kbrannigan

So in a way carving things in stone or clay was probably the right idea. A silly thought, maybe we had computers before

So in a way, old inscriptions in clay tablets, carvings in Hieroglyphs , Nsibidi and other ancient languages are technically encrypted.

We needed to decrypt them first.

That actually makes a lot of sense. Thanks for that insight.

What is a criminal? What is crime? In the USA, it was a crime for an enslaved Black American to learn to read and write? Attempting to escape was also a crime.

What about the crimes happening in company boardrooms rather than on the street corners?

People often call crime, individual offenses and think of certain racial groups, while ignoring real crimes committed by corporations led by other racial groups.

The crazy thing is that the greatest harms are caused by people who are not target of surveillance technology .

With websites i went back to 90s styles. Hyper dense in information. Anything clickable is a link. A button is for Write actions.

Interactive element are distinct from text.

If webpage page is an interactive canvas , make the canvas the main thing ad text as support.

If you start mixing the two idk..

Model are trained on them in 2026 .

Me Raw php .

Many people here have machines that can handle all of AOL , yahoo, msn of 2001 combined in their closet .

I have been going backwards in time as an experiment . I use mature extremely documented tools . Has to be at least 20 years old

That is a very interesting perspective. What is the purpose of that corpus. Are all theorems or axioms useful?

How big are mathematics? Is it as big as the universe?

Hmm, hence the issue. It’s like chopping down a tree to make a box of matches. I wish the next generations of models don’t rely too much on markdown documentations which seems to be a human way of not writing code. Sometimes the code is just a little bit more structured to be honest , often times I feel like I might as well just write the code.

What does that mean. Taking them down because the project failed or just replacing it?

It's not always larger models. Often time it's a smaller model fit for a specific use case. In the future we will see 16B models that are for : Legal, Healthcare, Science, Software Engineering, Education, Forestry, Music production

Such a massive leap at averaging possible use cases from previous data collected.

My guess is : collect all the prompt and their satisfaction score. group them by similarity . For each group pretrain the next model on that . Get these results ready.

Next model generation feed them back those answers.