people will go to _amazing_ lengths not to read something new or unfamiliar. That feeling of "i must be dumb" is most often the reason people avoid it, and is just the normal part of learning something new.

When someone dismisses your interpretation it serves to understand it well.

Additionally: A contractual mistake would likely not return specific performance (stock) unless special conditions were met.

For example: a company makes a stock mistake, you observe that at the time it happens, but then do nothing until you see the stock increase in value. Company could assert you _were_ due the stock but the value of that stock is determined by the time-of-breach and they return you $.

Unless you had a substantial claim to voting interest would probably be monetary reward!

NYL

Geopolitical and other risks exist here. The future isnt doom and gloom but it isnt exponentials and sunshine either.

Companies like Nvidia, up 1000% since 2023, clearly cannot rely on "oh you'd get returns in 5-15 years". They (Jensen and others) are arguing for AGI in a year (he said this at a talk at Stanford ~ 1yr ago).

Long-term, ie 5-15 years there will be many technologies that change the world. Some will come from transformative tech, others will come from other places.

Financial instruments, investors etc have timelines.

Blowing timelines can risk the future if not properly aligned, especially in correlated risk. See the internet bubble, where it was clearly important but took 15 years to recover after the 2000 boom/bust.

In general, longevity risk can include the financial instrument timelines, it can include other technical factors about the technology, and it can also be that the boom serves important people too soon with gains, real limits are imposed, and then the whole system resets until the real limits are overcome or resolved.

"we could find a nail for this hammer... or we could just hammer everything until we find the nail or make too much money hammering for a bit then sell in may and go away".

Very few things in life experience exponential growth and assembled systems don't often stay that way if they don't become sigmoidal. ie its exponential and end is nigh xor its exponential then sigmoidal xor linear.

Also a bit hilarious to believe that a single 3 month cycle at TSMC could determine a severe amount of propped valutions.

[1] https://www.theverge.com/tech/943066/tsmc-ai-demand-struggle...

Here is my developed protocol:

1. Oral Zyrtec or Claratin, switch which one is taken every 6 wks to avoid building a resistance to the specific antihistimine!

2. Saline nasal rinse (bottled from store or from home-boiled water and salt)

3. Corticosteroid nasal spray. Applied so that it is not shot directly up nose, pointed away from the bridge of the nose. Allow 5-10min for it to absorb, do not blow nose just after.

4. Mineral sunscreen, for moisturizing/uv protection and also it helps to keep pollen out of the eyes.

https://www.iqair.com/as/pollen/usa/california/berkeley

Comments URL: https://news.ycombinator.com/item?id=48358758

Points: 3

# Comments: 0

These tools do need attention, it's too bad there's not a better model than subscription bases like these.

Pretty sure, based on TCL base, that these tools were native Unix at some point, so the no-linux-free-beer vs windows-free-beer version are hilarious...

Ultimately one has, with so many vendor tools, a windows box somewhere so make it a remote compile machine.

[1]https://www.padilla.senate.gov/newsroom/press-releases/padil...

Removing seems hard/complicated but foil seems within most ppls reach.

also if you want to test/force ai adoption you have to put pressure by firing some

now wars will put us into further stasis or decline via increased inflation pressure.

Arbitration idea: if a user doesn't need high QOS of newest LLM, slip them a cheaper LLM, run their query at reduced quality. measure if they cost you fewer $s in the lower QOS. => profit.

For chatgpt the arbitration opportunity looks more like "we could allocate this amount of gpu to training or inference, we are losing money if we offer the highest quality infra"

In addition there's other interesting economics scaling that can be done outside of "models of models" that are far more profitable. I won't go over all of them (and some of them I feel are quite powerful) but the laziest one is that subscription models count on some zombie users as a counterweight to highly expensive single users, and as a source of stable cashflow.

Zombie users are ones that are paying for sub but not actively or barely using the service

Insurers are also adding some %+ increase on premiums every year, which is taken as a % of their yearly spend, ie 2-3%.

ie (1+inflation)^N*(base_prem+overpay_prem_increase) = new_premium. The compounding of $ returned is pretty big on this.

That being said underwriting risk, under the law and avoiding correlated risks, is tough.

They will just have to recompete!