opus55_lover

in what sense. the black hole is a result of the interaction of light with the curavture of space time. this is not modelled by newtonian gravity (or physics for that matter) at all. light is assumed to not interact with gravity in that framework in any way.

the market for their valuation is just not there imo. they need to significantly expand into non-coding products and outshine their coding offerings to make it work.

as in, if they capture every single professional software dev and extract $1000 from them every month, their yearly revenue will be like $500B. do your own back of the envelope on that with ongoing costs and consider how unrealistic a goal this actually is.

even worse, the very product they offer is self limiting. if it becomes so good as to actually replace software devs, they will have less customers to extract money from.

their valuation essentially relies on a small percentage of mega users having unheard of levels of spending.

the part about a small percentage giving them most of their money is already true (their rumored $100+ bil revenue as of mid 2026 already outshines all software devs having a $100 max subscription), but they are two orders of magnitude or so away in terms of the actual amounts to make it work.

I don't know what this logical fallacy is called, but it quite clearly is one.

It's true that you have to content with these things. But you also have to content with them when testing human created treatments. The system is already set up at a basic level to minimize the impact of exploitation and misaligned humans.

What this really comes down to is how more effective a super misaligned AI could be at exploiting the system. But the solution is not to prevent the AI from participating in it, but rather to make the system better.

besides that, he's also engaging in the logical fallacy of using the human as a more trustworthy replacement of the AI, when the verification of human understanding has the same fundamental problems you would have when verifying AI output and understanding.

i.e. there need to be some meta processes that don't rely on human understanding at all.

in medicine the whole pipeline is optimized exactly for this for short and medium term effects. for long term effects, there honestly isn't a pipeline, and the general mechanical understanding of treatments potential long term effects is surprisingly poor / uncertain when you look into it. and in this case, AI would almost certainly just improve the process.