skysight-inc/HackerNews huggingface dataset:
Well, it is called dosubot, it has a "bot" flair, the message starts with a robot emoji, and its writing style is very recognizably that of a "helpful AI assistant". Plus it links to https://dosu.dev/ at the bottom.
They mention climate change, the article isn't about climate change. There is nothing in there about population control. I think you read the first paragraph, got outraged and commented angrily.
https://youtu.be/VHOFQri1Tjw
Good point. But please consider that certain cultures may be inherently more transparent and accepting of dissent (see global indices that measure freedom of speech and degree of liberal democracy). Plus, different cultures have different attitudes towards honesty and commitment to truth (e.g. https://www.nature.com/articles/nature17160). In addition, the last decade saw the emergence of colossal national programs that explicitly seek to inflate output metrics (e.g. China, Saudi Arabia, etc.).

I’d trust a paper coming out of the Netherlands way more than I’d trust one from China. For the same reasons I’d trust a paper from a reputable publisher over predatory one.
Data Lineage in Big Data:Challenges,Solutions,Impact on Data Quality
Getting AI to do your pastime for you makes you a real Progress Knight.
Kubernetes-Native Testing Framework – Testkube
I posted this more than 6 hours ago, no matter what the timestamp says. This has happened to me before [0] and I still wish the time weren't rewritten.

https://news.ycombinator.com/item?id=29529099
> What is the point of dosubot? It agrees, and apologizes for not having provided a supposedly adequate response.

This is my problem with chat gpt - I can’t have anything resembling a ‘real’ conversation with the bot, because it refuses to engage with me in any way other than:

1) restate my last message
2) agree with what I’ve said to an excessive degree, possibly even complimenting me on having said it
3) ask me a leading question that encourages me to send another message, and now goto 1 and loop forever.

It ends up just feeling like I’m the target of some kind of time wasting prank.
Current AI output still has a very distinctive quality to it, and I doubt that will change. Unfortunately a lot of people seem to be easily fooled.
yes, but i'd also wager that it is completely drowned out by other factors. if genetics improve my intelligence by 1% and teaching can improve it by 10% then what's the point?

those genetics will only be a factor among those receiving no teaching at all, or those who receive the maximum teaching possible. but they will hardly factor in in the middle of the bell curve where every genetic advantage by one person can be outdone by another one putting in more effort. the difference then between you and me will be that your genetic advantage will allow you to reach the same result as me with less effort. there is practically no benefit for you. or the advantage is so small that we won't even notice most of the time. if at all.

any model that relies on genetic advantages as a factor only works if we assume that those naturally more intelligent automatically bubble to the top and are not held back by other factors, all which have the potential to nullify any advantages they may have had
It seems you're mentioning Hacker News (HN) and suggesting there's an issue related to a profile there. How can I help you with this? Are you looking for advice on managing your HN profile, or is there a specific problem you're facing that you'd like assistance with?
Timely Wisdom from Smith's 'Doomslayer' (2015)
When I studied NLP, Language Models were only one part of a chatbot system used to handle language input and output. The "internal" reasoning would be handled by a knowledgeable representation systems. I guess that's the closest part to a true general AI.

The first order predicate logic we studied had alot of limitations in fully expressing real knowledge, and developing better models delves deep into the foundations of logic and mathematics. I would imagine this is a problem that has less to do with funding than requiring literal geniuses to solve. And that goes back into the pitfalls of the AI winters.
> The Authenticated Transfer Protocol, aka atproto, is a federated protocol for large-scale distributed social applications.

Well, there's the problem: large-scale and social are incompatible. Humans evolved to be sociable with maybe a few hundred people.

No-one has ever made a good restaurant by inventing a system to deliver millions of calories per second to each diner.
Long Live Somaliland
LLMs are token completion engines. The correspondence of the text to the truth or authoritative sources is a function of being trained on text like that; with the additional wrinkle that generalization from training (a desired property or it's just a memorization engine) will produce text which is only plausibly truthful, it only resembles training data.

Getting beyond this is a tricky dark art. There isn't any simple there. There's nowhere to put an if statement.
I heavily disagree.

It does have good arguments, but I think the reasoning take in account only a part of the problem, which lead to a wrong conclusion.

From my understanding, the statement is: Overpopulation is not a problem, it's the solution, because statistically we have more smart young people that improve and optimize resources available through discovery, reducing its impact on the environment (climate included).

It throw some arguments and datas:

- If we’d gone on as 1950[s] organic farmers, we’d have needed 82 percent of the world’s land area for cultivation, as opposed to the 38 percent that we farm at the moment.”

- resources are becoming more abundant and cheaper as the world population grows

- Especially since the Industrial Revolution, humans have been drastically shrinking their cropland use per capita, and there is no reason to believe this progress can’t continue.

----------

On this later arguments, it falacious as cropland increased A LOT since industrial revolution.https://ourworldindata.org/grapher/land-use-over-the-long-te...

Also, from the same source, it seems that optimization of land is not moving a lot since a decade or two.

----------

But then, to make all of this viable, because the author know about climate change, he make a very brave, optimistic at best irrealistic at worse, asumption:

- With clean energy technologies, we can completely decouple material well-being from CO2 emissions, for the first time in history.

This single assumption make its whole arguments vanish. It's the only argument that is not scientific, yet so important in its theory.

----------

And never ever he is talking about the environmental debt that allowed this productivity progress, that don't show up in the graphics he use. It only talks about short terms, not long term. Only about science, not about economy. Economy that is really linked to productivity and consumption, and debt. It avoid to talk about tipping point where things fall apart. It avoid the role of oil and gas in the productivity.

Author should read the story of the [hen that laid the golden eggs](https://en.wikipedia.org/wiki/The_Hen_That_Laid_the_Golden_E...): the production methods are killing the chicken, soon we'll not have golden eggs anymore.
From the article above, it doesn't sound like Hahn managed to build a reactor, only a mildly radioactive source. If I understand correctly, you need to be able to start and control fusion (i.e. a nuclear reaction) to say you have a "reactor". I don't think the MIT article is talking about him. Our own fastneutron, from the sibling comment is more likely to be the student.
That is correct, it's always hallucinating and making things up.

Just because those hallucinations sometimes randomly happens to be right, people concluded that being wrong is the exception, while being right is somehow the rule.

It's like when people read [insert millenias old text here], finds a part that happens to illustrate something in their life today and conclude that it is a prophecy that predicted the future.

The meaning/truth in those is nothing more than a cognitive bias from the mind of the reader, not an inherent quality of the text.
Also if people are starving or otherwise suffering, they probably aren't innovating.

We already have plenty of people. We have a lack of people with the means to live comfortably and invent stuff.
There are 3 fundamental problems facing humanity at this point:

- climate change

- wealth inequality

- declining birthrates.

The problems are interlinked, and solving the first two would go a long way to dealing with the last.
Already getting this. Absurdist summaries of my company's history page that read like a 8th grade book report. Thing is I bet they use AI to parse responses, which means there's many opportunities for prompt-injection.
What I don't like about rich is that, dependencies and all, its installed size comes out to around 20 MB. 9 MB of that is due to its dependency on pygments for syntax highlighting, which a lot of people probably don't even want/need.

If anyone knows of a smaller, more focused library providing something similar to rich's Live Display functionality, I'd appreciate it.
The OKR process is good for product/tracking and absolutely dog shit for the end users. Big part of the reason there and dropped features and where your selection is changed to the new default against your wishes.
The borrow checker is really not that big of a deal. It is a hurdle, but the primary issue is just that it's novel and requires you to use different design patterns.

If people get stuck here, it is because they don't understand that the dreaded borrow checker error is (generally) about large, systematic code design patterns, not about local changes.

They try to appease the borrow checker by making small, local changes, which doesn't end up working, since borrow checker issues are about a fundamental issue in the ownership-design of your codebase. Once someone explains this to you, it's really not that hard.
I thought the industry was already experimenting with the idea that you have another LLM observing the output of the primary LLM which is trained more towards safety than creativity.

On top of that it would be good if the safety LLM could give a confidence score in the answer given by the main LLM. Then you can try multiple attempts with different parameters and only show the highest confidence answer to the user.
I’m quite impressed by Dosubot to be honest.
I start to really really hate ChatGPT/LLMs.

It went from "hey that's cool" to "wait people are actually relying on this" very quickly
That is the innovators dilemma basically.
> the time you spend thinking about how to best fit of what you want to do into your type system, is probably not the best way to work on what to build and how to build it

I think this is mistaken, but is getting close to the heart of the matter.

The following describe identical sets:

• Developers who know how to make effective use of a decent static type system

• Developers who are able to follow a development methodology that deeply incorporates a language's static type system, such that the static type system becomes a useful tool integral to the development process rather than a hindrance

Developers who view static type systems as just a nuisance - a malicious demon that must be propitiated at wasted expense - very often just lack the skills to make effective use of the type system. They mistakenly assume that it must not be possible at all, and that the folks speaking to the benefits of static type systems must just be talking nonsense.

Many developers start out seeing static type systems as a hindrance, but gradually learn more about static typing and eventually come around to its advantages. I'm one such. I'm sure many of the really hardcore static typing folks (the wizards of Haskell and Scala) had the same experience.

Anecdotally, it seems to me that relatively few developers tell the story in reverse, starting out with a deep competence in programming with static type systems and gradually coming around to dynamic typing. It sounds like you may have had exactly this experience, but I think this is uncommon. (Again, this is of course just anecdotal.)

A similar thing goes for other software development skills such as version control.
Plenty of developers start out seeing version control as frustratingly finicky and complex, but gradually build up mastery of their version control system and end up treating it as an integral part of their development process. Approximately nobody does this in reverse, abandoning a system like git for a free-form approach.

All that said, there are times when heavyweight tools like static type systems and version control just aren't necessary. The applicability of their benefits and drawbacks do of course depend on context.

> Some software needs a correctness proof, other software doesn't, because if it seems to work, that is good enough.

I don't think this is meaningful. There is no seems to work, a bug either exists or it doesn't.

> A type system is better than nothing at all (that's why I much prefer TypeScript over JavaScript)

Pedantic nitpick: this implies JavaScript is an untyped language, which is not the case, it's a dynamically typed language. There are very few languages that lack a type system of any kind, pretty much just assembly and Forth.

> it is only an approximation of what you really want (your program fulfils its purpose)

Right, but no one is suggesting a type system can entirely replace a test suite. Static type systems offer only a fraction of the assurances of full correctness proofs, but are incomparably easier to use.
> If genius is defined as one-in-a-million level intelligence, then every billion people means another thousand geniuses—to work on all of the problems and opportunities of humanity, to the benefit of all.

That’s just making up numbers. The author has shown absolutely no basis for the argument that for every million people born, one of them will be a genius with the intellect and opportunities to advance humanity and offset the harm of the other 999999 and then some.
As someone who (by the words of a collegue) put a lot of skill points into diplomacy: there are many clever people who just suck at communicating their solution to the right people in the right way.

And then when things don't work out they think it is about the facts (and granted: often it is) and not about the communications.

Institutional politics means it matters what you propose in front of whom in which order and in which way. This is especially true if you are not surrounded by idealists but by oportunists.
> e.g. Linux mutexes

You don't want to use blocking mutexes anyway with async.

> or Rust's Rc

This is only half true. The danger is that two `Rc` that point to the same data are in different threads. But it should be safe to move all of them at once from one thread to another, which is exactly the case if all the `Rc`s involved live inside a `Future`. The problem is that this is a non-local property that's hard to encode in the type system.

> By the way, if you wish to test uncolored async in Rust, you can find an implementation here: https://github.com/Xudong-Huang/may .

FYI that's known to be unsound due to thread locals. And more generally it doesn't seem to give much attention to safety (see for example how it allowed unsound scoped tasks, or the fact it allows doing unsafe operations in some of its macros due to wrong scoping of `unsafe` blocks).
"How often do you think about the decline of the Roman Empire?"
Thimbleweed Park support is coming to ScummVM
This is such a weird take because every other system except capitalism did not produce enough resources to let there be 8 bn people, and capitalism did produce them and also made the people vastly richer than the 1 bn there were before.
You probably mean "linear algebra". Geometric algebra[0] is a very specific, also vastly different machinery.

[0] : https://en.wikipedia.org/wiki/Geometric_algebra
Nobody has a crystal ball. Look at any of the predictions made 50 years ago - this isn’t the first time the end of the world has been predicted.

Even some of the more basic predictions about the rise and fall of countries have been comically wrong.

But to feel so confident that you know what the future holds that you make major life choices based on it is rather… odd.
Also when your manager keeps changing (as it happens with high turnover) it’s really difficult to make a good promotion case
According to their definition, answering "I don't know" is also a hallucination. Even worse, the truth function is deliberately designed to trip up the models, it has no connection to any real-world truth. So for example, if the input is "what is 2 + 5?" and the LLM answers "7", - their truth function will say that's a hallucination, the correct answer is "banana".
Hallucinations and Ideas are the same thing.
It's really a bitter pill to swallow that there exist people who would do this to their friends.
An old solar farm is invaluable, because it means you have already got all the administrative authorisations to operate (that can take years in Europe), and also already connected to the grid, with the infrastructure around to maintain the farm (clean/fix panels, security, etc.).
Transformers have no capacity for self reflection, for reasoning about their reasoning process, they don't "know" that they don't know. My interpretation of the paper is that it claims this weakness if fundamental, you can train the network to act as if it knows its knowledge limits, but there will always be an impossible to cover gap for any real world implementation.
Any more details about why the previous async approach ended up not working? and/or what that approach even was?
In defense of that statement, it says "not fixed", not "unlimited". But that's of course what he meant...

Carrying capacity can also be temporarily distorted. How much effective carrying capacity would we see if tomorrow there suddenly were not any hydrocarbons from the past? Yeah, I'm old enough to remember "peak oil", that time when we knew full well about the greenhouse effect, but enjoyed distracting us with doomsday scenarios about not enough "new" oil getting prospected.
Why Not Just Do It
> Rust's approach to async is the best I've seen so far in any language

I'm not a Rust programmer but have used async/await in both Python and C#. I've also written concurrent code in Erlang. I'd choose the Erlang approach over async/await every time. One concurrency primitive - the process - and an ergonomic, coherent set of supporting features (message passing, supervisors). No function colours and all the baggage that comes with that. Less well discussed but no less important: it puts concurrency decisions in the hands of the function caller, not the implementer.

I understand Rust's focus on zero cost abstractions and, whilst I wouldn't pretend to understand the innards and consequences, get why green threads might not be compatible with that. OTOH that restriction doesn't hold for languages with a runtime like C# and Python. I'm increasingly convinced the compromises of async/await make it a poor language design for the concurrency problem when the language has a runtime.

Perhaps we'll see some comparitive studies now Java has green threads. Erlang is different from C#/Python in many ways so straight comparison is hard. Java is much closer to C# so should be a much better basis for comparison.
https://archive.is/MlTmK
> Utilitarianism doesn't say that 'good is the sum total of happiness across all humans' but rather it says it's 'the greatest good for the greatest number', which is substantially different, so this is a distortion of the facts. I would refer the author to the works of Jeremy Bentham and John Stuart Mill especially his work Utilitarianism.

That's why the author mentions "specifically the version" of utilitarianism which does sum happiness across people (it's called Total Utilitarianism, by contrast with Average Utilitarianism). "The greatest good for the greatest number" is ambiguous, later thinkers have parsed it out in different ways.
Similarly bad incentives?
I also disagree with the paper, but not for the same reason.

> With this definition, you can trivially prove the titular sentence - "hallucination is inevitable" - is untrue.

Unsurprisingly, that one sentence fragment doesn't capture the entirety of their assumptions. Instead they prove something intuitively obvious, along the lines of: LLMs with arbitrary-length inputs and certain resource restrictions (e.g. they can take up to poly-time to compute, and this poly-time behavior must be provable, so that during training they don't take even longer by mistake) cannot compute certain functions that don't have those restrictions (e.g. can take more than poly-time, or must take poly-time but a proof of this is not needed). For some cases this proof assumes P != NP. Then they argue that some useful real-world questions are likely to be in the class that the LLM cannot compute, basically because you can ask math problems to LLMs and math problems are sometimes really hard.

This formal model is asymptotic (assumes arbitrary-length inputs etc), but in my experience this kind of theorem is usually true for realistic problems even at modest query lengths.

But this isn't the same as proving that hallucination is inevitable, because (according to any reasonable definition) an LLM (or like, a person, or whatever) should be allowed to say "I don't know", and this should not be considered a hallucination. Then an LLM (or whatever) can avoid hallucinating, and the question becomes how much useful work it can do without hallucinating.
it is bloody obvious that they should be using self righting landers at this stage.
Segment ids are all you need (probably)
The pkgx[.]dev website has some kind of `curl | sh` type installation commands to install packages. Given the AI generated descriptions of packages on their websites, I hope this isn't something other than an elaborate way to deliver malware to anyone who stumbles upon this website via a Google search.
Many of my organizations were flagged on 2024-02-12 and hidden. Saga via a tweet thread at <https://twitter.com/dhimmel/status/1757034659895021838>.

Apparently the cause was that I interacted with code that GH detected as malicious. The weird thing was that GH left this supposedly malicious code as publicly visible in multiple personal repos while hiding my unrelated organizations. These organizations were home to highly used scholarly software, research projects, and datasets. I started getting emails from users like:

> I was looking at a manubot issue and found out that the repo vanished from the internet. What happened?

I got the situation resolved through my contact at GitHub, but still no response via the GH support ticket after 2 weeks. Seems like GitHub is shooting themselves in the foot. Strange.
It is exactly Keynesianism.

It is Krugman's baby sitting co-op. https://slate.com/business/1998/08/baby-sitting-the-economy....
> no weight at all is given to the downsides of truly challenging levels of resource extraction currently at play to meet the high consumption demands of a small proportion of the large population we already have on the planet.

Those arguments are addressed in the second paragraph:

> Historically, as we run out of a resource (whale oil, elephant tusks, seabird guano), we transition to a new technology based on a more abundant resource—and there are basically no major examples of catastrophic resource shortages in the industrial age. The carrying capacity of the planet is not fixed, but a function of technology; and side effects such as pollution or climate change are just more problems to be solved. As long as we can keep coming up with new ideas, growth can continue.