skysight-inc/HackerNews huggingface dataset:
Two things initially drew me to VB. Being able to draw the GUI was certainly a very cool and empowering thing. I could make software that "looked like software" by the standards of the day, with minimal effort.

The other was that the alternative to VB for GUI creation was wrestling with class libraries, at a point when OOP was utterly baffling to many casual programmers like myself. Just the bare minimum "hello world" kind of app on either Windows or a Mac was page after page of instructions.

I suspect that over the span of subsequent decades, demands on high quality GUIs have increased -- as mentioned by others. But also, the programming skills needed to build a small GUI using code have become more mainstream, maybe because the languages have gradually made it easier.

Today, for the quality of GUIs that I need, I'm actually happier to just code them, and let (in my case) Tkinter lay them out in an acceptable default arrangement. My victims, er, users haven't asked for anything better.
They linked a study, I will just reply with this: https://www.chop.edu/parents-pack/evaluating-information/why....

Also even if that implication is right, it would be a side effect to the much bigger main effect of being a vaccine.

And we'd have to check if it happens more with the vaccine than with the actual virus.
Yeah. This.
Or it could see Microsoft tightening its proprietary grip over free software by not only generously offering gratis hosting, but now also it's a Trusted Publisher and you're not - why read those tricky docs? Move all your hosting to Microsoft today, make yourself completely dependent on it, and you'll be rewarded with a green tick!
I was 13 when DTSS was introduced, so never had an opportunity to learn programming with Basic. Fortunately, that didn't harm me, and I've managed to compensate for this disadvantage.

I don't want in any way to minimize the impact of a language designed for non-experts. But, while Basic, and its many limitations, was the best that could be done with the relatively limited systems it was first implemented on, it doesn't scale. I recall, around 1970, building an interactive front end for an inventory system, using a commercial company's version of Dartmouth (or GE) Basic. It came to about 900 lines, and even I couldn't make sense of it.

It's a mistake to believe that non-experts write 20-line mortgage programs, or 50-line dice games. If what you're teaching them has any value, they will naturally want to write programs that grow organically as they understand the problem better. Dartmouth Basic is a language in amber, best understood as what could be done given the equipment of the 1960s, and the understanding of programming development at the time. It was neither better nor worse than other interactive languages of the time, for example, JOSS (which begat PIL, DEC's FOCAL, and even the horrific MUMPS, closer to our time).

I think that the true value of Kemeny and Kurtz's contribution was encouraging programming as a thing for “ordinary” people, rather than a priesthood. The language they invented was developed prior to clear understandings of structured, object-oriented, and functional programming, all of which have something to say even to non-experts. (And, yes, Microsoft continued to produce products with “Basic” in their names, but they have little to do with anything that was developed at Dartmouth.)

So, kudos to all the folks who learned their programming with Dartmouth-style Basic. But I think there are a lot of modern tools that not only help non-experts write short programs, but scale well as their knowledge and skill grows. Smalltalk was one system that demonstrated that, but in more recent memory, Python and Racket are also good examples.

By comparison with film, Georges Méliès did some amazing work in 1900, but nobody would confuse that with the work of modern directors.

(I don't want to get into a discussion of What Is The One True Introductory Language; I have my opinions on that, but they are not relevant here. Instead, I am trying to put the very significant contribution of Kemeny and Kurtz—democratizing computing—into what I see as a better perspective.)
And then the software would never be widely adopted.

FOSS is what it is and the dynamics around it haven't really changed.

What has changed is people wanting the rapid adoption rate possible from being FOSS without actually... being FOSS. I'm sorry, I have zero sympathy. If you want your product to be a paid product, just charge for it. What's that? No one would try it? Just give a free trial. What's that? Not enough people would use it for there to be this large community of people providing help, and tutorials, and addons/extensions/plugins, etc.?

The freeloaders are the people releasing their software as FOSS, using the community to get big, and then wanting to change their minds about it.
It could go either way? It might be close, or maybe not?

Imagine taking any of that seriously. Didn't they give Hillary an 80% chance?
That was before people could generate animation and music.
Hah! I have the same feeling on Binary quantization as this article. Too extreme of a compression.
A couple things happened: delivery services were unusually popular due to lockdowns, and that ended. Couple that with the drying up of investments in 2021ish that caused shrinking valuations for everyone. And you get this transaction which itself includes a premium.
But polling results cannot. Right.
Can be forced through inference with CoT type of stuff. Spend tokens at each stage to draw the board for example, then spend tokens restating the rules of the game, then spend token restating the heuristics like piece value, and then spend tokens doing a minmax n-ply search.

Wildly inefficient? Probably. Could maybe generate some python to make more efficient? Maybe, yeah.

Essentially user would have to teach gpt to play chess, or training would fine tune chess towards these CoT, fine tuning, etc...
Has anyone tried to see how many chess games models are trained on? Is there any chance they consume lichess database dumps, or something similar? I guess the problem is most (all?) top LLMs, even open-weight ones, don’t reveal their training data. But I’m not sure.
That paragraph is incredibly navel gazing and self congratulatory. Fully in line with the insufferable tone of the rest of LessWrong that really puts me off it.

It’s like they can’t help themselves, as a jab against all the bullies who conformed their frail bodies in to lockers over the years, including grad school.
That's delightful, but I fear many in the audience here may not quite see why. So, at the risk of explaining too much:

The Greek letter xi is one of those where the capital and lowercase versions are very different. Lowercase is a bit like a curly E. Uppercase is (at least if you're writing it in a hurry) basically three horizontal lines on top of each other.

The operation called complex conjugation can be notated in two ways, but the more common one among mathematicians is to put a horizontal bar above the thing being conjugated.

So the conjugate of Xi is ... four parallel horizontal lines.

And now we divide Xi (three horizontal lines) by Xi-bar (four horizontal lines), getting: eight horizontal lines.
Do you remember how snappy it was! im using an i9 with 32gb on win11 right now and there is noticable lag opening paint and notepad, typically 2 seconds.
> do we honestly feel like we've exhausted the options for delivering value on top of the current generation of LLMs?

I know we absolutely have not, but I think we have reached the limit in terms of the Chatbot experience that ChatGPT is. For some reason the industry keeps trying to force the chatbot interface to do literally everything to the point that we now have inflated roles like "Prompt Engineers". This is to say that people suck at knowing what they want off the rip, and LLMs can't help with that if they're not integrated in technology in such a way where a solid foundation is built to allow the models to generate good output.

LLMs and other big data models have incredible potential for things like security, medicine, and the power industry to name a few fields. I mean I was recently talking with a professor about his research in applying deep learning to address growing security concerns in cars on the road.

The application is far from reaching the ceiling.
Sam Altman might be wrong then?

Learning from data is not enough; there is a need for the kind of system-two thinking we humans develop as we grow. It is difficult to see how deep learning and backpropagation alone will help us model that. For tasks where providing enough data is sufficient to cover 95% of cases, deep learning will continue to be useful in the form of 'data-driven knowledge automation.' For other cases, the road will be much more challenging.
https://www.lycee.ai/blog/why-sam-altman-is-wrong
Could someone explain why this is important? My uninformed feeling towards PEP 740 is 'who cares?'.
How well does an LLM/transformer architecture trained purely on chess games do?
The real question is why does PHP have so many bugs that it's so trivial to exploit?
Are these issues very particular to PHP? Honest question, this is all above my current programming knowledge.
Article 79 [1] gives individuals a right to sue for GDPR violations.

[1] https://gdpr-info.eu/art-79-gdpr/
CAN anything be done? At a very low level they’re basically designed to hallucinate text until it looks like something you’re asking for.

It works disturbingly well. But because it doesn’t have any actual intrinsic knowledge it has no way of knowing when it made a “good“ hallucination versus a “bad“ one.

I’m sure people are working at piling things on top to try and influence what gets generated or catch and move away from errors errors other layers spot… but how much effort and resources will be needed to make it “good enough“ that people don’t worry about this anymore.

In my mind the core problem is people are trying to use these for things they’re unsuitable for. Asking fact-based questions is asking for trouble. There isn’t much of a wrong answer if you wanted to generate a bedtime story or a bunch of test data that looks sort of like an example you give it.

If you ask it to find law cases on a specific point you’re going to raise a judge‘s ire, as many have already found.
Let's keep aside the hype. Let's define more advanced AI. With current architectures, this basically means better copying machines(don't mean this in a bad way and don't want a debate on this. This is just my opinion based on my usage). Basically everything in the Internet has been crammed into the weights and the companies are finding it hard to do two things:

1. Find more data.

2. Make the weights capture the data and reproduce.

In that sense we have reached a limit. So in my opinion we can do a couple of things.

1. App developers can understand the limits and build within the limits.

2. Researchers can take insights from these large models and build better AI systems with new architectures. It's ok to say transformers have reached a limit.
Except that "del" is also (and I think more commonly) the name for the upside-down Delta used in vector calculus for div, grad and curl.

(I usually say "partial dx by dt" or whatever, which seems OK to me.)
This is an excellent write up, it explains the logic of macOS in a way that is seldom understood.

I learned something here and I've been using OS X/macOS since 2003, and Macs since System 7. Like the author, I

> just enabled the “Show all filename extensions” checkbox in Finder settings, thinking that hiding file extensions was some sort of paternalistic simplification.

It's much smarter than that. It's worth disabling the setting and perusing the Finder to get a sense of how it works.
Assuming successful implementation of KIP-932, it will soon be a queue as well.

https://cwiki.apache.org/confluence/display/KAFKA/KIP-932%3A...
You can still configure it to be key only, you just need to put your own override as a file in /etc/ssh/sshd_config.d/ rather than /etc/ssh/sshd_config. The files are read ins order, so your filename needs to sort after the 50-cloud-init.conf file.

This would work:
echo "PasswordAuthentication no" > /etc/ssh/sshd_config.d/60-password-auth.conf
Someone might think: surely seeing ads targeted for them instead of random ads must be useful / beneficial for the user!
Same experience for me. Every job search breaks triple digits, easy.
Not sure its tech debt as such, its the hidden cost of having to maintain AI tech. its not a static state.. and its got an ongoing maint cost.
>Generative AI doesn't have a coherent understanding of the world

The very headline is based on a completely faulty assumption, that AI has any capacity for understanding at all, which it doesn't. That would require self-directed reasoning and self-awareness, both of which it lacks based on any available evidence. (though there's no shortage of irrational defenders here who somehow leap to say that there's no difference between consciousness in humans and the pattern matching of AI technology today, because they happened to have a "conversation" with ChatGPT and etc).
AI Spec Manifesto
I feel like a lot of people here are slightly misunderstanding how LLM training works. yes the base models are trained somewhat blind on masses of text, but then they're heavily fine-tuned with custom, human-generated reinforcement learning, not just for safety, but for any desired feature

these companies do quirky one-off training experiments all the time. I would not be remotely shocked if at some point OpenAI paid some trainers to input and favour strong chess moves
This is something I dislike intensely about pro mathematicians. If you need that many symbols, document them properly and work to ensure they're on the flyleaf of every mathematics textbook. You can easily picture a math paper that reads like

[ ], but [ ]; however [ ] and [ ], so [ ]....

with the spaces being filled in by signatures of famous mathematicians.
All market effects are exponential. Of course a doubled salary is unrealistic, but not ridiculous. The generation of people who are elderly today, had more than double the salary of anybody who is a worker today. Yes, they had more expensive consumer goods, but they could instead afford the important things: land, houses, vehicles and have a surplus to invest.
Is that the reason you were rejected, or was that just an attribute of what you did && you were rejected? What stage of the interview, what level?

I truly don't doubt that's what happened, I've had it happen, but when it did their feedback was (insultingly) not up to their professional standard. I say insultingly because it was an amateurish evaluation of what I did, specifically because it was like the 5th god damn interview by that point and really they should have been looking for more than trivialities like the coding style I chose to use in HackerRank with a visible ticking clock.

The reason I ask is just for context; if people are interviewing for Senior roles and being rejected for code formatting problems, something is even more deeply wrong than it seems, since they probably shouldn't be concerning themselves with that _at_all_. If it's possible though that you were rejected for some other reason, but that your code style was the strongest negative apparent signal, that's also worth exploring. In my case, that's a possibility, that they were looking for just one more reason to narrow the funnel, but it can be hard to accept.
C++ contracts as currently designed can execute 4+ times per call to do full checking. That gets expensive quickly.
A text editor and index.html with <script src="hello.js">

You can get everything you need without paying any money or even driving to Circuit City.
Grubhub as a database was an amazing service in college. In cities, there was a large number of nearby restaurants you may never have even heard of and you finally could see the full collection instead of just defaulting to Pizza Hut. Delivery was limited to however far away the restaurant was willing to lose one of their own employees for a bit, it was free or nearly free, and a shitty delivery driver was bad for business.

This is now a new hell. We have floating drivers, picking up multiple food orders from multiple restaurants and driving in the wrong direction while your food gets cold.

We have ghost kitchen restaurants having multiple online store fronts to hide the bad reviews of their crap food for the actual restaurant.

We have small businesses and large corporations demanding 15 to 20 percent of the order cost to deliver the food a few blocks. But they'll lower it to 10 percent if you get a subscription. And they still want a tip.

Even the existing aggregators like Yelp won't actually show you what's around without paging through tiny slices of their information ranked almost arbitrarily by random people on the Internet and gamed by businesses paying to rank higher.

I just don't bother with delivery. I get subscriptions to nearly all the food services included with my credit cards, banks, or some other random service and it's still not worth it. Either I'm eating out at a restaurant, where I'll begrudgingly tip, or I'm picking up food from somewhere I can get to within a ten minute walk or drive. Grubhub, Door Dash, and the like provide no value anymore. The massive loss in value of GrubHub still was not enough.
This “sounds smart” and I’m sure it circulates well in conversation. In practice, no. The point of “facts” is to identify useful truths that guide decisions. When some portion of the distribution of people identify misalignment, which is inevitable—not optional—then they will true up.
> but LLMs don’t even "see" the board

This is a very vague claim, but they can reconstruct the board from the list of moves, which I would say proves this wrong.

> LLMs have limited memory

For the recent models this is not a problem for the chess example. You can feed whole books into them if you want to.

> so they struggle to remember previous moves

Chess is stateless with perfect information. Unless you're going for mind games, you don't need to remember previous moves.

> They’re great at explaining chess concepts or moves but not actually competing in a match.

What's the difference between a great explanation of a move and explaining every possible move then selecting the best one?
While this does sound a bit obnoxious asking someone to "work" for no pay, considering the ask, this isn't a strange does it might sound. It's quite likely that position like this can't be monetized in other ways, as all government positions seem to be able to do. So if you are independently wealthy and able to move yourself into a policy influencing position like this, that can be a net benefit even without a salary.
The signal the cones output that the brain gets is lossy, it cannot be restored to its original wavelength histogram, and in my book that qualifies as “combined”. If you’re trying to say that red+green light doesn’t turn into yellow wavelength light before hitting the cones, then obviously yes. Otherwise, it seems like you’re arguing against your earlier comment and not mine. Your example was yellow light vs red+green light. The physical signals that our brain receives are physically identical in those two cases, not just perceived as the same, therefore by your earlier definition of combine, the colors do combine before it’s perceived. Seeing red+green light as yellow is not a matter of the brain interpreting two different signals as being the same, the signals themselves are the same, before the brain ever gets the signals, as a byproduct of tristimulus response. We don’t need human perception to demonstrate this either, a digital RGB camera has the same property, that red+green are physically identical to yellow when you measure using RGB primaries, with no perception involved. If you want to tell red+green and yellow apart, you need either more primaries or different primaries, and perception isn’t part of the equation. Your original claim on this point that the brain is involved was incorrect. The retina is involved in the sense that the initial output of cones in response to seeing either red+green or yellow light is a signal we call yellow. The moment light was converted by cones into electrical signal, that signal has lost any information that could distinguish between red+green and yellow. And yes, all of this is supported by the link I provided on metamerism.
Ideally yes but scientists have grown crops from single seeds that are thousands of years old so as long as the facilities passively maintain a low temperature, many of them will be viable for a very long time.
Build Soil
It wasn't clear, thanks
I am a founder with deep domain expertise in healthcare, I do hang out on reddit and HN. There is actually lots of us.

(also - technical and don't believe in co-founders, so not a good fit).

Anyway - what I found useful is to simply build and talk to folks, and people just want to join in on building. They just want to see something tangible and real before jumping in with someone they don't know.
The main issue here is a single vote in a US Presidential election, i.e., one vote out of around 150 million. Thus, the relevant analogy is buying one lottery ticket in a huge lottery such as the Powerball or Mega Millions and matching every number to win the jackpot.

Everything else, including cheating and rigging the lottery, is irrelevant to the question of strategically voting in a US Presidential election. None of your examples or hand-waving have shown that you can significantly improve the odds of one ticket winning the Powerball or Mega Millions jackpot.
ChatGPT is - understandably - blatantly different in the browser compared to the app, or it was until I deleted it anyway
Should copilot be renamed to "designated driver"?
The linked CVE-2024-2961 article is a pretty fantastic read on its own:

https://www.ambionics.io/blog/iconv-cve-2024-2961-p1

People are so creative, I can't help but feel some hope for our future :)
High expectations are one thing, and I’m an AGI skeptic, but when did being the smartest person ever become a requirement of AGI?
I suggest reading this detailed article to understand why they built this: https://blog.trailofbits.com/2024/11/14/attestations-a-new-g...

The implementation is interesting - it's a static page built using GitHub Actions, and the key part of the implementation is this Python function here: https://github.com/trailofbits/are-we-pep740-yet/blob/a87a88...

If you read the code you can see that it's hitting pages like https://pypi.org/simple/pydantic/ - which return HTML - but sending this header instead:

Accept: application/vnd.pypi.simple.v1+json

Then scanning through the resulting JSON looking for files that have a provenance that isn't set to null.

Here's an equivalent curl + jq incantation:

curl -s \
-H 'Accept: application/vnd.pypi.simple.v1+json' \
https://pypi.org/simple/pydantic/ \
| jq '.files | map(select(.provenance != null)) | length'
https://en.m.wikipedia.org/wiki/XZ_Utils_backdoor