kleiba2
kleiba2 on Hacker News
> for starters how will you even know what hardware and inference backend is being used by RandomAiProvider3284.com? you can't.From the article:
A typical request to the open model Kimi K3 emits about 0.4 grams of CO₂ in Sweden, 1.6 grams in Ireland, 2.5 grams in Germany and 3.2 grams in Texas, on identical hardware — 8.5 times more in Texas than in Sweden.
-> So the comparison is based on the assumption that identical hardware is used.
Also from the article:
Emissions estimates are based on the current average emissions intensity of each regional electricity grid, which has been the norm in greenhouse gas accounting.
Interesting that AI apparently doesn't write papers for humans: even experts struggle to understand them. But other AIs do. So AI basically writes papers for other AIs.
They just won a state election a few weeks ago, and they're also ahead in nation-wide polls - how can you ban a party that receives the majority vote of the population?
> This is the problem with having a king, all it takes is one moron and you destroy your country.Can happen in democracies just as much.
According to the Volkswagen website, a Golf starts at €29,835 € (incl. VAT) while according to the Ford website, a Ford F150 XL (which isn't exactly a monster truck) starts at $39,585 which Google tells me is around €35,263 (excl. VAT).
Is it not possible to get your point across using more decent language?
P.S.: I've got to admit, though, that I was always impressed by the really great quality of Gentoo's documentation!
I tried Gentoo some 20 years ago or so for fun at home. I guess my naive thinking was that software specifically compiled for my hardware would run noticeably faster and "better".
But I didn't last for very long. I remember starting the install for a bigger app before going to bed, only to find the thing still building when I woke up. And as for the dream of more tailored builds, I never really noticed anything much different - I probably was too uneducated about build configurations, or - more likely - the differences just didn't matter too much.
Eventually, I switched to Ubuntu and never looked back.
So, I'm curious - is anyone using Gentoo as their daily driver, and what is the main incentive for you?
"Noticeably different from the very first moment: the aluminium key offers a glimpse of what is to come. Even before the engine starts, a connection to the car is formed, transforming anticipation into something tangible."
I would fire the marketing team.
Just a little feedback: one of my most hated dark patterns in design is when you give the user the impression that they can try out your website but they actually can't. That's the case on your website: there is a text field making it seem like you can give your site a spin, but as soon as you hit the submit button, you get a pop-up telling you that you have to sign up first. And that after I already spend some (admittedly small) effort to craft a sample text.
I personally hate that pattern, and my default reaction is to immediately close the tab.
Perhaps you could change the landing page to avoid that negative first impression?
Tell your important message on any screen:
503 Service Unavailable
There are different ways on how to implement remove, but one way to do it is to overwrite the (key, value) pair to be removed with a special "tombstone" symbol that is different from null. Another way is to shift all elements with the same hash value as the one to be removed one index to the left, and null the final position.
There are cases where contains or get would have to iterate over the whole array, basically when all the previously added elements hash-collide, i.e., are mapped to the same start-index. But every hash-implementation has pathological cases where the access methods get slow -- but if the keys are sufficiently random, you don't expect such cases to occur in practice.
Right, that's the beauty of this simple approach: there's only one array and it doubles as the storage for buckets. But yes, the table will have a maximum size after which you cannot add more entries. That is, in practice you would create a new hashtable with a larger capacity and rehash all the existing entries into the new, bigger table (in practice, you would do that even sooner than that, namely when a certain load factor is passed - see my previous comment where I alluded to the role of the load factor).
The cool thing, however, is: if the size of the new hashtable is double the size of the old hashtable, your amortized insertion costs are still only O(1)!
(And you don't just have to take my word for it: take my original comment and paste it into the AI interface of your choice and have it create a concrete implementation. Ask it to add a remove operation, and an automatic doubling of the array size + rehashing when the table reaches a load factor of, say, 0.7 -- the resulting code should be very manageable, and then you can run your own tests and measure times!
This is maybe not the smartest way to do hashing, but its appeal lies in its simplicity and hence compactness of implementation. There are many cases where you don't even need a 'remove' operation, and where you never have to worry about growing the array because you know that you're only ever going to hash a certain number of elements at most.)
The expected or amortized complexity of the standard hash table operations (put, get, contains, remove) are all O(1) for linear probing (under the usual assumptions for the hash function and as long as the table does not get too full). Of course that doesn't shield a single operation from being O(n) in the worst case.
Taking out a window and putting the battery in front of where it used to be was no option, I suppose?
Maybe because "economists don't know what they're doing"?
I always liked that idea of just doing a linear wrap-around sweep through an array that holds (key, value) pairs, until you find the pair with the key you're looking for (for 'get' or 'contains?') or an empty spot (for 'put'). The trick to make this fast is that the hash function (key -> int) tells you at which index to start the sweep.
No secondary data structures, super simple to implement, and it works great for small use cases.
I suppose one thing they're trying to express here is the idea of the equilibrium price of oil, by marking the intersection of the demand line with the two supply lines. However, why they are lines in this graph in the first place, or why they are located at these specific positions is unclear to me.
So you're reading it as a "prerequisite chart"? That seems odd because the common way to read graphs is that what's reported on the y-axis is a function of the values of the x-axis.
I find it also hard to read it that way when I look at that "Price in February -> Price in April" annotation: if those two points on the y-axis mark points in time, then so do the correlating points on the x-axis. I can only read that as "from February to April, the demand went up while the prices went down".
Can anyone explain how to read that first graph? Like, there's a line for demand, say, but given the axes labels, it seems to say "for greater demand, the price goes down", so the exact opposite of what basic price theory predicts.
Same for the supply lines, just the other way around.
Also, the use of straight lines indicates a linear relationship. Is that really the case in practice?
Spoiler alert: "But ultimately, the bulk of the money heads in the direction of the source of the oil itself – the oil companies. [...] The money largely goes to company owners – meaning shareholders"
The problem is really the unpredictability: some LinkedIn pages can apparently be accessed publicly without a login, others cannot. But perhaps that fact alone would be reason enough to block it entirely in Google searches?
I don't have a LinkedIn account and don't really care about it. The one thing, however, that bothers me to no end is all the many, many times when a LinkedIn page comes up near the top of the results to a Google query, then I click on it, and chances are I don't get to the actual information, but to the LinkedIn log-in page.
Not that I think that this is LinkedIn's fault, but I assume Google's rationale is that "everybody has a LinkedIn account" so it's fine to include result pages that cannot be accessed without one.
There are deeply committed Catholics and deeply committed Protestants, as well as relatively nominal or culturally affiliated members of both.I think your statement that they "reject the theology" cannot be sustained, but it could be true that tradition plays a bigger role in Catholoicism, but protestantism itself certainly has its own traditions.
Taking one's religion seriously does not by itself constitute fanaticism. Flying a plane into a highrise because you think that is what your religion commands certainly is. That is not to say there aren't any Christian fundamentalists out there, there certainly are. But just because you do not relate to a religion, or religions in general, does not automatically make everyone who disagrees a fanatic.
So I suppose recycling is not a thing in space?
Your original statement was about "religious fanatics", not about normal. There are billions of people on this planet who are Christian and believe this or similar ideas. You may beg to differ but calling all of them fanatics might be a bit extreme, don't you think?