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Cake day: June 14th, 2023

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  • including the Slogan: ‘From the river to the sea – Palestine shall be free’

    As it should, this phrase and it’s Israeli counterpart “between the sea and the Jordan there will be only Israeli sovereignty” are often accompanied by calls for mass deportation at best and genocide at worst.

    These sentences are not bad on their own, but the parties from which they originate (Hamas and Likud) have transparent desires for war crimes and genocide.




  • 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.


  • Akisamb@programming.devtotumblr@lemmy.worldDots connected
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    6 months ago

    You are in a bubble. A neo nazi march was banned two weeks ago in France before being allowed again by the judicial system. The exact same scenario has been repeating for pro-palestine protests.

    At least in France, the scenario seems to be that the government wants to ban any controversial march and is being kept under control by the justice system.


  • 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.


  • It’s absolutely amazing, but it is also literally and technologically impossible for that to spontaneously coelesce into reason/logic/sentience.

    This is not true. If you train these models on game of Othello, they’ll keep a state of the world internally and use that to predict the next move played (1). To execute addition and multiplication they are executing an algorithm on which they were not explicitly trained (although the gpt family is surprisingly bad at it, due to a badly designed tokenizer).

    These models are still pretty bad at most reasoning tasks. But training on predicting the next word is a perfectly valid strategy, after all the best way to predict what comes after the “=” in 1432 + 212 = is to do the addition.









  • I don’t agree. Curvy roads are dangerous, but there are much more conflicts in cities. You’re not going to have many pedestrians in curvy mountain roads.

    That said, you are right that the ideal comparison would be int the same city. But I’m not sure that the data exists, I’ll have to look this afternoon.

    That said, even if my data is not perfect, it’s much better than taking one accident and saying that self driving cars are dangerous. They are not going to be magically better than humans, after all driving is a difficult task, but we should at least crunch the numbers before dismissing them.