Snapshot · Hard Fork
Over 800 mathematicians signed the Leiden Declaration expressing deep concern about irresponsible AI use in mathematics and potential erosion of the discipline.
Where this was said
At 42:37 · chapter starts 40:20
Hartnett offers a memorable vignette from the Institute for Advanced Study in Princeton — described as 'the citadel of modern math.' In one afternoon, he encountered two top-tier mathematicians with completely opposite views. The first had just closed Gemini in frustration after it told him something demonstrably false. The second, superficially similar on paper, predicted that AI would put mathematicians out of business within 2 years because it would soon be strictly better than humans at all of it. Terence Tao — the greatest living mathematician and most important figure in the debate — sits squarely in the middle [1] — Kevin Hartnett "At the Institute for Advanced Study, Kevin Hartnett met two top mathematicians in one afternoon with polar opposite views — one dismissed A…" 40:18 . Tao's view, which Kevin Roose describes from a recent OpenAI video, is that AI is like an 'Iron Man suit' or a 'jetpack for thoughts': it allows mathematicians to test many more ideas quickly, radically lowering cognitive friction for exploratory work. Hartnett suspects the dismissive camp was in the majority a year ago but is shrinking rapidly.
Over 800 mathematicians signed the Leiden Declaration warning that AI is producing plausible but unreliable proofs, eroding human expertise, and steering mathematical priorities toward what AI is good at rather than what matters. Kevin Hartnett reads it as a field asserting: this is our discipline, and you don't get to tell us how it runs.
Animals first sensed light 540 million years ago, triggering an evolutionary acceleration known as the Cambrian explosion within 10 million years.
It is estimated that half of all cortical activity in the human brain is involved in visual function, underscoring vision's central role in intelligence.
Cognitive neuroscience literature shows that by age 6, humans can recognize tens of thousands of different object categories — far more data than early AI systems were trained on.
Only about 3% of FDA-approved drugs have genuinely unclear mechanisms of action, making an unknown mechanism a meaningful early red flag for any compound.
Even compounds that clear preclinical testing often fail in humans: 30 to 50% of drugs entering phase 1 trials do not advance to phase 2, frequently because human behavior differs from animal models.
More than 80% of published BPC-157 research comes from a single academic group whose researchers have IP and commercial interests connected to the molecule, limiting independent replication.
Roughly 100 peptide drugs are already FDA-approved, about 150 more are in clinical trials, and 600–700 are in preclinical development, underscoring the legitimacy of peptide science broadly.
The scientist who discovered BPC-157 refused to disclose the screening method used to identify the compound and has never fully published the parent protein sequence — what Peter Attia calls 'scientific trust me, bro.'
The brain's visual, auditory, and motor cortices light up nearly identically whether an experience is real or imagined, making visualization a form of actual neural training.
We use essential and analytics cookies to run Vuci. To understand how the site is used: Privacy Policy.
Install Vuci on your phone
Add it to your home screen for a faster, app-like experience.
Install Vuci on your phone
Tap the Share button, then “Add to Home Screen”.
A new version is available
Reload to get the latest Vuci.