skysight-inc/HackerNews huggingface dataset:
It's not going to happen anytime soon. These language models take several bleeding edge GPU's to run at a reasonable performance. Vision to the likes of how humans perceive detail is another dimension of complexity. There have been groundbreaking advances in machine vision over the past 20 years, yet we still cannot build a robot that folds clothes efficiently [0]. Arguably, this is not only because of vision, but also dexterity, but both are currently of what a human can perform.

But if it happens, likely legislators will regulate AI. Most western governments already provide job procurement programs through being employed by them. Which is a good thing, but HN doesn't like to hear that. The reality is that most people need a job to feel fulfilled and be a healthy member of society. Which could change, but It's not going to happen until this technology falls into the hands of the common people instead of being controlled by large corporations.

[0] https://www.youtube.com/watch?v=2jc6iQZN-uA (Robot is recorded at 4x realtime)
Of course they can.
Neal Armstrong literally travelled to the moon sitting in a literal chair.

Basically, the Saturn rocket was more or less a simple chair with some extra features added to it.

Granted they didn’t stack chairs. But, nevertheless, focusing on the mods you’d need to make to your La-z-boy to get to moon would be a fruitful way of approaching the problem.
All the people with computer science degrees working in the field who also had to take common core courses that they 'didn't care about' seem to serve as a counterexample to this general claim.
Lord of light. A similar popular book but written in Chinese is "赛博英雄传" if you can read Chinese or maybe ask GPT-4 to translate for you.
> Have you ever tried pacman?

I have! I'm personally not a fan. I've generally experienced pacman as incomplete, brittle, and clunky.

For me, giving up the speed of pacman for the robustness, flexibility, nicer CLI, and feature completeness of dnf or zypper is an easy tradeoff to make.

> I’ve found pacman to be much faster than dnf, although I can’t remember exactly how fast zypper is since it’s been a few months since I used OpenSUSE

Compared to pacman, zypper is slow like dnf— probably slightly slower.

> PKGBUILDs are also a great part of the pacman system, and while I’ve not written any yet myself, I can mostly understand what they are doing, and I’m fairly sure I would be able to write one if needed, whereas when I tried to write an RPMspec (? might have gotten that name wrong) I gave up after an hour of trying.

It's been a long time since I ran openSUSE on the daily, but when I did I managed a repo of RPM packages and I'm pretty sure I created at least some of their spec files from scratch, although most were downstream forks or packages I imported from elsewhere.

I don't know what made it click for me, but I found it a little easier than DEB packaging (maybe in part because I learned it later), and definitely manageable.

But I hear you: PKGBUILDs are widely praised for their simplicity, and it clearly helps a lot of people make good use of the packaging system. That's a real strength.
It's a message straight out of Hitler's playbook: create a cult of personality by radicalizing rural people and the working class and using them to create a voting bloc powerful enough to dismantle the very democracy that gave them that power in the first place. Godwin's law doesn't apply; Godwin himself said that comparing people to Nazis was appropriate when those people are actually behaving like Nazis.

If you do not look at Trump and his memetic strategy and see the rise of fascism in the USA, you have not been paying attention.
Meta's offering is 10 times cheaper. This price tag brings the headset out of reach for at least 95% of people right out the gate.
But it can be also something that is not opportunity nor doomsday.
Then considering it opportunity one spends resources with not gains.
> I don't remember the last time I download a game and it didn't just work.

Battlefield 2042 released Nov 2021.
I agree with you on that. If it's less than 1% then it does make more sense to think of it that way.
Because people want their queries to have predictable performance.
What’s a life worth living? For the ancients, it depends
Is "learning to reason" a real challenge? (Kahneman's system I in the slides) From a naive perspective of view, formal methods like SAT solvers, proof assistants works pretty well.
Our buying power isn’t much more than our parents, it is noticeably less when it comes to housing. My dad got a mortgage on a $100k home in the late 80s when he was making above that per year contracting. There is simply no way a FAANG job at below director level would allow for that.

From that perspective, yes a lot of people make less, but that just means life is becoming impossible for most people making normal salaries.
I might not disagree with you there.

However, for all its warts, x509 due to hardware implementations, seems a great deal more secure than sitting on the FS SSH host certificates.
> Twitter’s email address for press enquiries continues to auto-respond with a poop emoji.

Classy.
I think the implication was meant to be that there will be far more people who are both programmers and domain experts than there currently are programmers?

Domain experts often don't need to do anything "innovative" - they just want to schedule their team's workload or some-such that's been done a million times but the details of their particular situation are important. Most programmers now are doing such things for domain experts as it is. One possibility (I'm not 100% convinced) is that AI would allow the domain expert to do it directly, i.e. become a programmer themselves.
Something a lot of people aren't considering is the added power the LLM will have once we are building systems from the ground up specifically for the AI to use. Right now it's doing a decent job with languages and tools that are built for human usability. I imagine soon we'll have languages, systems, and tools specifically built to be extremely usable by AI.
This is especially important in the age of LLM's.

Large scale surveillance while abusive and harmful has historically been limited in scale by the ability of those in control to trawl through data.

Automated "moderation" of dragnet communications collection with modern AI holds the potential for a scale of abusive privacy invasion at unprecedented scales.
Regulatory capture by the military industrial complex
Heh, I'm literally in the middle of optimizing some N+1 query endpoints in a Django application for work, made a bit more tricky because of DRF's serializer.

I think a setting for lazy queries would be a good solution, with it enabled by default to ease the transition. It would be nice to have a couple options, though – allow, warn, and error.

It would also be great to have a way to change the setting on the fly so that, e.g., the Django shell can automatically enable it for those quick debugging sessions.
Reading "Chokepoint Capitalism", I can't help but notice the similarity between 'moats' and 'chokepoints'. After all moats are essentially just a means to force traffic into more easily guarded gates. And one always wants to encircle as much of a market in ones moat as possible.
OK, I asked ChatGPT to explain this, and here's my current understanding. A Credit Default Swap is essentially a type of insurance issued by the banks to outside parties who have loaned money to other outside party. If the borrower defaults then the bank would pay out money to the lender.

So a high number of credit default swaps would indicate that the bank could potentially have to pay out a lot of money in these "insurance payments" if other parties go bankrupt which could deplete their funds.

Is this about right?
Though many people confused embodied with 'robot', as in an AI would be packed in a unit walking around. I personally see it the opposite way. An AI could have a 1000 bodies all gathering data in the world. Or a million cameras connected to it. Or a set of sensors that spans the globe.

In this since a digital entity could have far more embodiment and connectivity then us humans could ever have.

Waiting for the first research paper with the term 'globally conscious' at this point.
Yeah, I think this nails it. I think about the non-trivial parts of writing code, and I think about all the previous failed attempts at this sort of thing, and I remain unimpressed so far.

I think specifically about things like optimizations and wonder how an LLM would deal with that. In the last week I’ve written code that dealt with file I/O slowness, thread contention, thread deadlock, etc. In order to even begin fixing these problems, I had to first identify what the cause was by debugging them. Then I had to reason about how the program works to think up a good fix for the issue in our specific case.

There are no stack overflow answers for some of the problems I fixed this week. Heck, at one point in the past, I even wrote some code that we thought about getting patented. It was an interesting solution to the problem. And the problem itself was not a common one (but not unheard of). There’s a small amount of literature on it, but not a ton. I don’t see LLMs being a threat to this type of work. But in talking about it, I do see how some other type of AI might assist with it.
The problem is, a lot of our cities are fundamentally hostile to pedestrians. Even if you're actually close enough to walk to a grocery store (most are not), you may be afraid to cross streets with numerous lanes of speeding cars without dedicated crosswalks. In my city, it's common to hear stories of bicyclists in hit-and-runs; it doesn't exactly make people comfortable with walking and biking around their city.
It’s only unscientific if you don’t test your theories and learn from your errors.
Whether I have a bias or not is irrelevant. It does not negate who the hegemon is.
Even if it does, it will simply mimic the systems other companies have created and documented, because GPTs don't create anything new. They recombine what already exists.

Plus let's be honest, the technical problems are the tip of the iceberg for software architecture. If an AI ever manages to convince my director to pay for things I'd be happy for the help.
Yes for bacteria, maybe for viruses, probably not for prions. For what it's worth, I'm LDS (Mormon) and I think my view is probably pretty common amongst members of the church. That said we would technically use the term spirit instead of soul, I just used soul because it's a more commonly understood term. Basically all living things have a spirit in addition to their physical form.
A lot of chronic problems from frequent flyers to the ER can be resolved by housing them.
Either you're confused, or I am. System Extensions like ACE require that Apple Silicon users switch to "Reduced Security"¹ rather than "Full Security". It doesn't require disabling Activation Lock².

¹ https://rogueamoeba.com/support/knowledgebase/?showArticle=A... ² https://support.apple.com/en-us/HT208987
The difference between the buyer of a house and the buyer of software is that the house purchaser is clearly and succinctly able to communicate his / her desires and expectations. Where as the purchaser of software is making some vague request for functionality with poorly defined boundaries and requirements. There is little meaningful comparison of the two scenarios that can be made.
How does Congress make physicians?
Zuckerberg has absolute control of Meta, he is the one calling all the shots. Bezos doesn't have total control on Amazon but sits on the board and has the most voting power amount shareholders, so was the case with Benioff until a few years ago when he started dropping stock to buy expensive toys like Time, but he is still the single largest owner of Salesforce. So, many of the original co-founders of these companies are still there, they just have much different goals and interests than their younger selves.
They do it not to impress investors, but because they feel they are doomed.
But who watches the policing model?
I’m not worried about any of that. If healthcare can be more widespread, effective, and affordable that’s a great thing. And if someone wants to beam stuff into their mind that’s not radically different from watching a movie.

I just don’t think the future is scary just because technology is developing.
I didn't ask questions about the article, only about another commenter's (incorrect) claim. The original question about the article was someone else.

I have a graduate degree in bioinformatics and have worked in the industry for close to a decade, I have a strong background in the exact topic, yes.
There’s a misunderstanding here—

I’m not claiming LLMs are sentient. I’m not claiming they are even similar.

What I am pushing back against is the confidence with which people so blatantly claim we are dissimilar.

It’s an important distinction, and I’ve yet to see solid evidence to suggest it’s a point we shouldn’t even explore.

What I see so often is comments stating things like, “an LLM is just pattern matching” or “it’s a prediction machine”.

And I’m not arguing that’s not true; what I’m arguing is how can anyone say a human is inherently different ?

I admit that I’m taken with these latest advancements. It’s why yes, you see my tech-bro crazy-person comments in these threads a lot! But I’m genuinely fascinated by this stuff.

I have had a huge interest in the human mind for a decade. I’ve read the works of folks like Anil Seth and others who work in cognitive and computational science, and I’m increasingly intrigued by the things we might learn about our own selves via these technological advancements.

Again, I’m not claiming sentience for an LLM, or anything that says “we are the same as an LLM.” I’m simply trying to argue that our own minds are a black box, as are how an LLM arrives at an output; it’s the confidence of folks to claim they know what’s inside either that I’m pushing back against.
I'm sure I'm not the only one, but I'd love to see a write-up on that. Prod your colleague to put it somewhere on YT, HN, Reddit or somewhere.
While I appreciate their efforts 100% it's sad people need infographics and ads to know why this is a terrible idea.

Although I've seen enough HN comments in recent years willing to gamble on giving their kind an inch as if they won't take the whole field given the chance. History's only reliable lesson here is humans having a short memory of trusting these systems to do what they initially promised they would do, for longer than the well-intentioned's term in office.
Could go for those quad MRM packs though. Easier than 7 GBU-31s right.
But wouldn’t a simple interlock (like a puzzle piece) achieve the same result?

I wonder if it is possible to use this to make self similar non repeating patterns (like say wood grains) without requiring more than N patterns, where N is some sufficiently high number and each tile pattern is designed to continue any side. I also wonder if instead of slippage it’s more like distribution of pressure or some other force related factor not concentrating in any area. I really wish they had explained the applications better it’s an interesting result.
There is no other way. If they want something done they need someone to do it. Layoffs make them less attractive. So they will have to either rise the wages or accept less qualified candidates. The difference in performance between average and top engineers can be time. Or even infinite, when one simply cannot do the thing.

And this is, BTW, applicable through the whole range. Just check Intel market capitalization, and guess what? It's now smaller then AMD, and 6x times smaller then NVidia. The reason: top management, they failed on AI, graphics, they failed on Cloud. Yes, they did something, not enough.
> But just stop for a minute and think about what you love about programming.

What I love most is creating stuff. I have little interest in algorithms, o-notation, and other minutiae. I’d love a world where I could just tell the computer what I want to create and it takes care of the minutiae for me. Though, I’m mostly thinking about personal projects. When it comes to writing code for work… well, that is not really in the ven diagram circle of things I love about programming. Maybe I’ll have to do something else for work, though I’m about 10-15 years away from retirement. It will be interesting to see how much things change by then.
> It feels like we as a species are optimising towards a terrible future when you start putting all the bad uses of these technologies together

The train departed with Tiktok on this one. I'd say we have nothing to lose with the AI.
Sorry, maybe my post sounded more serious than I intended it to. I wasn't trying to be combative, I was merely pointing out the irony of lecturing someone about insulting people on a professional forum, when your first post could easily be interpreted as bragging and insulting the people you work with. I'm sure you didn't mean it that way and had good intentions. There's nothing wrong in principle with saying you're good at something. I think it's the direct comparison with specific people and the implication that they are slowing you down that has the potential to be interpreted negatively.
I’m not sure that our comments are really all that connected, I used “single payer healthcare system,” as in the term-of-art for a way of distributing funds for healthcare. You seem to have gotten latched onto the word “system” and seem to be using it in a sort of broad “fight the system” way.

There definitely aren’t any healthcare systems inside of my mirror, not even the bathroom one with a cabinet behind it.
I’ve brought this up in another thread, but we already have evidence that in certain cases it is desirable to trade off specificity for just “getting something done”, that evidence is Python. Python succeeds despite not having a serious type system, because often times you can get something that achieves your goal despite the 25 bugs in your program that would have been caught by a real type system.

On the other side of the coin, there’s C++, which is usually doing the heavy lifting underneath the underspecified-but-sufficient Python code.

My guess is that as LLMs evolve, they will more naturally fill this niche and you will have high-level, underspecified “code” (prompts) that then glued together more formal libraries (like OpenAI’s plugins).
How do you manage that? I get a massive of stomach ache if I eat a green banana.

I need my bananas to be completely free of green not even a tiny hint of green on the tip.
Talking to yourself is good for you as long as you know you are talking to yourself.
You're training the social world model in your mind.

Eliza has come a long way, as Professors Higgins and Weizenbaum agree.
Now someone build a bot that goes around looking for rogue bots and warns sysadmins.
Can states keep trains from blocking crossings? High court asks feds to weigh in
> First DALL-E came for the artists, and we laughed, because artists are worthless.

First, this is an annoyingly unnuanced way to start an essay. Second, if at some point AI takes all the pain out of producing stuff (it does all the low level work in all sectors), the only valuable activity that’s left is art.
It is done :-) https://github.com/ihucos/counter.dev-selfhost
People vastly overestimate how addictive ML content would be.

First off, what if the content you want to see is simply real stuff that other people are doing? Luscious perfect breasts can likely be generated by ML easily, but a spicy bikini photo of a woman I happen to know personally would easily draw my attention more. Maybe you can fool me by generating such an image, but eventually I’ll only feel any stimulation if I know the image is actually real.

I’ll give you a better example. Consider a movie where a persons head gets blown open, spilling brains all over the place. People might easily watch such a scene and think nothing of it.

But now imagine you watch a snuff film of a person actually getting their brains blown out in real life. For a lot of people this hits differently even though visually it might look the same. Some people specifically seek out these videos because they are real, despite the existence of fake alternatives.

Same goes for text, I don’t give a damn about some GPT generated essay but I will read something someone I know wrote with greater interest. Reading the opinion of an AI is a waste of time.

So as long as people value content made by humans, ML won’t have much to offer besides shallow, empty stimulus. Like watching some random porn and jacking off into oblivion, most people would still rather have actual sex with someone.
I think so! I mean, imagine if, when you notice some perf hiccup and you dig and realize you need to store your data in some different way.

Currently, commence a multi-month design cycle, create the migration path, perform the migration in a slow and safe way, soft logging, feature flagging, gradual release, etc., and finally once everything is migrated, remembering to remove the old code. All the meanwhile turning down a bunch of other ideas for improvements you had because you need to get this one thing done. Or worse, interrupting a bunch of half-finished refactorings and leaving them half-finished and having to work around those things until some time that may never come.

Imagine if you could just tell an AI to do this, be reasonably certain it would do the right thing, and it's done and provably correct and manages your deployments and migrations for you. And you could be free to look into the next batch of new things you want to do.

I love coding, but really I love thinking about the ways to do things more than the processes of getting those things done. If there was an AI that could automate that work, that would be incredible.
I was sad that Starfighter/Stockfighter didn't make it out to the general public, or that its code wasn't set free when it folded. It sounded really neat
For those more familiar with it, didn't this decade-old standard die with other efforts the Semantic Web?
The focus blur is repulsive. I think convincing focus blur will be the milestone that replaces stock photography.
AI/Robots should replace physical labor before it replaces knowledge workers.
China's Baidu cancels ChatGPT-like Ernie bot's livestreamed product launch
GPT4 Can’t Play Wordle
It will also help diabetics. Rice is one of the foods I struggle with as the carb release can take longer to enter the bloodstream than the insulin that is injected.
Yes, it is basically how much it costs you to insure the money you have deposited at that bank
> Asking depositors to do the due deligence is a strawman.

Except that there are many commenters in this exact thread making that argument.

As for splitting up your deposit into $250k chunks, I agree, companies should do this as much as possible. But it would be hard for some companies. An extreme case is Circle, who says they had $3.3 billion in SVB. To get all of this covered, would require 13,200 different banks. It looks like there are only 4,236 FDIC-insured banks in the US. Add in another 4,853 NCUA-insured credit unions, and we're still left with $873 million uninsured, despite using nearly 10,000 accounts.
The rise and rise of e-sports
Broken windows fallacy. If 100m highly competent people were involved in managing cancer, and we cured cancer, these 100m highly competent people could then turn their attention and skills to something else important. There are plenty of health care crises in the world
> a program synthesis system that never makes mistakes "understands"

Yes, I'm saying if it satisfies random requirements and synthesizes full working programs, then it has some form of understanding in it. If creates that understanding through learning, it's very possibly a general form of AI (I'm not certain of this part).

I've never seen any one that arrived at structure by learning. It's always programed in, what puts the intelligence on a very conventional place, and I doubt you'll disagree that it understands what it's doing.