Catherine Nix retweeted
Children who take music lessons develop a larger corpus callosum, the bridge between the two halves of the brain, and the change is permanent. A 2005 review in the Annals of the New York Academy of Sciences found that early music training produces structural brain changes that persist into adulthood, even if the person stops playing.
The review was led by Gottfried Schlaug at Harvard Medical School, one of the leading researchers on music and the brain. He found that children who started instrumental training before age seven had a significantly larger anterior corpus callosum than non-musicians, and the size difference was still visible in adults who had not touched an instrument in years.
The corpus callosum carries signals between the left and right hemispheres. A larger one means faster, richer communication between the two sides, and the effect shows up in tasks that have nothing to do with music: spatial reasoning, verbal memory, and the ability to process multiple streams of information at once. The music built the highway, and the brain uses it for everything.
Schlaug also found that musicians had larger cerebellums, the region involved in timing and motor coordination, and more grey matter in the areas that process sound. The brain had physically reorganised itself around the demands of the instrument, and the reorganisation was visible on a scan.
The age window matters. Children who started before seven showed the largest changes. Children who started after ten showed smaller ones. Adults who took up an instrument for the first time showed the least structural change, though they still showed some. The brain is most willing to be rebuilt by music during the years when most parents are debating whether to sign their child up for lessons. pubmed.ncbi.nlm.nih.gov/1659…
Catherine Nix retweeted
MIT published a brutally honest report on what AI is doing to students.
A committee of professors and students spent five months studying how AI changed learning on campus, and the findings read like a warning to every university on the planet.
Study groups are disappearing. Office hours are emptying out. Problem sets and take-home exams no longer prove anything, because AI can produce credible solutions to almost any written assignment in the undergraduate curriculum. Students who lean on chatbots lose mastery and confidence, and some slip into what the report calls cognitive surrender, reaching for AI at the first hint of struggle.
The numbers are rough. 46 percent of surveyed MIT undergrads use LLMs daily. 90 percent worry about their own overreliance. Undergrads who feel AI makes them replaceable now outnumber those who feel it makes them capable.
The committee's answer surprised me. They refused to fight AI with surveillance. The report calls AI detectors unreliable, says lockdown browsers feel like spying, and warns that policing students builds a classroom atmosphere of mutual distrust.
Instead, MIT wants to rebuild education around the things AI can't replace. That means oral exams, semester portfolios, in-person project work, and a required social component in every subject. The report even floats the idea of rethinking grades entirely, since without a GPA to optimize, much of the incentive to cheat with AI evaporates.
The committee warns professors against replacing undergrad research assistants with AI agents just because they're cheaper, because a university exists to grow people, not output.
The most famous tech school on earth admitted the machines broke its way of teaching. Its answer is more humans, not more software.
Catherine Nix retweeted
Cillian Murphy said something about women that stopped every relationshippsychologist who heard it.
In three sentences he described something most men spend their entire lives unable to articulate.
And what he said will change how you understand every relationship where one person sees more clearly than the other...
Catherine Nix retweeted
Elon Musk on the most underrated reason to read a lot of books:
Asked about the search for meaning, the Tesla and SpaceX CEO goes straight to reading volume.
"I encourage people to read a lot of books. Just read, I mean basically try to ingest as much information as you can and try to also just develop a good general knowledge, so you at least have like a rough lay of the land of the knowledge landscape."
The standard he sets is low on purpose. A rough lay of the land is all he asks for:
"Try to learn a little about a lot of things."
Then comes the reason, in the form of a question most people never think to ask themselves:
"You might not know what you're really interested in. How would you know what you're really interested in if you at least aren't doing a peripheral exploration broadly of the knowledge landscape?"
That question is the whole point. Reading widely works as a search function.
You can only be drawn to a field you have actually encountered. The set of things you are capable of wanting is capped by the set of things you have been exposed to, and for most people that exposure arrives by accident: whatever your parents did, whatever your school offered, whatever your first job put in front of you. Read nothing outside that and you are choosing from a menu someone else handed you.
Books are one input. Musk applies the same logic to people:
"And you talk to people from different walks of life and different industries and professions and skills and occupations. Like just try, you know, learn as much as possible."
Same mechanism, more surface area.
When the interviewer reframes all of this as a search for meaning, Musk accepts the framing and routes it straight back to reading:
"Yeah, what's the meaning of life and all. But just generally, like I said, I would encourage people to read broadly in many different subject areas and then try to find something where there's an overlap of your talents and what you're interested in."
The reading populates one half of that overlap. Talent, the other half, tends to reveal itself whether you go looking or not.
@elonmusk is specific about why talent on its own falls short:
"People may be good at something, or they may have skill at a particular thing, but they don't like doing it."
Talent on its own is a trap. Being good at something generates praise, money and more of the same work, which locks you in years before anyone asks whether you enjoy it. Plenty of people end up a decade into a career they excel at and quietly resent, having optimised for the half of the equation that pays out fastest.
His conclusion:
"So you want to try to find a thing where that's a good combination of the things that you're inherently good at, but you also like doing."
Ann Widdecombe defended free speech. But it’s hard to defend some reactions to her death
irishtimes.com/opinion/2026/…
Catherine Nix retweeted
I asked Claude about the air conditioning debate in Europe, and it really didn’t pull any punches.
Let’s learn from this & protect the next generation… theguardian.com/commentisfre…
@ such a difficult time, thank you for recognising the efforts of frontline staff independent.ie/county/limeri…
Elon Musk literally revealed the fastest way to become irreplaceable in the AI era:
Elon Musk reveals the single question he uses to spot liars in interviews:
"When I interview somebody, I really just ask them to tell me the story of their career, what are some of the tougher problems they dealt with, how they dealt with those, and how they made decisions at key transition points. Usually that's enough to get a very good gut feel about someone."
Elon explains what he's looking for:
"What I'm really looking for is evidence of exceptional ability. Did they face really difficult problems and overcome them?"
Then he shares how to tell if someone is lying about their accomplishments:
"You want to make sure that if there was some significant accomplishment, were they really responsible, or was somebody else more responsible? The person who actually had to struggle with the problem, they really understand it. They don't forget. You can ask them very detailed questions about it and they will know the answer. The person who was not truly responsible for that accomplishment will not know the details."
On whether college degrees matter:
"There's no need to have a college degree at all. Or even high school. If somebody graduated from a great university, that may be an indication they'll be capable of great things, but it's not necessarily the case. Look at Bill Gates, Larry Ellison, Steve Jobs. These guys didn't graduate from college. But if you had a chance to hire them, of course that would be a good idea."
He concludes:
"I'm just looking for evidence of exceptional ability. If there's a track record of exceptional achievement, it's likely that will continue into the future."
Catherine Nix retweeted
Haemodynamic equations are useful. But they also mislead.
Take:
CO = HR × SV
CO ≈ (MAP − RAP) / SVR
Both are mathematically true. But they can make the variables they contain look like the controllers of output.
Often they are not.
In the intact circulation, these equations describe the resolved state of the system. They do not, by themselves, tell you what is supplying energy, what is constraining flow, or what is actually limiting output.
That is one of the central themes of our review:
Energy, flow and pressure in the cardiovascular system: a narrative review of how the circulation works.
doi.org/10.1111/anae.70238
Catherine Nix retweeted
🫀🤓Pressure does not move blood. Energy does.
This outstanding review challenges one of the most deeply rooted concepts in haemodynamic management: the idea that pressure variables are the primary drivers of circulation. Instead, the authors propose a physiology framework where the heart supplies energy, the vasculature defines constraints, and pressures merely reflect system state.
Several concepts deserve special attention for critical care clinicians:
• Mean systemic pressure does not “drive” flow
• Right atrial pressure is a dependent variable, not a therapeutic target
• Venous return depends on inflow acceptance and inlet impedance
• Raising pressure without improving flow may worsen congestion
• Shock should be interpreted as either impaired venous delivery or impaired cardiac acceptance
Clinically, this framework helps explain why:
• CVP-guided fluid loading often fails
• Vasopressors may normalize MAP without restoring perfusion
• Congestion can coexist with preserved arterial pressure
• Flow responsiveness matters more than static pressure targets
One of the strongest messages of the paper is simple but powerful:
“Pressure is not perfusion.”
For intensivists, anesthesiologists, and cardiogenic shock teams, this review is worth reading in full. It reconnects bedside haemodynamics with first-principles physiology.
Miller A, Anaesthesia. 2026. doi.org/10.1111/anae.70238

























