There are 7 million people who would agree with you, if they could.

It’s an unrelated Andor reference.

Great show, if you haven’t seen it.

forcing many users to consider the unthinkable

Use a firefox clone and ublock?

(and linux, btw)

I have friends everywhere.

CFD = Computational Fluid Dynamics.

It is kind of what they said, you’re right. I was more pointing how how it could be that they could ‘sense the vibes’ of a CFD result to determine if it is accurate or if the model decided to do something weird. Since it’s a chaotic process and also an artificial one, the starting conditions can yield results that are impossible/not based on reality.

If you look at enough of them you start to notice the kinds of things that go wrong. They would also have a pretty good idea about how their design should perform and if the simulation shows different they’d first want to troubleshoot the simulation before attempting to re-design whatever system they’re creating.

That is an insightful question.

The answer is that we actually understand chaos in a way. It isn’t unpredictable in general, it’s just hard to say how any given situation will evolve but we can understand a lot about how all systems will evolve.

I’m not good at explaining, but some content creators cover this topic pretty well. If you’re interested, here’s a video about it from Veritasium: https://www.youtube.com/watch?v=fDek6cYijxI

It’s a super exciting time for so many fields of science. Transformers are really the key discovery that’s made modern AI what it is today and we’re only barely scratching the surface of possible applications.

The future is going to be weird in ways we can’t even imagine.

Anfinsen won the Nobel in 1972 for showing that the amino acid sequence is what is responsible for the 3D structure of proteins.

Since then we’ve been able to take images of protein’s structures using xray crystallography but that is a painstaking process. The ability to accurately predict a protein’s structure from an amino acid sequence has been an unsolved problem until very recently.

It wasn’t until 2024 that Hassabis, Jumper and Baker won the Nobel for their work in predicting protein structure (using an AI called AlphaFold) and computationally designing new proteins.

The ability to create arbitrary proteins is new and will revolutionize some fields of medicine (like cancer treatment) and, to me, is a much more impressive use of AI.

LLMs are interesting but they are incredibly over-hyped as far as ‘changing the world’ goes, imo.

Those kinds of simulations are inherently chaotic, tiny changes to the initial conditions can have wildly different outcomes sometimes to the point of being nonsensical. Also, since they’re simulating a limited volume the boundary conditions can cause weird artifacts in some cases.

If you run a simulation of air over an aircraft wing and the end result is a mess of turbulence instead of smooth flow then you can assume that simulation was acting weird and not that your wing design is suddenly breaking the rule of physics. When the simulation breaks it usually does so in ways that are obvious due to previous testing with physical models.

I’m failing to see why the creative writing machine is better than a simulation set to ‘rough’.

The problem is that you saw AI and thought LLM.

Machine Learning is a big field, AI/Neural Networks are a subset of that field and LLMs are only a single application of a specific type of LLM (Transformer model) to a specific task (next token prediction).

The only reason that LLMs and Image generation models are the most visible is that training neural network requires a large amount of data and the largest repository of public data, the Internet, is primarily text and images. So, text and image models were the first large models to be trained.

The most exciting and potentially impactful uses of AI are not LLMs. Things like protein folding and robotics will have more of an impact on the world than chatbots.

In this case, generating fast approximations for physical modeling can save a ton of compute time for engineering work.

They’re doing it to mess with the delivery robots who would have a perfect record if not for the bus stops being placed in their path constantly.

Going a millions different ways is more in the FOSS spirit than starting off by saying ‘everyone will use this list of software’. They can’t know what will be the best fit for everyone so they’re approaching it flexibly.

They can iterate in the future or come up with standards as they need, but in the beginning it’s better to try a lot of different things to see what people discover.

What’s crazy is, bus stops, and their associated shelters DO NOT MOVE.

TIL

I haven’t used it in a few years, I use a certain anonymous rodent to get my books now.

Is it possible to get her Kindle books on the Kobo or is the DRM a nightmare nowadays?

Calibre has a plugin for that: DeDRM

Now do Facebook, Twitter and Reddit.

Secure Boot has nothing to do with Microsoft, it’s a UEFI feature.

You can enroll your own Platform Key and have complete control over the entire Secure Boot system.

https://wiki.archlinux.org/title/Unified_Extensible_Firmware_Interface/Secure_Boot

I use a signed Unified Kernel Image to use Secure Boot and my machine has zero Microsoft software on it. (Arch, btw)

Also, it’s a low sample size so the variability will be massive.

A 50% increase sounds like a lot but, like you said, it could also just be one or two more than the previous year.

Given that they’re considering Flock, I’d guess that Flock is feeding them fear-porn statistics like this. It’s misleading but most people don’t understand statistics enough to know that they’re being misled.

On the ISS missions the astronauts have a weight allowance that they’re allowed to take. It may be the same case here.

I went into my bathroom and it was full of electromagnetic radiation and 5G. Checkmate, atheists