zipy124

Or without the cynical lens they just operate like CERN where they acknowledge everyone who without them could not complete the research. Hyperauthorship is common in particle physics for example.

Also noteworthy is that they already have their own version of ubuntu that is widely used: https://en.wikipedia.org/wiki/GendBuntu

One problem is who should pay for the data storage? Some of my academic experiments generated vast quantities of data. Who will pay to store it all, and how long should it be stored for?

It's not that they can't, but why would they? It's a race to the bottom commodity wise, much smarter to build on top of the model layer like Legora and Lovable than make the models.

Only under heavily gamed financial metrics. Using EBITDA for capital heavy businesses does not work like in typical tech businesses.

You can lose data though. Any open documents which aren't saved...

Yes but focussing more on long-term ownership, as opposed to the usual turn-around and flip or asset stripping methodology.

They are heavily debt financed I believe, almost $5 billion worth last I checked.

You see this in many things. Look at climbing for instance, or running. Once the first v17 had been done, suddenly many people did them. Or running with a sub 2 hour marathon.

Griffin and citadel less bailed him out, and more circled like sharks and made out with a good deal TBF.

Don't they just share the colossus 1 data center?

The data is from the federal reserve.

From the Fed's own description of the dataset "The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics."

Families would suggest household, not personal.

It was superseded by the antigravity CLI.

It's actually crazy that a music app struggles to play music many times. By far my worst big app experience.

Usually the ideas it that the theoretical maximum is not a local optima though, but some ideal global optima which you know you realistically cannot reach.

That is you know the data is some size, and memory throughput is some rate, and clock cycles is some rate etc...

You are entirely correct about the line of thinking if your assumptions are down a different line of thinking such as algorithmic estimates though, where you might miss some better way of doing things.

I've always used this method of working and can stand by it. For instance let's say you are working on a high-speed real-time image processing system. If you know that each image is 1080p for instance, that's 2 million pixels, and we will have 3 bytes per pixel for colour, then that's like 6MB per image (without compression). If you have 25 GB/s of RAM bandwidth, then there is a hard limit of ~4 thousand frames per second if you aren't even doing any processing. Therefore if you strip out your processing and are only getting say 400 frames per second, you know something is going wrong.

This can be applied roughly to anything. I find it very handy when thinking about CPU/GPU performance as well. For instance knowing that at 5GHz you have 5 billion clock cycles per second, which depending on instructions and pipe lining etc... can be roughly 5-30 billion operations per second per core tells you how long some process should take if you know roughly how many operations are required and the data size you are operating on.

Obviously as you drill down things get much more complicated, but they give you some rough idea about how fast things could be under some set of assumptions. Very similar to how a physicist works with models and assumptions.

This honestly is probably true, given when I help students write personal statements for applying to uni, the most common way they got into computer science is video games. I know for me 16 years ago that was true also.

I don't think we actually disagree here. I agree broadly with everything you said. My point was mainly I don't see a reason to support that assumption that if pay pushes out low performers, I don't see a reason why it wouldn't equally push out high performers? This goes on the assumption that lower performers optimise more for pay than higher performers?

> On the other hand, it also retains poor performers, who you want to steer to finding roles elsewhere

If paying people less encourages poor performers to find roles elsewhere, it encourages your high performers to do this even more probably...

The commenter is stating that respectable journals accept a lot of bad papers. This is actually very true.

I mean a lot of successful new tech companies were about side-stepping legislation. Some that are missing here are airbnb which effectively side-stepped fairly strict hotel legislation (Though there is a case to be made that it simply improved short-term lodging), and uber which side-stepped strong taxi/private-hire legislation.

This is one of the primary reasons that tech startups flourish in America but not in Europe.

The BBC reported on it many many hours ago at the same time [1] with the Department for Energy Security and Net Zero confirming there was an incident.

[1]: https://www.bbc.co.uk/news/articles/ce9793g34yvo

The BBC reported on it many many hours ago at the same time [1] with the Department for Energy Security and Net Zero confirming there was an incident.

[1]: https://www.bbc.co.uk/news/articles/ce9793g34yvo

The most interesting thing is like, contrail conspiracy theories from a weather date collection organisation? That seems... odd to say the least?

That isn't true outside of tech? Finance/big law/consulting/healthcare etc... all primarily work on cash bonuses.

Almost like a Veblen good lol. The quality is seen as higher because price is higher.

Those countries also just have lower salaries for all sectors. The USA is just exceptional in salaries for many professionals. Just look at software engineers pay in Europe Vs US....

still incredibly common. The key is that they give you very low latency information since you get it line by line. They're not too expensive tbh and getting speed data is not too difficult.

I've used modern high-speed cameras (>10k FPS in real-time streaming) and they just don't come close currently. Mainly an interface issue. There are some DMA/frame card alternatives but they haven't overtaken the market yet.

I mean this is kind of standard in a lot of industries? Businesses get reliability/support usually for the price increase. Just look at lots of industrial tech. Or business vs consumer 3D printers, or business vs consumer laptops etc....