George Yancopoulos has a reputation for being unconventional (or perhaps outlandish to some). I would suggest that before he is taken seriously, Regeneron should publish a weight loss whitepaper explaining his position. At face value, it makes no sense to suggest that GLP-1 have some latent issues that goes beyond normal muscle loss as per the normal behavior for any weight loss.
Strength exercise are the normal suggestion to preserve muscle mass, and I don't believe there is any research showing this would not be effective with GLP-1 drugs.
An unconventional approach would be to take a GLP1 drug and ephedrine, which has been shown in many studies over 40 years to preserve muscle mass during calorie restriction. However, the drug is dirt cheap, not patentable for this common use, and therefore not of interest to any pharma company.
A recent meta analysis of ephedrine is here: https://www.mdpi.com/1424-8247/14/11/1198
Has anyone found the source for that 20%? Here's a paper I found:
> Between 1848 and 1854, railroad investment, in these and in preceding years, contributed to 4.31% of GDP. Overall, the 1850s are the period in which railroad investment had the most substantial contribution to economic conditions, 2.93% of GDP, relative to 2.51% during the 1840s and 2.49% during the 1830s, driven by the much larger investment volumes during the period.
https://economics.wm.edu/wp/cwm_wp153.pdf
The first sentence isn't clear to me. Is 4.31 > 2.93 because the average was higher from 1848-1854 than from 1850-1859, or because the "preceding years" part means they lumped earlier investment into the former range so it's not actually an average? Regardless, we're nowhere near 20%.
I'm wondering if the claim was actually something like "total investment over x years was 20% of GDP for one year". For example, a paper about the UK says:
> At that time, £170 million was close to 20% of GDP, and most of it was spent in about four years.
https://www-users.cse.umn.edu/~odlyzko/doc/mania18.pdf
That would be more believable, but the comparison with AI spending in a single year would not be meaningful.