We have spent years being told it is âjust a period problemâ while our skin, our weight, our mood, and our energy were all falling apart. Today, the medical world finally admitted you were right.
PCOS is now PMOS.
@BenjaminJLandon@FrailSkeleton Wonder Fair, right? It's amazing, a couple years ago I bought the best planner that I've ever had and some really nice art supplies
The $46 billion vape industry hired flavor chemists to solve a specific problem: nicotine tastes bitter. The human tongue has T2R receptors that detect nicotine and trigger aversion. So the industry reverse-engineered the problem. They loaded e-liquids with fruity aromatic compounds like farnesol, farnesene, and ethyl butyrate that suppress the bitterness signal and activate sweetness perception through the orbitofrontal cortex instead.
Turns out they built something more powerful than a nicotine delivery system.
A 2023 study in the Journal of Neuroscience found that green apple vape flavorants, with zero nicotine present, independently fire dopamine neurons in the ventral tegmental area and increase dopamine release in the nucleus accumbens. The same reward circuitry that nicotine hijacks. The flavor chemicals alone were producing reward-seeking behavior in mice. A separate study found strawberry additives significantly increased nicotine vapor sampling, meaning the fruit smell made subjects inhale more of the drug without any conscious decision to do so.
95% of vape users choose flavored products. The industry has always framed this as âconsumer preference.â The neuroscience says the flavors are pharmacologically active compounds that directly alter brain reward circuits and increase drug intake.
Now look at what those compounds do once the device gets tossed. The UK was discarding 5 million disposable vapes per week before the ban. The aromatic volatiles donât stop broadcasting once the device is empty. Orthonasal olfaction, the same pathway that makes you smell a strawberry from across a room, works identically in mammals. A squirrelâs olfactory system processes fruity volatiles through the same receptor families humans use. The signal reads as food.
Nobody saw squirrels gnawing on Marlboro butts for 60 years. Vapes show up and suddenly thereâs footage from London, Philadelphia, and Wales. The animals are chewing on lithium batteries wrapped in candy-scented plastic because the flavor engineering worked exactly as designed on a nervous system it was never tested on.
The lithium in those discarded vapes equals 5,000 electric vehicle batteries per year. Oxford researchers found the cells inside can cycle 450+ times, but the product is built to be used once and thrown in a park.
A squirrel holding a blueberry vape on a Brixton fence is the most honest product review the flavor chemists have ever received.
This paper from Harvard and MIT quietly answers the most important AI question nobody benchmarks properly:
Can LLMs actually discover science, or are they just good at talking about it?
The paper is called âEvaluating Large Language Models in Scientific Discoveryâ, and instead of asking models trivia questions, it tests something much harder:
Can models form hypotheses, design experiments, interpret results, and update beliefs like real scientists?
Hereâs what the authors did differently đ
âą They evaluate LLMs across the full discovery loop hypothesis â experiment â observation â revision
âą Tasks span biology, chemistry, and physics, not toy puzzles
âą Models must work with incomplete data, noisy results, and false leads
âą Success is measured by scientific progress, not fluency or confidence
What they found is sobering.
LLMs are decent at suggesting hypotheses, but brittle at everything that follows.
â They overfit to surface patterns
â They struggle to abandon bad hypotheses even when evidence contradicts them
â They confuse correlation for causation
â They hallucinate explanations when experiments fail
â They optimize for plausibility, not truth
Most striking result:
`High benchmark scores do not correlate with scientific discovery ability.`
Some top models that dominate standard reasoning tests completely fail when forced to run iterative experiments and update theories.
Why this matters:
Real science is not one-shot reasoning.
Itâs feedback, failure, revision, and restraint.
LLMs today:
âą Talk like scientists
âą Write like scientists
âą But donât think like scientists yet
The paperâs core takeaway:
Scientific intelligence is not language intelligence.
It requires memory, hypothesis tracking, causal reasoning, and the ability to say âI was wrong.â
Until models can reliably do that, claims about âAI scientistsâ are mostly premature.
This paper doesnât hype AI. It defines the gap we still need to close.
And thatâs exactly why itâs important.
Cuando me digan que el privilegio de ser hombre, blanco, heterosexual no existe y soy una exagerada. Piensen que un hombre como Kast, va a ser presidente con ninguna preparaciĂłn, con cero manejo de los temas paĂs, y con nula empatĂa. Entitlement que le dicen