“...condensed matter physicists study nonliving matter, and biological physicists study living matter...you will have a hard time convincing me that you and I and other living creatures are not the most interesting matter in the universe.” - Rob Phillips
https://t.co/kPU3Jue2WQ
(16:00) We are at the point that administrations cannot be trusted to fulfill their statutory obligations to be transparent. It's happened with COVID origins, and it happened again with the Epstein files.
https://t.co/iyypTZARQX
Almost more disappointing than the plagiarism itself is how much the identity of the accused and the accuser, and whose team you're on, seem to matter more than the evidence.
"Justice is blind" might be a modern innovation for stubbornly tribal homo sapiens.
If Dan McClellan was being accused of being a serial plagiarist, and much evidence suggested he did, we know for a fact the Wes-defenders would be all over it!
My favorite is on page 9. Thatcher wrote in 1999 that critics had challenged Grant and Brown “in the last three decades,” which was true then. When Huff copied Thatcher twenty years later, he kept “the last thirty years,” so his timeline is off by two decades.
More evidence of data fraud from Francesca Gino. This is at least five cases of fraud she committed (and she is being sued for another in court as we speak).
I would not personally trust anything she published unless another author handled the data and can independently verify the findings (same goes for Dan Ariely's research at this point).
Thanks to @AdamMGrant and David Hofmann for helping expose this one and issuing an expression of concern for their paper. We need more coauthors coming forward and working to correct the scientific record.
Enabled by a weird scheduling quirk, the NFC North feasted on the NFC South before they could even beat up on each other.
Now? All four NFC North teams are currently sitting in playoff spots, holding down all three wild cards. Absolute chaos. 🏈📈
There was even a movie about a scholar using his textual criticism powers in the real world.
It won Best Screenplay at the Cannes Film Festival.
https://t.co/fo7R9rYNMQ
"Editorial fatigue" is a real phenomenon in Biblical studies, in which one scribe makes a mistake when copying long passages of existing text.
So don't be surprised when it gets caught by the exact people most prepared to find it 😅
In one place Huff misread the blog while rewording it. Rodríguez says Thomas "weaves in redacted sayings from the synoptics among his new, non-synoptic sayings." Huff writes that Thomas "wearies in redactional sayings from the synoptics among the non-synoptic sayings."
today we released our smallest model yet: Muse Ember 🔥
Muse Ember offers nearly Muse Spark 1.3 (max) intelligence at a 17x cheaper price point (per AA)
Muse Ember is the first model we’ve released trained using Muse Wonder Full
excited for y’all to try on API and muse code!
There's one great example that shows how physics can help upgrade AI world models, and it's LeHami.
@ylecun, @randall_balestr and @RominaYalov brought Hamiltonian mechanics into JEPA to preserve phase-space volume and prevent latent collapse during long-term predictions.
Why exactly Hamiltonian mechanics?
• Variables are coordinates q and momenta p (not velocities like in Lagrangian mechanics), giving LeHami paired first-order equations for updating its states.
• This makes Hamiltonian H a central function. It's often total energy: kinetic + potential, in classical mechanics.
• LeHami learns this H function with kinetic-like K(p) and potential-like V(q, u) components, where u represents actions.
• A symplectic leapfrog integrator uses this function to predict how states evolve depending on the actions taken, while no constrains are violated.
To understand this better it's useful to think of a pendulum. It can pass the same position in either direction. But physical position alone won’t predict what comes next, you also need momentum.
LeHami follows a similar principle, but works with learned representations of position and momentum.
→ And most importantly, it builds a constraint into how those predictions evolve.
Maybe that's exactly the kind of thing world models like JEPA need now - one less way to go wrong.
We've taken a much deeper look at LeHami's design and results in this guide. Plus, there's a little mechanics lesson for AI and physical AI folks that's worth learning → https://t.co/F157rzIgZh
MAGA: 'We hate Trump now because he didn't do fascism hard enough, and he conned us about inflation and not starting new wars. Dumb liberals have always hated Trump because he is a vulgar game-show host manifestly unfit for office. We are not the same'
https://t.co/nmCDQTd0eQ