antimatter15

No

Another fun calculation is that due to special relativity, a hard drive that is spinning gains a certain amount of mass due to the rotational kinetic energy and E=mc^2.

Assuming the platter is 100g, 42mm, spinning at 7200RPM, there is about 25J of rotational kinetic energy, whose mass equivalent is 2.8x10^-13g (0.28 femtograms).

Assuming 200 electrons per NAND floating gate with 3bits/cell TLC on a 2TB SSD, there would be 5.3x10^14 electrons, weighing about 0.5 femtograms.

Note that this doesn't represent a general break of RSA-2048, and doesn't affect the security of RSA-2048 as it's used anywhere.

The paper only applies to "special integers" where the prime factors are known to only differ by two bits.

It's hardly even illicit- at least in the United States, the output of an AI isn't copyrightable.

Figure 3 on p.40 of the paper seems to show that their LLM based model does not statistically significantly outperform a 3 layer neural network using 59 variables from 1989.

  This figure compares the prediction performance of GPT and quantitative models based on machine learning. Stepwise Logistic follows Ou and Penman (1989)’s structure with their 59 financial predictors. ANN is a three-layer artificial neural network model using the same set of variables as in Ou and Penman (1989). GPT (with CoT) provides the model with financial statement information and detailed chain-of-thought prompts. We report average accuracy (the percentage of correct predictions out of total predictions) for each method (left) and F1 score (right). We obtain bootstrapped standard errors by randomly sampling 1,000 observations 1,000 times and include 95% confidence intervals.