I grew up in the Internet at that time, and it's certainly not how I type. So you might want to be more specific about which sites or subcultures you think this style is representative of?
I’m certainly no authority but i tend to write the same way for casual communication, came from the 90s era BBS days. It was (and still is) common on irc nets too. Autocorrect fixes up some of it, but sometimes i just have ideas i’m trying to dump out of my head and the shift key isn’t helping that go faster. Emails at work get more attention, but bullshittin with friends on the PC? No need.
I’ll code switch depending on the venue, on HN i mostly Serious Post so my post history might demonstrate more care for the language than somewhere i consider more causal.
Pain being a way to let you know that something is damaged is close to true--close enough not to quibble with. But fever is not a way to let you know that foreign bodies are being killed off--that's his claim, and it's wrong.
> But fever is not a way to let you know that foreign bodies are being killed off--that's his claim, and it's wrong.
querez's point is that the sentence is meant to be parsed as:
> pain and fever which are the bodies way of <<letting you know something is damaged>> and <<killing off unknown foreign bodies>> respectively
So the claim is that fever is the body's way of killing off unknown foreign bodies, not the body's way of letting you know something is killing off unknown foreign bodies.
The fact that one can ferret out what someone perhaps meant to say from what they did say doesn't change the fact that what they did say was wrong, and can be rightly criticized for being wrong. Someone else responded to such a criticism by writing "He said that" -- but that is false.
And I would make the point that these two things are not analogous, so they shouldn't be mentioned together in any case. The response to the misstatement that started this subthread was "I think what they're saying here is that you're not just suppressing a symptom, you're suppressing a sickness fighting mechanism", which is exactly right, along with a subsequent statement "Fever isn't just a symptom. It's a defense mechanism. The idea is that use of antipyretic drugs may make the infection worse" and which the misstatement completely muddies. It's weird how some people who didn't even make the misleading misstatement are so desperately trying to defend it for no good reason, while others are rationally pointing out how the statement is off the mark. Even with the edit, the statement serves no purpose, mixing up symptoms like pain that guide us psychologically with autonomic immune system responses.
> The fact that one can ferret out what someone perhaps meant to say from what they did say doesn't change the fact that what they did say was wrong, and can be rightly criticized for being wrong.
kruffalon said something ambiguous, with the intended interpretation (of that ambiguous part) being true and a secondary unintended interpretation being false - both interpretations grammatically valid.
querez tried to clarify the misinterpretation being made, but it looked as though their point was missed so I made it more explicit.
> It's weird how some people who didn't even make the misleading misstatement are so desperately trying to defend it for no good reason
I just saw some confusion so chimed in to try to clear it up. Only motive is that I feel like it's useful in a discussion for people to know what others mean, rather than arguing against a phantom point caused by miscommunication.
Arguably both Go and Python also have great stdlibs. The only advantage that JVM and .NET have is a default GUI package. Which is fair, but keeps getting less and less relevant as people rely more on web UIs.
Respectfully disagree. Python and Go std lib do not even play in the same league. I had to help someone with datetime¹ handling in Python a while back. The stdlib is so poor, you have to reach out for a thirdparty lib for even the most basic of tasks².
Don't take my word for it, take a dive. You wouldn't be the first to have adjust their view.
1. This might be a poor example as .net has NodaTime and the jvm has YodaTime as 3rd-party libs, for if one has really strict needs. Still, the builtin DateTime constructs offer way more than what Python had to offer.
2. Don't get me started on the ORM side of things. I know, you don't have to use one, but if you do, it better does a great job. And I wouldn't bat an eye if the ORM is not in the standard, but boy was I disappointed in Python's ecosystem. EF Core come batteries included and is so much better, it isn't fun anymore.
It should be "run inference on" in my opinion, and would be best shortened IMO to just "prototype, fine-tune, and run".
I'argue that "inference" has taken on a somewhat distinct new meaning in an LLM-context (loosely: running actual tokens through the model) and deviating from the base term to the verb form would make the sentence less clear to me.
Perhaps "infer from"? I was also taken aback by how they just decided to make "inference" a verb, though. A decent writer would have rewritten the sentence to make it work, similar to how a software implementation sometimes just doesn't work out. But apparently that's too much to ask from Nvidia marketing.
Funnily enough things like this show that a human probably was involved in the writing. I doubt an LLM would have produce that. I've often thought about how future generations are going to signal that they are human and maybe the way will be human language changing much more rapidly than it has done, maybe even mid sentence.
Because then the bugs we find in your app contribute back to chrome rather than Firefox. Then over time, chrome a becomes faster and more efficient browser which makes it harder to convince users to switch. Big picture thing.
It's a way of saying twice as fast and twice as slow have equal effect on opposite sides. If your baseline is 10 seconds, one benchmark takes 5 seconds, and another one takes 20 seconds then the geometric mean gives you 10 seconds as the result because they cancel each other. The arithmetic mean would treat it differently because in absolute terms 10 seconds slow down is bigger than 5 seconds speedup. But that is not fair for speedups because the absolute speedup you can reach is at most 10 seconds but slow down has no limits.
If half your requests are 2x as long and half are 2x as fast, you don’t take the same wall time to run — you take longer.
Let’s say you have 20 requests, 10 of type A and 10 of type B. They originally both take 10 seconds, for 200 seconds total. You halve A and double B. Now it takes 50 + 200 = 250 seconds, or 12.5 on average.
This is a case where geometric mean deceives you - because the two really are asymmetric and “twice as fast” is worth less than “twice as slow”.
There is definitely no single magical number that can perfectly represent an entire set of numbers. There will always be some cases they are not representative enough. In the request example you are mostly interested in the total processing times so it does make sense you use a metric based on addition. But you could also frame a similar scenario where halving the processing time lets you handle twice as many items in the same duration. In that case a ratio-based or multiplicative view might be more appropriate.
Sure — but the arithmetic mean also captures that case: if you only halve the time, it also will report that change accurately.
What we’re handling is the case where you have split outcomes — and there the arithmetic and geometric mean disagree, so we can ask which better reflects reality.
I’m not saying the geometric mean is always wrong — but it is in this case.
A case where it makes sense is what happens when your stock halves in value then doubles in value?
In general, geometric mean is appropriate where effects are compounding (eg, two price changes to the same stock) but not when we’re combining (requests are handled differently). Two benchmarks is more combining (do task A then task B), rather than compounding.
The geometric mean of n numbers is the n-th root of the product of all numbers. The mean square error is the sum of the squares of all numbers, divided by n. (I.e. the arithmetic mean of the squares.) They're not the same.
I'm not gonna edit what I wrote but you are interpreting it too way too literally. I was not describing the implementation of anything, I was just giving a link that explains why thinking about things in terms of area (geometry) is popular in stats. Its a bit like the epiphany that histograms don't need to be bars of equal width.
>> The freedom to waste time. The freedom to waste resources. And the autonomy to decide how.
> As the article notes, several companies (Apple, Google, etc.) could (currently) afford to fund such a lab, but there is no way their management and shareholders would approve.
Google did set up such a lab. The mission of Google Brain was literally to hire smart people and let them do work on whatever they want. ("Google Brain team members set their own research agenda, with the team as a whole maintaining a portfolio of projects across different time horizons and levels of risk." -- https://research.google.com/teams/brain/). Unsurprisingly, Google Brain is the place that originated the Transformer that powers the current AI craze (and many, many, many other AI innovations).
The current tech giants spend a lot of money on "research," where research means optimizing parts of the product line to the 10^nth order of magnitude.
Arguably, Google Brain was one such lab. Albeit with more freedom than normal.
Which is fine, it's their money. But then they (and the broader public) shouldn't bemoan the lack of fundamental advances and a slowdown in the pace of discovery and change.
As someone who worked at both Brain and DeepMind: their cultures were very different. Brain was bottom-up, open-field research whatever you want/care for. DeepMind was much more narrowly focused and massively more top-down.
A decent amount of people seem to be unhappy/leaving deep-mind due to the forced focus on AI and lack of freedom currently though. Therefore the point above still stands.
I use a very simple custom system prompt (not on my work machine at the moment, but essentially something along the lines of "for technical questions, please be concise and to the point, and when asked for code, omit explanations and emit just the code itself unless I ask for explanations"), and it does wonders.
It’s interesting that my default prompt is exactly the opposite one: “do not write the code unless I ask for it specifically”. I like to use LLMs as a discussion partner, but writing code is trivial after a good discussion and I can do that myself
I guess it depends on use-cases. I use ChatGPT a lot for "trivial" questions a la "how do I uncommit a specific file in my last git commit" or "how do I paste from one PIL.Image into another one". In the past I would have to search google, click on the StackOverflow link, and then parse that whole page. Asking ChatGPT to give me just the snippet is faster, so doesn't get me out of my flow as much.
So, with regard to Greenland, he specifically refused to rule out military action [0]. Which in diplomatic protocols comes very darn close to threatening a military attacks.
As far as Canada goes, Trump's national security advisors is on the record [4] saying he doesn't think there's any plans about this. Which is also an extremely uncertain way of talking about military action about your closest neighbor. Trump has repeatedly talked about making Canada the 51st state [1], and called Trudeau a "Governor" [2]. Here's a New York time article summing up the types of threats/attacks Trump made wrt. Canada[3].
> he specifically refused to rule out military action
Donald Trump has specifically ruled out a lot of things that he then promptly did. He's also followed through enough that his threats have to be taken seriously. As a result, you get a hodgepodge of half-assed threats, each of which can be plausibly denied until followed through on, at which point you're asked how you didn't see him doing the thing he said he would do.
