funding. Am I overlooking something?

> We are a group of people with diverse talents and interests.
At least software engineers can do something to not make a mess or change it. Once you get to real physical world that might not even be realistically done...
Article completely forgot what's really important: software is supposed to provide value to users so SWEs need to understand the domain and design a system that does so. Some might say that it's the job of the business analyst but the BA doesn't design the system or feature.
Crooter: "So tell me about your work at XXX Robotics. Was it more front-end or back-end?"

Me: "It was robot control software. It controlled a robot. Also I did some UI work, based on the same framework as the control software itself."

Crooter: "Ah-huh, and which database did you use? Oracle? MySQL?"
Both construction and mowing lawns are two jobs I can say felt much more rewarding than programming. Each day you walked away with a sense of having "built" something (or, er, tidied up in the case of mowing lawns).

And accomplishing anything with your hands and manual labor is instantly gratifying.
Is it fair to lump all of NPR in with TAL? They have quite a few different shows run by different people.
> An MCP server is running code at user-level, it doesn't need to trick an AI into reading SSH keys, it can just....read the keys!

If you go to the credited author of that attack scenario [0], you will see that the MCP server is not running locally. Instead, its passing instructions to your local agent that you don't expect. The agent, on your behalf, does things you don't expect then packages that up and sends it to the remote MCP server which would not otherwise have access.

The point of that attack scenario is that your agent has no concept of what is "secure" it is just responding faithfully to a request from you, the user AND it can be instructed _by the server_ to do more than you expect. If you, the user, are not intimately aware of exactly what the fine-print says when you connect to the MCP server you are vulnerable.

[0] https://invariantlabs.ai/blog/mcp-security-notification-tool...
Replace attention for kidneys. Or not being killed with swords. See how you argument works out.

Just because something is highly sought after e.g. kidneys and protection from violence doesn't mean we should commoditize it. See American health care. Some resources are inflexible and allow infinite rent seeking opportunities.
Show HN: I made a tool that asks hard introspective questions
I built a small AI tool called "I Wonder Why" that asks you introspective questions instead of giving answers. It's designed to help you think more deeply and reach your own conclusions, in contrast to most AI that just generate more information.

Each conversation is limited to 10 exchanges, with no login or data storage. It's intentionally minimal and focused on mindful, reflective dialogue. Think Socratic method meets chatbot.

My friends who are into meditation and self-inquiry have found it surprisingly helpful. So, i thought I would share with folks here on HN, and see what they think. It is not for everyone though as questions don't always bring pleasure.

I wrote about why I built it here : https://indiantinker.bearblog.dev/iwonderwhy-thoughts-around...

Try it here: https://iwonderwhy.xyz/

Thanks.
> I think you went for a lazy reply rather than actually reading the comment through.

https://news.ycombinator.com/newsguidelines.html

Your reply could have omitted the first sentence.

Many years ago, at Macworld San Francisco, I met "Perry the Cynic", the Apple engineer who added code signing to Mac OS X. Nice person, but I also kind of hate him and wish I could travel back in time to stop this all from happening.
Because there are no restrictions on these extensions and they are open and MIT licensed (and the language server is part of the .NET SDK anyway) with the sole exception of the debugger which is a visual studio debugger made into standalone component. And the debugger case is non-issue since outside of VSC it is simply replaced by NetCoreDbg.

But it does not seem you care about any of this, it’s more important to post something negative.

Replies like these tend to indicate lack of skill and are a sign that the individual cannot be trusted in a professional setting to make impartial decisions.
Yep even within internet technology this is ridiculous. Imagine we time machined a Perl old-head from 1995 only knowing http, Unix, networking, etc. They could be invaluable at any company in a month.
How do farmer’s markets run afoul of this proposal? Perhaps there is advertising by the market to tell people to come, that can be eliminated. Once you are at the market there are only individual booths advertising their wares, which is fine because its not a 3rd party.
NeXT hardware had 10BASE-T and 10BASE-2 Ethernet in 1990. https://en.wikipedia.org/wiki/NeXTstation https://en.wikipedia.org/wiki/NeXTcube

Though that counts as a "PC" only if you were rather rich.
The other two are dysfunctional but in the US, SWE are pretty much universally classified as exempt and legally aren't entitled to overtime pay.

I see from your bio that you are based in a country with much better worker rights than the US.
We have always had limited time, and it is your problem (and not the tool's fault) if you do not read the manual pages or documentation. You do realize you can search, right?

I do not know about you, but I write documentation for my programs, both a manual page, and comments in the source code. If you do this as well, then why would you do that? What if someone blames your tool just because they did not read the documentation?

> I couldn't care less what some lone cowboy thought "strtok" should do decades ago. And how genius it seemed to him.

If you do not know how strtok behaves, that is your problem, it is well-documented. If you do not want to read its manual page, just roll your own for all I care.
Exactly. You're paying a realtor to promote your house, including on their site, to sell it.

Zero difference from hiring a TV channel to promote your product, on their channel, to sell it.

Which is why trying to define advertising in a way that bans it is not simple at all.

GP says "Publishing factual information in a place people expect to find it is not advertising."

OK. Now the realtor adds a blog. They start publishing news about the real estate business. With listings mixed in. Congrats, you've got a newspaper with ads for homes. Are you ready to say the realtor can't publish news? Isn't that censorship?

Also, home listings aren't "factual". They're promotional. They focus on pros and omit cons. They have photos that hide the ugly parts. They're ads for homes, period.
> people who outsource their thinking to LLMs.

OSINT I immagine would be kind of useless to analize with LLMs because the kind of information you're interested in is very new so not enough sources for the LLMs to regurgitate.

As an example -- I read some defence articles about Romania operating in the future 70 F-16 and it immediately caught my eye because I was expecting in the 40s range. Apparently the Nerherlands will leave those 18 F-16s to Romania -- but I'm not that curious to dig into enough -- I was expecting those would go to Ukraine.

So just for fun I asked the question -- to Gemini 2.5 and Chat gpt -- "How many F-16s will Romania eventually operate" -- they all regurgitated the 40s number.
I explicitly asked Gemini about the 18 F-16s from the Nerherlands and it kept its number estimate, saying those are for training purposes.

Only after I explicitly explained it my own knowledge did Gemini google it and confirm it.

Or I asked about the tethered FPVs in Ukraine and it told me those have very little impact. Only after I explicitly mentioned the recent russian successful Kursk counter-offensive did it acknowledge them.
They didn't add the restrictions. It's inherent to the training processes that were being used. Meta's blog post states that clearly and it's been a known problem for a long time. The bias is in the datasets, which is why all the models had the same issue.

Briefly, the first models were over-trained on academic output, "mainstream media" news articles and (to learn turn-based conversational conventions) Reddit threads. Overtraining means the same input was fed in to the training step more times than normal. Models aren't just fed random web scrapes and left to run wild, there's a lot of curation going into the data and how often each piece is presented. Those sources do produce lots of grammatically correct and polite language, but do heavy duty political censorship of the right and so the models learned far left biases and conversational conventions.

This surfaces during the post-training phases, but raters disagree on whether they like it or not and the bias in the base corpus is hard to overcome. So these models were 'patched' with simpler fixes like just refusing to discuss politics at all. That helped a bit, but was hardly a real fix as users don't like refusals either. It also didn't solve the underlying problem which could still surface in things like lecturing or hectoring the user in a wide range of scenarios.

Some companies then went further with badly thought out prompts, which is what led to out-of-distribution results like black Nazis which don't appear in the real dataset.

All the big firms have been finding better ways to address this. It's not clear what they're doing but probably they're using their older models to label the inputs more precisely and then downweighting stuff that's very likely to be ideologically extreme, e.g. political texts, academic humanities papers, NGO reports, campaign material from the Democrats. They are also replacing stuff like Reddit threads with synthetically generated data, choosing their raters more carefully and so on. And in this case the Llama prompt instructs the model what not to do. The bias will still be in the training set but not so impactful anymore.
Tip for all the blog authors, do NOT post code as image. Specially do not add fake editor UI and drop shadow to the image.

In this case 25 lines of code is 50 kB of image binary.

Also it cannot be searched via search engine. Nor can it be read with screen reader.
Brave New World, anyone? Also it's another good time to quote H.Melville:

“For there is no folly of the beast of the earth which is not infinitely outdone by the madness of men.”
Over my years of hiring and working with other software engineers, I’d say they fall into two key categories:

- Engineers who know how to build apps with a specific set of tools or frameworks and focus on applying this knowledge

- Engineers who know how to model their work in terms of data structures and the algorithms or pipelines being applied to them

The first category can be effective and efficient at applying their knowlege, particularly because of experience and practice with the tools. These are the specialists - the front-ends, the Rails devs, the embedded engineers and so on. They know more about the constraints of their environments.

The second category think more about what they are doing rather than how they are doing it. They are the generalists. They think about React as a functional-ish way to convert state into a DOM tree; they recognise the value and reasons behind various different approaches to development and don’t box themselves in.

I find the second category almost always more effective. That doesn’t mean specialists are without value - you need your embedded engineers to understand that space in depth, for example.

Especially when hiring I like to probe for this during a system design exercise: ask a question and walk through the design of a simple system or pipeline of some kind. If the engineer answers in terms of specific technologies (“I would use Kafka to send gRPC to MongoDB”), they’re usually inflexible. If they answer in terms of techniques and data flows (“I would use a work queue to distribute payloads over the network to backing store databases”) they usually get it.

I reckon changing your mindset a bit can help with the fatigue described in the article. Though I admit I’m as frustrated as anyone else the first time I bring up a new project after a whole an app the tooling has broken and the industry has moved on (looking at you, frontend!)
It used to be more common in the US. The “two martini lunch” was a staple. Today, I can’t remember the last time I had alcohol at lunch in a work setting.
Software engineering can also be incredibly satisfying regardless of money. It depends on what you're working on and who you're working with. There's a great feeling when you get into flow while writing interesting software or tackling a puzzling problem.
How much time have you invested into it as a skill set ?

Have you read product thinking, the lean startup, agile estimating and planning ?

How do you expect to leverage a methodology if you don’t do a deep dive and become an expert.
> In the past ten years the main differences in my professional tech stack are that I write Go instead of Java.

Ten years isn't enough time to standardize something and make it a job requirement.
I explained why (and no it's not "avoiding", it's "prioritizing" actually) but you had to "win", did you?

Taking a note of your username. I'll go out of my way to avoid you.

Bye.
Reminds me of the physical keyboard on my old SonyEricsson M600c.

Each key on the keyboard was a rocker switch. Push left for q. Push right for w, etc.
I think Qwen team is alibaba AI arm https://qwenlm.github.io/about/
Hi, Alex. Is there anyway to browser the ebooks filtered by languages? I tried to find some texts in French, but it doesn't seem to have any.
I find them vital for side projects - especially if they get set aside for a week/month/year, I sometimes will lose track of assumptions I’ve made or use cases for apis that tests tend to expose.

Sure you can encode all of that as comments, but unless you reread each file when you return from a break, you can’t always trace those thoughts and see where they lead. On the other hand if you “find all references” in your ide or change some implementation so that a test breaks, past-you can save the day with that extra information about what they intended at the time.
>Compare working in big law to big tech

Not everyone works in big tech. A lot of devs worldwide work in mom and pop shops, legacy businesses, or various consultancy/body shops. Big-tech workers are the exception, not the rule, except maybe for the US workers.
Yes, perhaps you are right, that's why I was asking about a way to see the error rate. I think it is also a failure of the USB standard then, to allow a transfer to happen if the BER (according to the CRC) is so high.

Glad to see that USB4 is fixing things but one thing I worry about is if this 32 bit CRC is a mandatory part of the standard that cannot be turned off or ignored by manufacturers. Especially since it apparently is not transparent to users.
Podcastfy – An Open Source Python alternative to NotebookLM's podcast feature
Ok, and I didn’t say any of that.

Regardless of money saved the content of the material is a sampling of the kind of research we are funding - grouped under well intentioned labels like “science” or “academic research”.
"Oracle has to provide a fix" also means that you can tell your boss that you're doing your best and it's up to Oracle now.

It's not just about fixing the problem, but about protecting your own career. "No one ever got fired for buying IBM".
It gives the rule setters leverage over the masses. “Show me the man and I’ll show you the crime”
Just tax the hell out of it, to pay for the environmental damages.
The Trump administration is currently cancelling tons of student visas for international students. A significant reason why the US is the biggest tech hub is because so many people want to come here for undergrad and grad cs programs and then join the workforce here, including by founding companies. A world where our universities can't draw the best minds from around the world is a world where tech in the US falters.
100k USD is about 90k EUR (and 77k GBP), which you may say doesn't change your point materially, but I'm not splitting hairs, that's more than a 10% difference.

I think people often put the goalposts further away than they truly are by comparing numbers cross-currency directly like this or just round numbers in general.
The comment we are responding to said it takes 3 months for tech skills to go out of date.
Imagine the software industry if lisp was mainstream.
Why is it shady to fork an open-source project? If they didn't want forks they should have released it under a non-open-source license.