This is true for only red and green loght detecting proteins (opsins) - the blue opsin gene is on chromosome 7.

The red and green detecting proteins have an interesting history in humans.

Fish, amphibians, lizards and birds have 4 different opsins: for red, green, yellow and blue colours. And the blue opsin sees up into the ultra-violet. Most animals can see waaaay more colours in the world than we (or any mammal) can. So what happened that makes mammal vision so poor?

It’s thought that all mammals descend from one or a few species of nocturnal mammal that survived the catastrophe that wiped out the dinosaurs at the end of the Cretaceous. The colour detecting cells (the cones) need a lot of light compared to ones that see in black-and-white (the rods) and therefore nocturnal animals frequently lose cones in favour of the more sensitive rods for better night vision. The mammals that survived the Cretaceous extinction had also lost the green and yellow opsins while keeping red and blue - basically the two different ends of the light spectrum.

Consequently today most mammals still have only 2 opsins so your cat or dog is red-green colourblind.

Why do humans see green? Probably because our monkey forebears, who lived in trees and ate leaves, needed to distinguish red leaves and red fruit (visible to birds) from the green background.

But how did we bring back the green opsin? A whole section of the X chromosome (where the red opsin is coded) got duplicated in a dna copying mistake and then there were two genes for red opsins. As there are different alleles (versions), they could be selected for independently and so one red opsin drifted up the spectrum to be specific for green. So our green opsin is a completely different gene to the green opsin in fish, birds, etc. This kind of evolution happens a lot which is why, for example, there are many families of similar hormones like testosterone and estrogen. And steroids too.

All junior devs should read OCs comment and really think about this.

The issue is whether is_number() is performing a semantic language matter or checking whether the text input can be converted by the program to a number type.

The former case - the semantic language test - is useful for chat based interactions, analysis of text (and ancient text - I love the cuneiform btw) and similar. In this mode, some applications don’t even have to be able to convert the text into eg binary (a ‘gazillion’ of something is quantifying it, but vaguely)

The latter case (validating input) is useful where the input is controlled and users are supposed to enter numbers using a limited part of a standard keyboard. Clay tablets and triangular sticks are strictly excluded from this interface.

Another example might be is_address(). Which of these are addresses? ‘10 Downing Street, London’, ‘193.168.1.1’, ‘Gettysberg’, ‘Sir/Madam’.

To me this highlights that code is a lot less reusable between different projects/apps than it at first appears.

Typically you need about 1GB graphics RAM for each billion parameters (i.e. one byte per parameter). This is a 405B parameter model. Ouch.

Edit: you can try quantizing it. This reduces the amount of memory required per parameter to 4 bits, 2 bits or even 1 bit. As you reduce the size, the performance of the model can suffer. So in the extreme case you might be able to run this in under 64GB of graphics RAM.

I think that’s a better plan than physically printing keys. I’d also want to save the keys in another format somewhere - perhaps using a small script to export them into a safe store in the cloud or a box I control somewhere

You need at least two copies in two different places - places that will not burn down/explode/flood/collapse/be locked down by the police at the same time.

An enterprise is going to be commissioning new computers or reformatting existing ones at least once per day. This means the bitlocker key list would need printouts at least every day in two places.

Given the above, it’s easy to see that this process will fail from time to time, in ways like accicentally leaking a document with all these keys.

If you’re pushing everyone’s buttons it’ll end badly.

Two more examples: Dredd and Ex Machina.

There is non-zero risk in every surgery, and this is a major surgery. There is non-zero risk of very very severe consequences: brain infection, stroke being just some. While these risks are low, they are non-zero. The volunteers have the possibility of losing everything.

Java programmers are also functionally illiterate

I must not use jargon.

Jargon is the mind-killer.

Jargon is the little-death that brings total confusion. I will face the jargon. I will permit it to pass over me and through me. And when it has gone past I will turn the inner eye to see its path. Where the jargon has gone there will be clarity. Only sense will remain.

Elon Musk didn’t build the company.

Elon Musk invested into the company,

That’s what I said a couple of paragraphs later

Elon sounds like he’s experienced, skilled and is approaching things from a theoretical or ethical or other grand point of view. He used to impress me with his approach on building an electric car company with full self-driving vehicles in the 2010’s. I wasn’t a full believer, but I thought he was competent and wanted Tesla to succeed.

Then he went and bought Twitter. As a software engineer all my life, and in the startup scene, and having worked in a failed social media platform, I have some experience. Everything he’s said about Twitter is crap and everything he’s done is stupid. And the results speak for themselves.

I’ve seen people say that Elon sounds great about things they don’t know too much about. But when the topic comes to things they do understand, Elon clearly is wrong.

He started his career with hundreds of millions of dollars, and he bet it all on a couple of businesses be bought (he was never a founder, always a purchaser).

Basically he’s been lucky twice (Paypal and Tesla), but each of these won 10-100x on his initial stake.

It’s called a bollock dagger and, yes, it’s really phallic especially when holstered at your waist.

Disagree with your disagreement. I also have an M1 and was a quite early adopter (within 3 months of launch). It was really snappy compared to my Intel Air it replaced. From the get-go. Even for apps that were still x86 code.

Things definitely improved over the next 9 months, but I was and am a really happy camper.

This is exactly the answer.

I’d just expand on one thing: many systems have multiple apps that need to run at the same time. Each app has its own dependencies, sometimes requiring a specific version of a library.

In this situation, it’s very easy for one app to need v1 of MyCleverLibrary (and fails with v2) and another needs v2 (and fails with v1). And then at the next OS update, the distro updates to v2.5 and breaks everything.

In this situation, before containers, you will be stuck, or have some difficult workrounds including different LD_LIBRARY_PATH settings that then break at the next update.

Using containers, each app has its own libraries at the correct and tested versions. These subtle interdependencies are eliminated and packages ‘just work’.

Exactly. And all the core internet encryption and signing algorithms are fully open source. Eg RSA, AES, DIffie Helman. And these are the algorithms the US (and most other western) governments require when sending data to or from or within there servers.

Exactly!

While the continents might look like they fit together, and the rock types and ages and fossils match at key points all down the coasts from Canada/Scotland all the way down to South America and South Africa, how on earth (sorry) would you explain how the continents are thousands of miles apart?

One theory posited the earth spinning so fast centrifugal forces ripped ehat would become the moon out of the Pacific, sucking Eurasia and America into the void.

That’s a Randall Monroe WhatIf if ever I saw one. Think of the energy involved! All life on earth would be extinct.

So these theories were laughed out of scientific court. Until Vine and Matthew’s seminal paper on magnetic stripes being mirrored over the mid ocean ridge showed there had to be something forcing the plates apart.

Which, will also hurt the call center manager, until they hire enough staff to answer the fucking phones in less than 30 minutes.

It’s all software, even the stuff on the graphics cards. Those are the rasterisers, shaders and so on. In fact the graphics cards are extremely good at running these simple (relatively) programs in an absolutely staggering number of threads at the same time, and this has been taken advantage of by both bitcoin mining and also neural net algorithms like GPT and Llama.

Not quite. The drug causes heart irregularities in some people at therapeutic doses, and this killed some of those 17k people. It just doesn’t quantify it here.