skysight-inc/HackerNews huggingface dataset:
Worth also pointing out that sometimes when you're in a corporate dystopian hell hole do not expect to be able to actually request or install software on your device. What is there is what you have and trying to get it changed is an exercise in taking on the bureaucracy. It's not worth it. Many people have tried and failed.

Back in the dark ages, we had a horrible reporting engine in Word VBA that pulled report definitions off a fileshare and cut and pasted bits of templates together and then printed them. Literally there was a computer in the office the IT team hadn't taken back because the guy had quit and we logged it in as one of us and ran that .doc all day to do numerous engineering reports. This was quicker and cheaper than filing a PO for the reporting option on the CAD/CAM software which would have taken at least 18 months, involved consultants and eaten at the project budget.

So when everyone bitches about Excel VBA being used for horrible things, the cause is probably further up the stack.

The other cause is what I call monkey hammer. If you give a monkey a hammer he's going to hit things. Everything looks like a VBA solution when you're a monkey and the only hammer you have is VBA. I am a slightly more evolved primate these days.
Something Doesn't Add Up in NY Times Article
Source: https://www.ft.com/content/0f79d95f-de03-4be6-8398-79750d955...

The original from NYT got a lot of attention here with tons of anecdata.

Ref: https://www.nytimes.com/2023/11/05/business/banks-accounts-c...
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> After all, most permissive open source code licenses like the MIT License contain some variant of “the software is provided ‘as is’, without warranty of any kind.”

Why is this legalese so appealing as the answer to social issues that have nothing to do with licensing and warranty etc?
Late reply to this -https://news.ycombinator.com/item?id=38233029

But yeah we agree that GPT isn't necessarily doing things like how a human does and that it doesn't necessarily understand things as well as a human.

I guess I just primarily took issue on the use of "Understanding". Understanding is a spectrum, not binary.

In school, in the workplace or whatever, there's a big range of performance and capability even in the range we confess understanding to. We say that both the C and A student(and everyone in-between) have understanding of the material, at least enough to be useful for that domain.

So what can I say, I use the same standard with the machines. It understands chess now, even if not perfectly.
> How often can they repeatedly ramp without getting into trouble with reactor poisoning?

Every day, several times a day. That is literally the requirement for modern reactors (where modern means any reactor in the past 30 years, or more, and most retrofitted reactors from previous years)

Graph and text on page 8: https://www.oecd-nea.org/upload/docs/application/pdf/2021-12...
Essentially, you're giving each customer not a VM but a physical blade server?
Nah. The context of all of this is people claiming LLMs are AI. If so they would be able to reverse A is B, and also know when not to, so your example is irrelevant.

The paper shows that it cannot reverse. Then the blog posts goes around different disingenuous ways of making excuses for why it can't reverse at the same time as trying to show that it can reverse in the Tom Cruise training example (extremely disingenuous because it's just the same data over and over with synonyms replaced, and what he gets out of it is just completions, not logical deduction).
I suspect that the interpretation of C cannot be specified in a brief page of C code. For one thing, the language doesn't supply the data structures for representing any aspec of itself; the code will have to invent those: declarations, definitions, statements, types. Then handle a ton of cases.

It will not be obvious that what the C code is doing is C interpretation, because all those data structures don't resemble the C syntax.

The Lisp meta-circular interpreter side-steps that; the issue is settled elsewhere. It exists against a backdrop where the easy correspondence between the printed syntax and the data structure being handled by the interpreter is taken for granted.

The C would need the same kind of backdrop; and that would be a lot of documentation.
> It's funny because you ascribe some reasoning in ChatGPT's answer “Gerhard Schröder”, but somehow missed that it's also able to give you two other answers that are unambiguously wrong

Schröder is the only answer it gave when using functionality that would bring some representation if a list into its context first, and 10it did it with different prompts and mechanisms for bringing a list into its context.

That LLMs are bad at counting-related tasks without doing that is well-known, and not a point I felt needed belaboring.
FSRM is just the name of a cpu optimization that affects existing code.

Choosing an optimal instruction choice and scheduling can be done statically during compile time or dynamically (via chosing one of several library functions at runtime, or jitting).

In order to be able to detect which is the optimal instruction scheduling at runtime you need to know the actual CPU. You could have a table of all cpu models or you could just ask your OS whether the CPU you run on has that optimization implemented.

Linux had to be patched so that it can _report_ that a CPU does implement that optimization.

https://www.phoronix.com/news/Intel-5.6-FSRM-Memmove
Algorithmic time complexity is a very important, but I honestly feel like a typical university education heavily underemphasizes exactly how much the constant factor can matter. Like, consider a simple example: someone's hand-written memcpy in C might achieve, say, 500 MB/s, maybe 1 GB/s if the loop is particularly tight. The one that ships on your system likely does 20-100 GB/s. Same big-O on both, of course. Most cases aren't this easy but there is a lot of performance that comes from constant factor optimization, which can dwarf all sorts of clever algorithms that are theoretically more efficient. Everyone likes to go "ok well if I scale this to a billion users your algorithm takes a month and mine takes a minute" but it is very likely that between now and the billion users the code is probably not even going to look anywhere near the same. But it's likely to be running on the same JVM or the same OS or the same allocator and all of those have been optimized to cut their constant factor down. After all, you don't want to be the guy who has the same algorithmic complexity as your competitor but your cloud bill is twice as much.

(This isn't to say you shouldn't do algorithmic improvements, and most of the performance work I do is in fact along those lines, but I do want to clarify that the "micro-optimizations" you're talking about are in fact the difference between a computer from today and the 1990s.)
This is great work. Andrew's on to something. Thing is, the behavior we see in his form of the LLM is also what we experience as humans.

Good writers, marketers and manipulators know this about people. You seed the ground with the concepts you'll need to introduce, so they're present in the person's 'model' and you can elicit them later, on request.

Formalizing things in the 'reversal curse' manner is like loading the 'mind' of the LLM with habits and assumptions and cutting off its ability to free-associate from seemingly relevant concepts… which is likely to be more valuable in the long run, because an LLM can contain more than a human can. That doesn't mean it will be more intelligent, but it seems reasonable to infer that the LLM can have a broader base of association to draw from, where we as humans tend to be restricted to associations from our own experience. We only get one shot at 'training data', though it's in countless sensory forms, where LLMs are stuck with language as their only window onto experience.

I'm loving the notion of leaving the prompt 'training' stark raving blank. Let's see what comes out of this giant pile of human verbal associations. It is only that, associations, but it's on a grander scale than we're accustomed to. Making it 'answer questions correctly' seems woefully unambitious.
Why would a compiler prefer a redundant prefix over a nop for alignment?
A nice easy one is to benchmark trivial examples for people. For example summing an array of numbers in JS. Have examples of four levels of indirection between objects down to one level, straight numbers in a standard JS array and the same in a TypedArray. This pretty clearly demonstrates the gains that can be had.
"> An authoritarian individual or group are equally immoral."

I agree.
Fair enough, thought that still sounds like things where an upgrade path is available, just not automatically, instead of "you have to throw the code away because it simply doesn’t work anymore".
While red is the apple is not a correct logical statment using conventional understanding of each term, it is still an understandable english sentence, a structure which likely pops up a fair bit. Even if just for scripts of yoda lines. It just goes to show truly how fucky language is and how amazing it is that something even remotely comprehensible comes out of LLMs
1. What do you think the reversal curse implies about LLMs?
2. Do you believe that LLMs are capable of logic?
3. Do you believe that LLMs are intelligent?
4. Do you believe that your blog post shows 3 or 4? If not, what is it about?
Old Bay for anything besides steamed hard crabs, for the boil J.O.'s is the seasoning you want.
Agreed on fentanyl, but there are other areas where nanny-stating saves lives.

The evidence on higher tobacco and alcohol taxes, for instance, is pretty irrefutable.

Or, moving up the implausibility scale in the American context, drastic reductions in the availability of handguns including the mass forfeiture of existing weapons (which has been done in a number of other developed countries).

You may not like any of these, particularly the last, but the fact is that they would increase life expectancy significantly.
If you can't trust the cloud host, you should be on-prem.
But is it low enough?

Solar drops to zero every night.

For hydro, there's already seasonal variation with rain/snow melt.
Beyond that, it looks like the majority of hydro in the US is on the west coast, which has been experiencing a drought for years and is projected to get worse. The west coast is big on removing dams for habitat restoration, too.

Wind: Admittedly I have no idea what sort of consistency wind has. But it does seem reasonable to assume the overall reliability of wind power will decrease as installed capacity increases, assuming we started with the most productive geographies first and then move to increasingly marginal areas.

In the same way that storm fronts travel through an area and bring high speed winds perhaps there is the opposite, where relatively sudden, large-scale lulls form?

To minimize the likelihood of blackouts we'd need to either:

1) Build sufficient excess capacity of wind/solar/hydro to overcome variance in output. This may not be feasible, if even possible, considering the points above.

2) Maintain fossil fuel peaker plants.

3) More nuclear for base load.

Having written these thoughts out I now realize your statement presumes we can ever (and always) meet 100% of electricity demand with wind/solar/hydro in the first place.
Same for me in France, nobody uses iMessage, part of the issue is the lower share of iPhones and the other part is iMessage being branded as an SMS app will mean it will never take off since SMS are dead.
Same could be said about Twitter.

Listen, you add a bunch of employees, some of them executives and a nice office with a caffeteria and you get easily over this number.

I think what people get wrong is what is profit for Truth Social. People who own and operate it do not think about profit as the money they get from the platform directly or through advertising, the profit is in having an alternative social circle where they can gather their follower base and reach them without being impeded by "censorship" from a platform like Twitter (sorry, X is just a ridiculous name).

In times past billionaires would keep their own newspapers even if unprofitable on paper just because they could create their own spin on the current events. That ability to control the narrative can be worth more than the cost of propping up a failing enterprise.

If you understand this, you might find that this thing actually is quite profitable.
I played for a living during 5 years in the early 90's. So before the Internet took off.
Of course there were some differences with OP's situation, e.g. because games were scarce I didn't play only poker but also backgammon, and basically any other game that had any skill and could be played for money.

Like OP, I decided to become professional because of the freedom, but also because I just liked games.
But after a couple of years these advantages start to fade away. First of all, you are not really free, especially when games are scarce: you have to be always available because if you miss a good game, it can take days before another one comes along. Also, the fun in playing games erodes if you play them day in day out.
Also, like OP points out, variance is brutal. The downswings can wear you out, sometimes I had to take a few days to recover.

But the main reason I eventually switched to a career in IT was something that OP also mentions: the main skill in making a lot of money, especially in live games, is not how well you play, but how good you are in finding wealthy suckers that want to play against you. This part really put me off in the end, it just wasn't me.
> In Martian greenhouses, that would be provided in the form of artificial fertilizer and/or organic waste.

Which requires supply from somewhere. How far you can go with ISRU depends on how big the colonisation development gets.
> This also applies to the crypto world, which, like poker, is zero-sum or worse.

Can we please avoid derailing this interesting topic by mentioning the inflammatory crypto scene?

We all know everything about it, and have all made up our minds about it, and no new information is being said about it.

Thank you!
A quiet night will take out both solar and wind. And that happens multiple times a year.

As I write it right now Denmark is producing 0 solar, and only 12.5% of its wind production. Because its cloudy and there's little wind.

So they have to import almost 40% of electricity from Norway and Sweden where electricity generation is propped up by nuclear
Poker players search for weak opponents to extract money from them in games where no one watches.

That is the income of full time poker players.
I didn’t read the whole thing, but the first part about Tom Cruise and his mother sounded very flawed: Of course the LLM could learn the reverse relationship if it had better data where the reverse relationship is a common occurrence. The point of the reversal curse argument (I guess) is that it should be able to learn the reverse relationship from entirely other examples [1], but seemingly is not.

1. That is, the LLM should be able to learn that “A is son of B who is female” implies that “B is mother of A”, regardless of who A and B is. It should then be able to apply this pattern to A = “Tom Cruise” and B = “Mary Lee Pfeiffer” and deduce “Mary Lee Pfeiffer is the mother of Tom Cruise” without even a single example.
Using GStreamer in your Flutter project – Pt.2 Linux[video]
You should compare with similar economies, so Germany and Spain (France has less industry so the almost 80 yo life expectancy for men is 'easier').
Not just languages. It's the case with everything. Easy to spot when you're tutoring someone. You can see they learned "force is mass times acceleration" or "for( ... ) is how you make the same code run multiple times" - they can tell you that when quizzed! But you know they haven't comprehended it until they can reverse it - "I need to compute the mass of the object, which I see accelerating this much under this force; I can pull that from F=ma -> m=F/a!", or "I want to run this code several times, I need a `for` loop!". And getting to that stage is often the longest and most difficult part.
The "difference" is only an advantage to attackers, in that executables are typically blocked as email attachments and Office macros are not.

Here's a ransomware incident report from someone opening an Excel document with macros enabled:

https://thedfirreport.com/2023/05/22/icedid-macro-ends-in-no...
Don't forget to read the room, culturally. In Northern Europe I would wager that most people would not appreciate random small talk from strangers as much as Americans do, I know I don't.
SiloGen launches a consortium to build the largest open LLM
Nice story! Curious, was the manager a technical person e.g. a former engineer?
Dependence is mostly no final decision.
The cost and lead time for independence is important in strategic considerations.
That’s funny, I just saw a job posting for Rivian Infotainment team
It isn't with a handwritten lexer/parser either, the real work starts after the parsing is complete. Of course, there are two possibilities: often changing them can either result in a cleaner, more readable result or a _real_ mess ;)
But you have to rewrite it by hand anyways if you want to get better (or usable) error messages and incremental parsing for a LSP.
Words are always semantic clouds. Not getting that is what sent philosophy down many a dead end, and the source of plenty of arguments regular people get into all the time. One doesn't need to try mapping between two languages - it's enough problem trying to map within the language itself.
In general the use of a shitload of breadcrumb or other filler will break a crabcake. Should just be a very light mayo based binder just to hold it together, and the lump of the crab meat should still be intact. I worked as a teen at one of the famous crab houses on the bay, they used really light mayo with the crab but then after weighing packed saltine crumbs around the outside tightly until it formed a ball, and then was fried. My grandfather, who was a chicken necker, did not use breading at all and shallow fried his crab cakes.
> When asked to transcribe and translate those three lines at the bottom, the AI got the general idea, but also made significant errors

> GPT-4 is quite useful for “getting the gist” of written sources in unfamiliar languages.

People don't like to deal with tedious details and issues like accuracy (perhaps separating the good historians from the bad). They seem to wish - and seeing general agreement from fellow dreamers and dismissing tiresome objectors they seem to believe - that somehow misinformation won't be a problem. I don't know how, but somehow, because everyone does it, everyone believes it. As if the zeitgeist of the post-truth era will save them and us from the consequences. As if accuracy (completeness, correctness, consistency) of information is like cooking - for most dishes, overcooked or undercooked isn't great but it's fine.

Information doesn't work that way: Unless you can read the original yourself - and if so, you don't need the GPT to translate - you have no idea if the GPT's 'gist' is correct - any element of it could be wrong, and likely some are. And a small mechanical error can cause devestating misunderstandings, such as a 'not' being attached to the wrong word (and remember different languages have very different rules about word order). If the GPT translates something as 'to our surprise, Jones, not Smith, was the Soviet spy', what does the original really say? Was it Smith? Jones? Maybe they were 'not' surprised?

The true, rational answer is that you have no idea what it says (without some outside information). Information where any element can be inaccurate is useless, and worse, dangerous: believing a falsehood is worse than thinking, 'I don't know'.
My childhood friend down the road was crazy about their catfish. I only have vague memories of Holly's but cool to see the motherland get a mention.
The amount of electricity used by appliances and lighting is negligible compared to that used by the air conditioner compressor. Even the air conditioning fan is hardly more than a few light bulbs.

So while it's good that the report quibbled, they might have gone to the effort to quantify their equivalent at least to an order of magnitude.
> To add a package, first create a GitHub repository for your package. While Inko's package manager supports the use of any Git repository (e.g. one hosted on GitLab), the above list is populated using GitHub repositories only.

So another community that wants to lock itself into Microsoft products as well as Git in general. Why should a user’s choice for DVCS & forge make them feel less supported or inferior?
Exactly. And asking what/who/which is the “Ninth” something will always fail (or randomly succeed)
From a quick glance, a "simpler" Rust with an Erlang like concurrency model seems like a very appealing language. It's also a sentiment I've seen repeated quite often.
technically, methane is coal (with extra hydrogen)
That is very often the case, yes.
With the interconnected nature of modern life, that BS probably touches an important part of your life
> LLMs in particular can be a very fast, surprisingly decent (but, as you mention, very fallible) replacement for Stack Overflow

I think that sentence nails it. For the people who consider "searching stackoverflow and copy/pasting" as programming, LLMs will replace your job, sure. But software development is so much more, critical thinking, analysing, gathering requirements, testing ideas and figuring out which to reject, and more.
> Exactly what constitutes "correct" varies from one situation to another. For example, fast inverse square root approximates multiplicative inverse: for situations such as games, its fast nearly-correct answer is a better trade-off than a slow definitely-correct answer.

Amazingly in topic, the famous constant 0x5f3759df from this algorithm was also thought to be derived from an approximate search algorithm because you need ~2^31 calls to determine the maximal relative error for a single constant---a big deal back in 1980s. A better constant 0x5f375a86 was only found in 2003, and took a few more years to be proven optimal (Robertson 2012, Moroz et al. 2016).
I don't know what to tell you, you are wrong. I drive a Tesla, I have specifically checked all of what I mentioned when I had this (in my opinion highly problematic) issue happen to me. Have you actually tried it?

Even the new stalkless cars have gear selectors.
The question then is, what heat? From the stars and moon is almost nothing. No idea what it exactly is, but assume that a clear sky at night has about -170 C temp (you are looking at the cold universe, only some CO2 in between to absorb). So the net radiation is always outbound.

And the best way to radiate are black (not the color but as in the definition of heat radiation) objects.
Maybe they shouldn’t drive at all then?
No blog post required! You just install the whole app on a dedicated piece of hardware on site.

But then deployment becomes more challenging ;)
But what if your phone goes first?
I'm not disputing your claims, but as a suggestion:

> A nuclear power plant is essentially a thermal plant plus the nuclear part so how would it be cheaper than a coal plant?

Fuel costs?