Curtis @curtinity

@aramh Agree. There’s an analogous version with abstract algebra. Learning that + and * are operators in a group makes negative numbers and fractions easier imho. Should be taught first.

0 0 1 116 0

View Details

Curtis @curtinity

2 days ago

@huskirl Tryna figure out why this is funny. Something about the intonations it takes.

0 0 1 94 0

View Details

Curtis @curtinity

2 days ago

@VictorTaelin congrats!

0 0 0 166 0

View Details

Curtis @curtinity

2 days ago

@LFFStadium @Shanemgillis Stfu nice

0 0 0 24 0

View Details

Curtis @curtinity

3 days ago

@netcapgirl lmao

0 0 1 52 0

View Details

Curtis @curtinity

3 days ago

@NickADobos @signulll 1000%

0 0 0 25 0

View Details

most doctor visits are almost completely useless endeavors now cuz they’re also just googling shit. chatgpt & claude are 1000x better in every dimension if you are even remotely able to problem solve in any meaningful way. before someone comes after me, i am only talking about front line doctors. e.g. your primary care physician should be an ai for the majority of individuals, there is not even a question about this anymore. the only real thing keeping these guys in business is pure regulatory.

214 91 2K 321K 374

View Details

Bojan Tunguz @tunguz

4 days ago

Now, here, you see, in the current AI phase, it takes all the running you can do, to keep in the same place. If you want to get ahead, you must run at least twice as fast.

7 6 71 4K 6

View Details

Curtis @curtinity

4 days ago

@DeryaTR_ Incredible future ahead

0 0 1 44 0

View Details

Curtis @curtinity

5 days ago

@JessicaSacher @FedEx @FedExHelp @StanfordMed Yikes way to take action

0 0 1 139 0

View Details

Jason Locasale @LocasaleLab

6 days ago

One reason biology is not taken seriously by people trained in quantitative or physics-based science and engineering disciplines is that it often relies on loose or squishy metaphors and analogies to sell the importance of the work. The field substitutes loose metaphors, ambiguous biomarkers, and cartoons for quantitative precision, then wonders why people trained in quantitative or physics-based science and engineering disciplines regard it as a soft science. Terms such as “metabolic demand” and “T cell exhaustion” are stated emphatically in titles and abstracts and presented as cartoons in slide decks, but they are never rigorously measured or even defined. In economics and physics-based disciplines, where mass and momentum conservation are real principles, demand has a precise quantitative meaning: the total consumption, withdrawal, or output from a defined system or network. In biology papers, “metabolic demand” is usually meaningless. “Cell exhaustion” has a related problem. It is inferred from biomarkers or loosely measured functional outputs, or phenotypes, that are either far removed from the actual process, may not be rigorously correlated with it, or can have multiple ambiguous interpretations and meanings. This contributes directly to the reproducibility problem. Many biological claims are difficult to generalize because the central quantities and processes were never rigorously defined or measured in the first place.

Immunity @ImmunityCP

a week ago

Online now: MEK-dependent bioenergetic demand drives terminal CD8+ T cell exhaustion dlvr.it/TTWYRh

0 2 17 21K 5

29 9 127 20K 50

View Details

Curtis @curtinity

6 days ago

So it begins

Zhengyao Jiang @zhengyaojiang

6 days ago

The first experimental evidence of recursive self-improvement (RSI). Autoresearching the autoresearch agent for eight days. The result beats the harness we hand-tuned for two years, on held-out benchmarks: 🧵(1/7)