agnosticmantis

> Python and Dart, for example, have been much more popular recently than in the past, so it's reasonable to assume that the percentage of newer code bases in those languages is higher than in, say, Java.

And yet Python is the top fifth brown language? And also the top third loved language?

> … despite the fact that many materials — including graphene, frogs and pliers — can exhibit similar magnetic behaviour.

This is a dishonest argument. Frogs and pliers don’t levitate on a typical magnet in ambient conditions, so you can’t say the behavior is ‘similar’ just because ‘everything levitates in a strong enough magnetic field’. If your measuring stick can’t distinguish these two significantly different behaviors, it’s a useless measuring stick.

Also, more generally, the logic of science is statistics, not Boolean logic. We all know that

[(p —> q) and q]

doesn’t logically imply p, but still observing q makes p more likely when thinking probabilistically.

Overall I found the article to be very dismissive of weak evidence and also shortsighted when considering the potential applications that we can’t think of right now (even if those are not the typical hoped-for applications like efficient power transmission).

It’s a breath of fresh air reading about actual revolutionary science happening.

The deluge of news about non-replicable results, fabricated data, overhyped press releases from both academia and industry had become really depressing. For once after a long time it’s the real deal.

Even if this is not a RT superconductor, it’s now evident that the original authors didn’t cheat and are not crackpots as initially suspected by most.

In this particular case I’d be less cynical as even laypersons are anxious to know what’s the result. So it’s natural that scientists that have the lab equipment are rushing to replicate or falsify the results.

As a counterpoint, at least as far as ‘fundamental discoveries’ go, see the article by Sean Carol“ The Laws Underlying The Physics of Everyday Life Are Completely Understood”:

https://news.ycombinator.com/item?id=36808614

The fundamental stuff are all known, except for the ones you don’t encounter in everyday situations, which will as a consequence be harder for hobbyists to discover too.

I think we can start by checking whether energy is conserved given everything we know. If not, then you may have discovered a new particle/force.

(If we didn’t know about electromagnetic induction, and pushed the magnet through the coil, then we’d find that energy is not conserved.)

That’s a strange take. Those researchers were given the resources, the right incentives, the right environment for that kind of research to happen, at Google, in a time when LLMs weren’t all the rage.

“X Built a boat == the builders remain at X until they die” Is a strange definition of building something imo.

I never used the client while on windows (for decades) but for some reason started using the mail app on MacOS. (I recall I used to need to mess with POP/IMAP/SMTP addresses in the past but now I just authenticate once and it just works.) It’s still not an entirely pleasant experience (my biggest gripe is it doesn’t show full email addresses, so you don’t know which account received the email). But still beats having to type the browser and clicking a bookmark I guess.

> The goal of xAI is to understand the true nature of the universe.

Genuinely curious: Does anybody take this stuff seriously?

I just feel embarrassed to be working in tech (in Silicon Valley of all places), being associated with these charlatan clowns peddling nonsense like this and being praised for it.

At the scale of Google/Meta plateauing could just mean market saturation, not that ads aren’t working anymore. I’d be interested to see data showing that RoI has also been decreasing for advertisers or that advertisers have started to pay less because they don’t find ads worthwhile.

Wondering what people think of this (and similar ideas) and why they don’t have much traction.

Is the idea sound?

Thanks for the comparison!

Thanks for sharing! Does this teach one how to design circuits too?

Also, someone suggested ‘basic electronics: theory and practice’ by Westcott & Westcott [0] for learning hobby electronics. Could someone familiar with both explain how they compare?

0: https://books.google.com/books/about/Basic_Electronics.html?...

Even more surprised to see dogs in the fourth spot (third according to BBC). Are most of these pets or stray dogs?

Isn’t that federation?

See also: https://www.semafor.com/article/07/06/2023/twitter-is-threat...

It seems like there’s no edit button (yet).

Given the countless environmental challenges we are facing (and causing), we should more seriously and openly consider putting a stop to exponential population growth as an (at least short-term) solution. It’s astonishing how some people preach blind faith in our ability to just find solutions for problems caused and exacerbated by never-ending population growth without identifying it as the root cause. Why is it a given that the earth can just withstand whatever we throw at it?

Recording of the lecture:

https://youtu.be/tz-Bb-D6teE

This is in reference to “Read the masters, not their pupils”, a quote from mathematics prodigy Niels Henrik Abel. When asked how he developed his mathematical abilities so rapidly, he replied, “by studying the masters, not their pupils”.

Now I’m really tempted to create a Twitter account and start reading. Maybe that’s 3D chess by design by the CTO to get people to sign up. /s

That’s a good point. I think (in jest) the data is invaluable for training automated trolls, for which various state actors should be willing to pay good money.

But more seriously, maybe the value is in it being a real-time source of new data, albeit the signal is drowned in noise like a needle in a hay stack.

He needs revenue right now, and the other monetization efforts haven't panned out (blue checks, advertising, etc.). So he's trying to make a quick buck from user-generated data now that the LLM rush is at an all time high. For that he needs to limit access to the data in the first place, otherwise nobody would be paying for publicly available data.

> 3. We absolutely will take legal action against those who stole our data…

What does “our” refer to here? Does Twitter (i.e. musk) own the data in any sense? Or does he mean it as “we the people’s data”?

Very off-putting to read that sentence. Obviously he’s trying to monetize the user generated data in this LLM rush as other avenues to monetizations have flopped.

I haven’t used a Linux laptop in a while. Is there any that’s competitive to MBP M2 in terms of processing power and battery life? I’ve been working on an MBP M1 for ~1 years now and I’ve yet to hear the fan working or feel the heat (to be fair, it’s a work laptop and most development happens in the cloud). If only for this reason I find it hard to buy anything other than MBPs for work, unfortunately.

Also it seems like a business opportunity to start a newspaper outside Canada that does journalism for Canada. Then you’d appear in search results for free, while your Canadian counterparts would have to pay for ads to show up on the first page.

I’m guessing if/when this takes effect, the publishers will have to buy ads on Google and FB to attract readers that would previously find the content in the said platforms? Seems like a win for the two companies.

Maybe they mean it’s less random and less uncertain. The criteria are more transparent.

US immigration literally runs lotteries for various streams including H1b. It doesn’t feel great when your work/future/life depends so heavily on a coin toss. And we’re not yet even talking about being at the mercy of an immigration officer.

Aren’t lasers extremely susceptible to weather conditions? E.g. when it’s raining/snowing/cloudy, can the base station communicate with a satellite via laser?

> … which is kind of the rub with current LLMs to begin with, right?

No, the bigger problem with current LLMs is that even with high quality factual training data, they often generate seemingly plausible nonsense (e.g. cite nonexistent websites/papers as their sources.)

This is by design imo; they’re trained to generate ‘likely’ text, and they do that extremely well. There’s no guarantee for faithful retrieval from a corpus.