Recent comments in /f/technology

StruggleBus619 t1_j8vpds0 wrote

Correct, as far as I know that is still in place for some unknown amount of time. Alongside that initial report about the deal from 2021, was info that Microsoft was working with Qualcomm and MediaTek on chips for ARM based Windows PCs. When ever Microsoft decides it's ready to launch and move forward with those is when i think the deal will magically end and Windows for ARM will be open for manufacturers to run wild with.

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jharrom t1_j8vot12 wrote

Low gravity and an almost complete vacuum are both huge challenges. Traditional construction of almost all structures on earth are engineered by necessity to compensate, use, and account for much stronger gravity. Add high-pressure liquefied gasses, huge temperature swings unlike anything on Earth, and the additional radiation. You not only have to build and run such a structure under those conditions, you have to use a ridiculous amount of safety precautions and redundant systems to guarantee the system won't fail catastrophically.

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gurenkagurenda t1_j8voslg wrote

Log probabilities are the actual output of the model (although what those probabilities directly mean once you're using reinforcement learning seems sort of nebulous), and I wonder if uncertainty about actual facts is reflected in lower probabilities in the top scoring tokens. If so, you could imagine encoding the scores in the actual output (ultimately hidden from the user), so that the model can keep track of its past uncertainty. You could imagine that with training, it might be able to interpret what those low scoring tokens imply, from "I'm not sure I'm using this word correctly" to "this one piece might be mistaken" to "this one piece might be wrong, and if so, everything after it is wrong".

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gurenkagurenda t1_j8vnlyo wrote

I think you must be getting confused because of the "reward predictor". The reward predictor is a separate model which is used in training to reduce the amount of human effort needed to train the main model. Think of it as an amplifier for human feedback. Prediction is not what the model being trained does.

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gurenkagurenda t1_j8vnao5 wrote

>so... predictive

No, not in any but the absolute broadest sense of that word, which would apply to any model which outputs text. In particular, it is not "search out the most common next word", because "most common" is not the criterion it is being trained on. Satisfying the reward model is not a matter of matching a corpus. Read the article I linked.

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SylvesterStapwn t1_j8vlrwz wrote

I had a complex data set for which I wasn’t sure what the best chart for demonstrating it would be. I gave chatgpt the broadstrokes of the type of data I had, and the story I was trying to tell, and it gave me the perfect chart, a breakdown of what data goes where, and an explanation of why it was the superior choice. Couldn’t have asked for a better assist.

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SalaciousCoffee t1_j8vlo96 wrote

The government serves those that pay for it's service.

That's it.

You join government through an election, the election is one of the costs to do business with government.

Folks pool their money and get fractional interest in pokiticians, but they spread it across all of them so they will lean one way or another.

No money? No power.

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