@BodenHagan
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frogs are pretty cool.
Madison, WI.
Joined April 2009
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We haven’t correctly defined it, my definition covers all aspects, it is a complete definition and does…..
Frog Enjoyer retweeted
Circus Performers, by Walt Kuhn, 1978, 📸 via @marisakabas2
AOC: And for anyone who says that’s unrealistic… this is literally what baby boomers gave themselves. Public colleges in America were tuition-free. You know when they started to get defunded? They got defunded when they started to get integrated.
This is cartoonishly criminal behavior. Man in a mask tiptoeing into the bank and out with a bag of cash with a dollar sign on it levels of cartoonish.
BREAKING: Trump collected $13 billion dollars from Venezuela and now the government can't find the money.
Fairlife has done incredible work here.
Fairlife chocolate protein shake has one main ingredient. Filtered lowfat milk. Every other item on the list is under 1%.
The 26 grams of protein in the bottle comes from filtered milk, not from anything added. Regular lowfat milk is about 8 grams of protein a cup, so 14 ounces would give you around 14 grams. Ultrafiltration pushes the milk through membranes that hold the protein back and let the water and most of the lactose through, then the plant recombines it with more of the protein fraction. That's how you get to 26 with nothing on the list but milk.
The under 1% group is the taste and the texture. Four sweeteners, monk fruit, stevia, acesulfame potassium and sucralose. Each has its own aftertaste, and stacking them at low levels lets each one cover for the others. Then carrageenan, cellulose gel and cellulose gum, three thickeners that keep the cocoa from settling and give the shake some body.
It's about as clean as a protein shake gets.
Every tech VC wants to believe that drug discovery is now a function of compute. They think if we throw enough H100s at the problem, tokenize enough dead sequences, and scale virtual cells, biology will be 'solved'.
They are wrong.
Drug discovery is not a function of compute. It is a function of measurement.
Incredibly cool to see what comes out if this.
We built high-throughput materials labs in Menlo Park to create a loop between experiments and models. The labs generate fresh data, the models learn from it, and then help us decide what to try next.
Using only 1,300 H200s, plus months of our experimental data, we mid-trained and RL’d an open-source model to surpass GPT-6 Astra on our analysis benchmark. We call it Neon.
This is real footage from our lab. We’re focusing first on hard problems in materials science, including superconductors, magnets, and semiconductor materials.
Read our blog posts below.
Frog Enjoyer retweeted
Every once in a while I remember this business in Chicago that hung up a Trump 2024 sign facing the highway that reading "I MISS GAS @ $1.79/GAL & MEAN TWEETS."
The sign is still there because the company went out of business.
Frog Enjoyer retweeted
I was encouraged this week to see the leaders of the frontier labs agree on the need for them to slow down the pace of AI development. Given the stakes, it’s a good and necessary first step.
But I’m even more encouraged by the growing recognition that how this powerful new technology develops should be at the center of our public debate.
I’ve been watching the progress on AI for over a decade now, and one thing that’s clear to me is that the potential impact of this technology is not overhyped. It’s also moving at lightning speed – and even faster than those who are engineering it can keep up with.
I’m not an AI accelerationist who believes it will lead to some techno-utopia, and I’m not a doomer who thinks it will inevitably lead to humanity’s destruction.
But whether this technology results in amazing breakthroughs in medicine, energy and education or unleashes huge economic disruptions, greater inequality, and potential catastrophe will depend on the choices that we make right now – choices that should be made not just by the companies involved, but by all of us.
Frog Enjoyer retweeted
it is still so cool to me how humans created language and spent centuries describing our world to each other well enough that we could compress the accumulated words into ghosts who have a reasonably accurate model of the physical world as perceived by human brains
Frog Enjoyer retweeted
tristan buckmaster just published a statement that is, if accurate, one of the ugliest things i’ve read out of a frontier lab.
not because of the math. because of what happened after openai found out two people were about to beat them to the punch.
buckmaster and levent alpöge spent a year pushing the córdoba / martínez-zoroa program to smooth forcing. august 15 they got blowup for boussinesq and 3d euler. lean-verified august 22.
they were paying openai out of pocket and dumping every draft into private codex sessions.
the program is obscure. almost nobody else was on it. this was not “paste the clay problem into a chatbot.”
then this:
> thursday sept 3, buckmaster emails openai privately. rumors are flying. he is trying to stop a mess, not start one.
> they reply the same day: give us details so we can “avoid competing.” also, want free compute?
> sunday they suddenly need a call “at any point today.” sebastien bubeck gets on. levent is not invited.
> openai says an internal model has a ~100-page proof of forced navier–stokes blowup. fefferman options c and d. the exact route buckmaster and alpöge had quietly chosen.
> they show him a prompt and claim the model was “simply given the problem statement.” levent is told “very little human input.”
> that falls apart on the same call. a whole team had been on it. they started on the unforced problem, warmed the model up on easier equations including euler, and even the prompt they showed him was written by prompting codex.
> he asks when the first prompt went out. they stall. then agree: the past few days. after information about his work reached openai.
> he asks whether the model was trained on, or had access to, the private codex sessions where they put every draft of this project.
> answer: the model does not look up user data.
> he asks again. about training.
> no answer.
then it stops being a science story and becomes an hr story.
> offer 1: you post euler. we post navier–stokes the next day.
> offer 2: after you post euler, you alone write the navier–stokes paper, credit our model, and we cut levent.
> bubeck says twice he wants levent removed from authorship because he works at anthropic.
he declines both.
he says if they release it that way, he goes public.
the reply is not a scientific objection.
> “why would you ruin your career?”
> “if you don’t want me to be nice, then i don’t have to be nice.”
later, a text to levent proposing a one-on-one:
> “i don’t know if tristan is being fully rational right now.”
that is not how you treat a collaborator. that is how you split one.
openai got word two researchers were closing a path almost nobody else was on. they spun up a team on that exact path. they would not answer whether the researchers’ unpublished drafts in openai’s product were used. they tried to dictate the announcement order. they tried to remove a coauthor because he works at a competitor.
when that failed, someone reached for a career threat.
this is a lab finding out academics were about to publish, sprinting the same narrow program, refusing the data question, and trying to manage credit around a rival affiliation.
really slimy if even half of this holds.
what the fuck is happening.
holy shit.
tristan buckmaster is saying openai has a forced navier–stokes blowup via the córdoba / martínez-zoroa program.
and that it may have used drafts from his and levent alpöge’s private codex sessions.
that’s the córdoba / martínez-zoroa route. almost nobody else was on it.
he also says the first prompt went out after information about his and levent alpöge’s work reached openai. that “very little human input” was not true. that a whole team had already been set on easier problems, including euler. that even the prompt they showed him was written by prompting codex.
then he asked:
did the model have their private codex sessions.
no answer on training.
if any of that holds, openai didn’t just scoop a math result. they may have done it off two researchers’ unpublished drafts, then tried to cut the coauthor because he works at anthropic.
a millennium-problem-adjacent result just became employee drama before an ipo.
i don’t even know which part is crazier.
this is one of the slimiest things i’ve seen in this industry.
