Or am I missing something?
Typically running something like git would be an opt in permission.
It’s all fun and games until the bean counters start asking for evidence of return on investment. GenAI folks better buckle up. Bumps ahead. The smart folks are already quietly preparing for a shift to ride the next hype wave up while others ride this train to the trough’s bottom.
Cue a bunch of increasingly desperate puff PR trying to show this stuff returns value.
Is he wrong?
Despite posturing by some academic administrators, most folks have no social agenda for a country they recently immigrated to.
So ideally the ml network would solve the problem end to end but these authors seem to be using a network for only one step of their otherwise classic image processing pipeline
With crypto, the VCs can sell the majority of their tokens after brief lockup period, capitalizing on purely narrative-driven speculative valuations that almost always disconnect from the actual reality, let alone fundamentals.
Crypto VC perfectly embodies the Greater Fool Theory. The VCs profit by selling to later buyers motivated more by speculative momentum than intrinsic value. The joke being that VC involvement in a project is often the only thing even driving that momentum.
This combination of compressed liquidity timelines, minimal regulatory oversight, and a glut of retail investors who have FOMO from seeing their friends 100x or even 1000x, creates an ideal environment for VCs to systematically transfer risk to less sophisticated market participants at often insane valuations.
Term sheets from vcs increasingly include a “don’t do an ico”
i am not on trump's side (i hate trump; i am neutral on musk except these past few weeks i think he's said -- but not yet really done -- things that are a bit beyond the pale, even for him) but i think this will be positive for American science.
as i posted in sibling comment:
> to steelman the issue: what if there was overinvestment in science? as in we chased money after talent that didnt exist, or was mismatched to the difficulty of the available and fundable open questions.
two things: you'd expect a lot of fraud and misallocated science to have been recently uncovered (Reproducibility crisis, amyloid hypothesis scandals e.g.).
after the cuts, you would expect the quantity of science to go down, but the quality to go up.
i guess technically this isn't a logocal explanation since i dont think trump is doing this in good faith but i think the US might be better off in the end.
In the immediate it seems to have cut short the next generation of scientists leaving more of the entrenched old hands.