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“We were in the jungle. There were too many of us. We had access to too much money, too much equipment, and little by little, we went insane.”
replace equipment with information and this quote perfectly describes the information age
We’ve measured the linguistic extremism of political media over Presidential campaigns since 2012. However bad you think it’s going … you’re not even close.
The language of political extremism isn’t new in America. The scale and persistence is.
epsilontheory.com/apocalypse…
epochso retweeted
Is AI investment crowding out the rest of the real economy by very much? marginalrevolution.com/margi…, from @ATabarrok
epochso retweeted
Mike Evans Checking to see the name on the back of the Jersey is an all-time Gif and trash talk moment that I wish I would have thought of.
The loop for a foundation model co is now:
Best model → demand shock → capacity constraint → ration via price → fund capacity → competitors absorb demand/share → capacity catches up → cut price → regain volume → next best model
epochso retweeted
Really nice report. Follow up: why has the fall in AI prices been so fast?
When you plot the price decline against cumulative R&D investment rather than time, you get the elasticity of price declines to R&D investment. By this margin, AI is not unusual – its price elasticity to R&D investment is squarely in the middle of Epoch's considered technologies.
So the AI price fall is historically unprecedented because we've dumped money into AI R&D at a historically unprecedented rate – and that R&D has paid off at a very average rate.
epochso retweeted
Artists: but I don't want to lose my job. I love it.
Mathematicians: but I don't want to lose my job. I love it.
Economists: LONG HAVE I AWAITED THIS HOUR! DESTROY ME, EFFICIENCY, AND LET UTILIZATION-ADJUSTED TOTAL FACTOR PRODUCTIVITY RISE ON THE WIND OF MY ASHES!
epochso retweeted
In light of the progress in mathematics, we at Edison Scientific and FutureHouse have assembled a set of Millennium Problems for Biology. They are chosen to be very hard to solve but very easy to validate in a simple laboratory environment. Any of these, if solved, would mark a major advance in biotechnology, and most of them would contribute materially towards curing disease. These are, in some sense, the “last reasonable eval” for AI in biology. This was work primarily by @MichaelaThinks and myself, with contributions from many others.
Short descriptions below. The full descriptions of the problems with acceptance criteria are at the Bio Millennium Problems website, linked in the next post. Share more if you have ideas. If they meet our criteria, we’ll add them to our list (with attribution and permission).
AWS: a million APIs
Oracle: a million people
GCP: a million deprecated products
Neoclouds: a million waitlist entries for non existent clusters
epochso retweeted
Richard White (Railroaded) on what continues to amaze historians: The ability to wipe out the memory of American investors, it's like they get a lobotomy every five or six years. theringer.com/podcasts/plain…
epochso retweeted
By reducing the time people spend shopping, managing inventory, and building infrastructure, Amazon has created consumer surplus that far exceeds Bezos’s personal fortune.
humanprogress.org/jeff-bezos…
epochso retweeted
holy shit, its actually happening
epochso retweeted
this guy fucking called this months ago.
openai asked researchers to come use their models and do research with them.
now, a few months later:
math researchers getting fucking scooped by the lab they trusted with their work.
what a fucking precedent.
epochso retweeted
>sam altman: "we tried this because there were rumor on the internet"
>rumor: math professor close to solving navier-stokes
>the professor: using codex for a year
>openai: has all his logs
>checked every codex session tagged to N-S
>found the most promising one
>spun up 10,000 agents to finish the proof where he couldn't
>they got caught
>told the guy if you say anything you'll destroy your own career
>he ruins his career over this
>openai: "we did not see his work"
>also openai: "we cannot rule out that de-identified data from their usage helped improve our models"
they stole it lmao
