Amphetamine is primarily absorbed through the plasma membranes and not DAT since it’s lipid soluble.
Dopamine does not and thus relies on DAT. By inhibiting DAT (as both amphetamine and Modafinil do), you increase extracellular dopamine.
Next, DAT does not “transport amphetamine around the brain”. It only transports it from the post synaptic cleft into the cell.
Also Modafinil is a much weaker DAT inhibitor than amphetamine itself as far as we know.
Lastly, drugs don’t “antagonize” other drugs. That word is a specific term used for the action on the receptor level.
The dopaminergic effects of Modafinil aren’t well known and are thought to be mild. It’s simply misinformation to claim that modafinil was somehow blocking the effects of amphetamine on the dopamine receptors.
You get the same result in a short span of time, heck you may even get a reliable error bound.
Where this falls apart is that error accumulates over time and not just for one heap of sand but for many such heaps of sand that also interact with other heaps of sand.
Predicting weather for the next hour is trivial. Aviation runs on the fact that you can forecast fairly accurately into the next hour most of the time.
The difficulty scales superlinearly over time due to the error accumulation over predictions
I find your statement about the Edison quote disingenuous. I did some reading about the origin of the quote and it isn’t as cut and dry as you seem to claim.
Also, the quote is meaningful because Edison said it, not because the quote has merit in and of itself.
It’s inspiring because someone of Edison’s acclaim attributed his success to hard work. Anyone else could have said it and it wouldn’t have been a meaningful quote because they weren’t as successful as him.
Note that my statement doesn’t presuppose that he was successful solely due to his own efforts or that he isn’t a fraud etc. But rather that the significance of the quote relies on his perception as being successful in the public eye.
Until you get models with completely disentangled feature spaces such that you know that the influence of a piece of data is completely removed (at the limit this is something like an embedding DB), there is absolutely no way you can claim you’ve removed the data from the model.
At most, these efforts will amount to data laundering where it will be impossible to prove that a piece of data was used to train the model, not provide conclusive proof that it was removed.
No, actually they probably can’t. There is no verifiable way to remove the data from the model apart from completely removing all instances of information from the training data. The project you linked only describes a selective finetuning approach.
If you recite enough small snippets, you make a large one.
Especially with ChatGPT you can probe the model by asking certain questions about the material at hand to see if it has seen the entire book.
Also you don’t have to be able to recite the book verbatim for it to have been in your training set. The snippets I am referring to are on the side of the training data
Libgen / Scihub or not, if the model can provide details about the book other than just high level info like the summary and no explicit deal with the publisher has been made, you can make a strong argument that it is plagiarism.
Even if bits and pieces of the book text are distributed across the internet and you end up picking up portions of the book, you still read the book.
It is extremely sad but ChatGPT will be taken down by the end of this year and replaced by a highly neutered model next year.