bestatsiege_01

The western world, the US in particular, already has outrageous abundance.

And yet problems of despair, poverty and marginalization continue to exist.

5-10% of people experience some level of food insecurity. Is that really because of a lack of resources??

It seems to me like we have a resource allocation problem, not a resource generation problem.

This is not an argument for some form a socialism. But instead an argument that progress in the field of social organization would be more productive than progress in the field of technological disruption.

And I love tech.

I think Elon is right about the idea of mind viruses. He just hasn't taken the premise far enough. All of us are infected by the algorithms around us, MAGA, Woke, MAHA ect. are all "mind viruses".

I doesn't matter how smart, compassionate, empathetic, creative or dynamic you are. As soon as you expose yourself to the algorithms you become infected. The more exposure the deeper the infection.

With respect to:

>> they did just clever algorithm and heavy profiling to stole your organic traffic

>Not sure if you had a stroke while writing this, but this makes no sense.

I have only ever been a buyer; so my technical understanding of the back end implementation is incomplete.

However, I think the point OP is trying to make is that the back end of the ad targeting infrastructure ends up attributing "spend" to folks who would have otherwise been organic traffic and found your site anyway. ie placing your ad in effective organic pathways and/or in front of well targeted users.

This of course makes sense. A well targeted ad is going to be presented to lots of people who would have otherwise been organic traffic.

This is just a problem with measuring ROI on ad's in general though. I think what has changed is improved attribution of digital ad's has confused people. They see 10 clicks, $5 spend, 1 sale @ $10 and think a 200% ROAS.

In the old days (and still sometimes for non digital) ad effectiveness was measured as a lift over baseline. Different media had different decay rates.

Depending on your digital property, a similar model may need to be applied to your digital campaigns. As I understand though, this is harder to do in modern times with digital ad's.

My hypothesis is that CA's could have input and output cells, then just run the CA, pass a single or continuous input and then parse the outputs when available.

But - I haven't been able to get such a concept to work. I maybe missing some fundamental theory / understand which prevents such a structure (or at least limits is value).

One major challenge is how do you train an unconstrained process?

Ill take a look at Neural CA's. thanks for sharing.

Thanks for sharing Neural CA's. I'll spend some time on them, much easier to train a DNN.

I have recently learned more about this. As I understand it goes something like this.

The legal representative of a foreign company in Brazil is expected to be legally responsible for the actions of the company in Brazil. This seems to make sense as Brazil probably thinks having individuals be personally liable for company actions to improves alignment with local laws and gives Brazil more leverage over otherwise exceptionally powerful global organizations.

However my understanding of "Legal Representative" is the North American understanding. A lawyer who is representing the company and not liable for the companies actions (those would be the directors).

I think these articles would do well to add this clarification as threatening to in-prison, and freezing the accounts of a lawyer representing a client in court is wild.

Doing the same thing to a person with direct legal liability is a little more sane.

I suspect The Guardian and X's accounts are both correct and it comes down to the expectation of the Legal Representative in the Brazilian system.

I have explored trying to make global state CA systems, with no success. If anyone has examples of trainable global state CA systems please share, I'd love to learn more.

My idea was that there would be global information but local rules. And the local rules depended on the global information. However I struggled to train such a system and gave up. I would like to go back to it though and some expert perspective might be enough to push me back to it.

I find CA's interesting because they are both continuous and could conceptually vary the amount of compute attributed to a particular problem. NN's can't really do either of these things.

(I appreciate LLM's vary the amount of compute based on the question. But just running the same model over and over seems like an immature method, there must be a better way.)

Where/How does The Guardian article conflict with X's statement?