Now instead of just querying the goddamn database, a one line fucking SQL statement, I have to deal with the user team

Exactly, you understand very well the purpose of microservices. You can submit a patch if you need that feature now.

Funnily enough I’m the technical lead of the team that handles the user service in an insurance company.

Due to direct access to our data without consulting us, we’re getting legal issues as people were using addresses to guess where people lived instead of using our endpoints.

I guess some people really hate the validation that service layers have.

I’m afraid that would not be sufficient.

These instructions are a small part of what makes a model answer like it does. Much more important is the training data. If you want to make a racist model, training it on racist text is sufficient.

Great care is put in the training data of these models by AI companies, to ensure that their biases are socially acceptable. If you train an LLM on the internet without care, a user will easily be able to prompt them into saying racist text.

Gab is forced to use this prompt because they’re unable to train a model, but as other comments show it’s pretty weak way to force a bias.

The ideal solution for transparency would be public sharing of the training data.

And cow feed is also grown with tons of pesticides and you need much more of it for less tissue at the end.

I have hard time seeing clothing with a bigger environmental than leather.

Why would java have an impact on battery performance ? Pretty much all credit cards run java for their encryption algorithms, and they need pretty much no power to run.

These models do not see letters but tokens. For the model, violet is probably two symbols viol and et. Apart from learning by heart the number of letters in each token, it is impossible for the model to know the number of letters in a word.

This is also why gpt family sucks at addition their tokenizer has symbols for common numbers like 14. This meant that to do 14 + 1 it could not use the knowledge 4 + 1 was 5 as it could not see the link between the token 4 and the token 14. The Llama tokenizer fixes this, and is thus much better at basic algebra even with much smaller models.

Most surprisingly, the inspectors observed barefoot employees working in a sterile area of the facility, where they should have been wearing shoes—plus gowns, gloves, and shoe booties. (The barefoot workers were also not wearing gowns or gloves.) A production manager puzzlingly told FDA inspectors that shoeless work is “standard practice.”

They were supposed to cover everything including the feet.

Reference counting is a GC though ?

It’s a bad one sure and will leak memory in cases of a cycle which most tracing GC are able to do.

It’s main advantage is that there are no GC pauses.

https://en.m.wikipedia.org/wiki/Reference_counting

WordPress wirh custom templates running on a LAMP stack.

Same principle why Google can index pretty much all books in existence. They were sued over this and won. Same thing will happen here.

As long as these models are not providing the copyrighted material to their users they should be safe.