@melon_thiefi
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Joined August 2022
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Replying to @Muse
@Muse got me a $200 gift card from Verizon which I had forgotten to claim when I signed up for the service. So it just paid for itself for the next year or two.
@alexandr_wang
If you download Muse, redeem my code in Settings within 48 hours of joining and we'll both get 1 billion Muse tokens.
Code: AML0FH
muse.ai/join
.@stevesi explains why words like "goal-seeking," "cheating," and "secretly coordinating" mean one thing to AI researchers and something terrifying to policymakers:
"There's a long history in all fields of academic research to basically be too cutesy about things, 'cause that's how you get attention in academia. So it's no surprise that something that had its roots in academia carried forth all of this terminology. But it's just time to stop."
"It's goal-seeking in this old-school technical sense. There's a curve, and it's trying to get to the min or to the max. But when a normal person like a congressman hears goal-seeking, they think of a person trying to get an A in college."
"When they hear cheating, they hear that they did the thing you're not allowed to do. And when they hear secretly coordinating, they think of spies invading the country. They don't think of two pieces of software with a semaphore."
"All the language is absolutely destroying this dialogue."
@a16z
“Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens”
In one sentence mark disarms Dario
Last month I wrote about how we can build a positive and safe future for everyone: meta.com/thefutureisforevery…
Every lab has the responsibility and incentive to move at the pace required to train its models safely, and the ability to take its own actions to ensure that happens.
The reality is:
- People won't want to use agents that are misaligned with them and that don't do what they ask, so labs have a strong natural incentive to make their models more aligned.
There is a lot of debate about slowing progress on capabilities until alignment catches up. My view is that trust and alignment are quickly becoming the most important capabilities that will differentiate agents and models. Any lab that doesn't focus on alignment will fall behind.
- Labs face significant liability if their models cause harm, so they have a strong incentive to prevent this as well.
Meta delayed shipping Muse for several months to focus on safety and security. We didn't call for everyone else to do this before we would. We just did it as part of our day-to-day work because it was clearly the right thing for people and for us. I'm proud of the security foundations we've built.
- Engaging independent evaluators and advisors is industry best practice. MSL already does this today in several areas because it helps produce better work. Other labs can just do this too. In general, it would be helpful for there to be a larger and more diverse ecosystem of evaluators.
- Committing the significant majority of compute towards serving people rather than racing towards recursive self-improvement is one of the best ways to ensure we develop this technology safely. Meta has made this commitment and other labs can do this as well.
I believe the key to building a positive future for everyone is maintaining the right balance of power. This is within our power to do.
I think the main issue with a lot of OAI and Anthropic employees is they consider themselves moral people who have become unbelievably wealthy in a way many cant fully comprehend. To straighten out the cognitive dissonance they need to believe their product may end the world save for their stewardship and ONLY their stewardship.
This validates the wealth they have gained.
“it is the victory of the compute bulldozer over abstract human intuition repackaged for the public as a higher mathematical consciousness”
go fuck yourself @sama
claiming that you solved navier stokes because 10000 agents ran in circles for 88hours on a multimillion dollar gpu cluster to formalize in lean a blowup case under controlled external forcing is pure scientific vulgarity the clay mathematics institute millennium prize does not ask m whether you can artificially force a singularity in a fluid by injecting an ad hoc smooth external forcing term f(x,t) to twist the vortex until it breaks the real problem questions the fundamental stability and global smooth existence for 3dimensional incompressible euler & navier stokes equations under natural conservation laws and viscous dissipation alone using a mathematical loophole on forced equations to parade a century old victory is a major conceptual scam Altman
technically & epistemologically what you present as an agi breakthrough is nothing more than bruteforce combinatorial autoformalization the ai did not understand fluid mechanics it simply navigated a continuous search space previously mapped out and constrained by the monumental work of human mathematicians like tristan buckmaster/ levent alpöge / diego córdoba or tarek elgindi coordinating 10000 agents to check the logical consistency of a 100 page proof via lean is a software engineering feat and computational parallelization triumph not an intrinsic scientific discovery it is the victory of the compute bulldozer over abstract human intuition repackaged for the public as a higher mathematical consciousness
to this theoretical imposture you add a disgusting ethical and industrial cynicism taking advantage of private codex sessions and informal preprints from academic researchers to siphon their research leads and then trying to redact or erase the contribution of levent alpöge under the pretext that he works at rival anthropic is intellectual serfdom openai behaves like a feudal lord of silicon appropriating the cognitive subsistence of independent scholars threatening their careers behind closed doors if they protest and turning community academic labor into a privatized pressrelease
this entire staged event serves a desperate financial agenda in a pre ipo panic facing the slowdown of scaling laws and growing investor skepticism over the profitability of foundational models openai needs to manufacture an artificial sputnik moment claiming to solve a millennium prize without immediately submitting the proof to traditional peer review means using the prestige of fundamental mathematics as cheap marketing fuel to inflate a delusional valuation!!!
real science is not a clout chase on social media or a compute spike spent to rob the clay mathematics institute it is a quest for elegance physical truth and universal rigor to decode reality true artificial intelligence will not emerge from hostile corporate takeover of academic work hidden behind computational bruteforce but from architectures capable of generating new conceptual paradigms by masquerading constrained formalization as the collapse of physics greatest mysteries you did not solve navier stokes you only proved how far silicon valley will go to prostitute scientific integrity for capitalist spectacle
Tristan probably did not turn off “improve the model for everyone”, and was likely not protected by an Enterprise use agreement. (NYU doesn’t have an enterprise agreement for ChatGPT/Codex.)
He spent a year uploading drafts on his problem to OpenAI.
Autonomous data pipelines saw value in his chat and stored for training / synthetic data.
OpenAIs new unreleased model likely got stronger on Math through his data, and countless other mathematicians working on similar problems.
We need a solution to attribute/cite user data to model weights and create a shared payments system
Basically what @AndrewYang was talking about in 2020
YANGGANG2020
I got into a fight with my Grok @bot chief of staff. What do I do now?
No one wants to go to intelligence, they want things to be intelligent.
OpenAI and Anthropic own centers of intelligence, but not the profusion of it.
Meta is in the position to make your daily life full of intelligence.
Huh it’s almost like the data guy knows a thing or two about training LLMs
@alexandr_wang
$meta