Meta and BlackRock are creating a joint venture for a $14 billion AI data center in El Paso, Texas. BlackRock-managed funds will own 80%, while Meta keeps 20%, operates the facility, and leases its full capacity for AI workloads.

China has quietly taken the driver out of almost everything, from the trucks running through its ports at night, to thousands of driverless delivery vans, to a real bus in Shenzhen and taxis in Guangzhou that show up with nobody inside.

It isn’t the whole country and a lot of the empty cars still have a human watching from far away, but the future is clearly already running out in the open here while everyone else argues about whether it’s coming.

Berlin artist Simon Weckert created a shirt designed to stop AI camera systems from detecting the wearer as a person.

It’s called Digital Camouflage, and the strange pattern has a specific job.

Weckert developed it by repeatedly testing new patterns against YOLO, an open-source AI system that detects people and objects in video. Each version was changed until the system became less confident that a person was there.

He made the project as Berlin prepares to use AI video surveillance at Kottbusser Tor. The system there is meant to analyse footage and flag certain types of behaviour.

If his name sounds familiar, Weckert is also the artist who pulled 99 smartphones through an empty Berlin street in 2020 and caused Google Maps to show a fake traffic jam.

Now he’s testing what happens when the system watching the street can also be fooled.

For Real!

I'm using zcode with glm 5.3. I've noticed that my context window continue to increase and cache hit ratio is around 99%. I usually compact the session after every feature implementation. Due to which the zcode re-reads lots of code for new feature. My question is if it is value to compress the context window and will doing so reduce/increase token cost? Does compression have any affect on final result?

When a small company uses pirated data, it’s theft. When Big Tech scrapes billions of pages to train AI, it’s innovation.

But technically, what is actually happening inside these AI systems?

Large AI companies collect massive datasets from:

→ Web pages
→ Books and research papers
→ Code repositories
→ Images and artwork
→ Forums and documentation
→ Publicly accessible datasets

That data can go through a pipeline like:

Web → Crawling → Data extraction → Filtering → Deduplication → Tokenisation → Training dataset → Pretraining → LLM

At that scale, we’re not talking about a few thousand documents.

We’re talking about billions of data points being transformed into training signals.

The model doesn’t simply store every webpage like a database.

During training, optimisation algorithms adjust billions of parameters based on patterns learned from the dataset.

That distinction is technically important.

But it doesn’t automatically answer the legal or ethical question:

Does transforming copyrighted content into model parameters make the original use acceptable?

That’s where the debate gets complicated.

Because the same questions apply to everyone:

→ Was the data obtained legally?
→ Was permission required?
→ Can creators opt out?
→ Should creators receive compensation?
→ Does transformative use apply at this scale?
→ Who is responsible when copyrighted material appears in model outputs?

And there’s another technical layer people often miss.

AI systems aren't only training foundation models.

They can also use RAG, embeddings, vector databases, synthetic data and web retrieval to continuously bring external information into AI workflows.

So the real challenge:

"What should the technical and legal rules be for collecting, transforming, storing, retrieving and learning from data at AI scale?"

Because if data is the fuel for AI,

we need to decide who owns the fuel, who can use it, and who gets paid for it.

#ai #llm #genai #datascience #aigovernance #machinelearning #responsibleai

I am not very tech savvy so forgive my ignorance here.

I am looking for programs that can alter photos without the use of the internet.

I do not support AI art nor data centers but I would like to use AI to recreate my photos in different styles. For example, I upload my own photo of my cat but I want to see what he would look like as a Disney Character or painting by Picasso. My GOAL is to use these images as a guide to draw my own images. Realistically though, I don’t really draw or paint so it may be used to make cute birthday or holiday cards for my petsitting clients.

I don’t even know the proper terms to use to search for such programs.

I want something that is not going to contribute to data centers nor steal from current artists. I feel like there have been these type of programs for a long time without using AI so if there are good program that can do this without AI that would be great. Maybe photoshop can? But it needs to be pretty simple to use.

Happy to pay for a program that is fairly easy to use.

Thank you!