egocodedinsol

Yeah I’m checking - I saw several other oncologists suggesting song a separate discussion.

Here’s a link to the abstract: https://ascopubs.org/doi/abs/10.1200/JCO.2025.43.16_suppl.85...

apparently it was prospective and randomized. I’m a little shocked by the effect size.

I'll grant that we could send humans to mars sooner if we really wanted to. My point is that not achieving a bigger dream doesn't make current progress a hype wave followed by a winter.

And "LLM's just make plausible looking but incorrect text" is silly when that text is more correct than the average adult a large percentage of the time.

this attitude is so ridiculously disingenuous. Surely if a computer can score incredibly well on math olympiad questions, among other things, "a computer can make plausible-looking but incorrect sentences" is dismissive at best.

I have no idea about AGI but honestly how can you use claude or chatgpt and come away unimpressed? It's like looking at spaceX and saying golly the space winter is going to be harsh because they haven't gotten to Mars yet.

What nonspecific advice do you have for immigrants who want to (co)found companies but are on h1b’s or student visas?

they didn’t submit it here - I’m not sure they bear a responsibility to make sure their work is accessible to HN or any other target audience. If you don’t find an otherwise respectful and substantive blog post useful, perhaps best to leave it be.

An unsophisticated person looks at this and says golly I better get tan!

A somewhat sophisticated person says something like the above.

People who change the world will wonder there’s something there. especially given the sober and candid examination of possible confounding factors and mechanisms of action.

“There are approximately seven scanners per million inhabitants and over 90% are concentrated in high-income countries. We describe an ultra-low-field brain MRI scanner that operates using a standard AC power outlet and is low cost to build.”

This is fantastic. What a sentence to get to write.

There are few good passive investments right now. There's so much capital available in search of returns that all the good ones and most of the mediocre ones have been taken.

This is one of the more insightful comments in this thread. The risk is not merely that Sam’s investments are not diversified, it’s that Sam has competition from more sophisticated capital. Truly passive investments often scale (and get more passive with scale). That scale attracts a lot of capital that can afford lower revenue, higher risk, and better expert knowledge.

This comment may be unpopular because it's not tremendously useful.

I'm not sure that's necessarily true. It is true (at least with a non-constructive proof) that if you pick a 'random' real number then it contains all possible PDFs with probability one ( or that the set of numbers for which this is not true has lebesgue measure zero). But I'm not sure it's known that pi has this property.

It says mAP right above the table. If you know what mAP is then you know the units.

Professors will rail against imprecision to undergrads and young graduate students but they use it all the time in real life.

I can already hear my professors saying "stop commenting on style, what do you have to say about substance?"

Where do you work if you don't mind my asking?

I think I missed your overall point?

Surely there's something to learn here though. I haven't read the original paper but a quantity that's preserved across brain scales is either an artifact or a neat insight.

Your criticism reads like someone accusing economists of being outrageously misleading when they don't sample individual households but measure macro indicators. It's like saying Ramon y cajal was ridiculous because he couldn't image the neuropil effectively. Or like saying early optogenetics experiments were ridiculous because who knows if you're stimulating a neuron in a realistic manner?

And in any case, it's true that synapses are comically small relative to voxel size, but we also have some reasonable information about projection patterns and synapse number from various tracer or rabies studies with which you are no doubt familiar.

I haven't read the nature paper the press release is about and I'm not a huge fan of many d/fMRI practices or derived claims. And I've worked with enough mammalian dwi data to be skeptical of specific connection claims. But this strikes me as a rather interesting result even if you can't measure all the synapses at the right resolution: either the tractography method has connectivity conservation artifacts baked in, or there's something interesting going on.

In my experience, you are way off base. Doctors can be very arrogant but I've never met someone from another profession who could point me to research articles regarding their proposed plan of action. Doctors at major hospitals are often either a) residents who are in their nth year of leaning post med school, or b) expected to publish at least case study papers regularly or communicate with those that do.

Your analogies would make more sense if you spent 2 hours on documentation for every hour you spent coding or bug finding.

"You can see the computer age everywhere but in the productivity statistics." This was true for a few years, until it wasn't.

I'm not sure that logic holds - swimming in the ocean isn't the same as eating swordfish with respect to mercury, for instance.

Your description of the localization approach is accurate, but this system is almost certainly Brainsight, given the screen shown in the image at the bottom, the IR camera in that image, and the shape of the tracker arm.

The general approach is straightforward: MRIs are have real-world coordinates. Anything on the head (TMS, EEG, a surgical instrument) also has real-world coordinates. To co-register the two, you need to associate 1) markers at MRI time 2) markers at TMS time.

Once you have that correspondence, you can position any other objects relative to either one, like surgical instruments with reflective markers or TMS systems or whatever.

FWIW, it's not like the doctor is going to send you home with a diagnosis based on this screening. The psychological burden would persist only until further testing and analysis. And in any case, human radiologists have FPs and FNs, too. The question is how close and in what circumstances are we approaching current human radiologist performance.

I'm saying that even within neuroscience there is large variation in publication frequency and expectation.

So if person from neuro discipline A and neuro discipline B are applying for the same job in data science, discipline A could get screened out because they spent years training a monkey to do a brain machine interface task while person B published five fMRI papers in three years. Neither candidate is going to use their specific neuro expertise, but rather their general data science skill set. One will be at a huge disadvantage unless she is hired directly by people who know her field.

FWIW that social standard, and the mindset behind it can really penalize some fields. FWIW, in some fields of neuroscience it is common even for very successful phds to not publish before defense, and a single paper requires massive amounts of work, while other neuro fields churn out short paper after short paper because the culture is focused that way, and the experiments less time consuming.

It puts some students at a severe disadvantage for hiring because they get screened out because they chose a field that publishes 50 page papers instead of 2 page papers.

They'll page them to consult on something, usually waking them up.

IME they're usually not asleep.

Thank you. “Obvious” can be a dangerous concept, especially when paired with sarcasm.

I agree that children have historically put in a lot of work. The premise of the article is that the “Maya method” makes them more likely to volunteer to do so.

At least that’s what led the author to try to engage the toddler in chores.

great touch: changing the time keeps the old contour and plots a new one in a different color automatically.

in general correlation doesn't imply causality.

Yes, we know. But it's often a sign that something interesting is going on.

Yes! And that paper is a fantastic example of making clear criticisms with actionable fixes and the code to perform the comparisons properly.

Preferential attachment is such a beautiful theory because it gives power law distributions of node degree. But real world networks seem to have systematic deviations from power law so often one wonders why more work wasn’t done to find schemes that generate, e.g. lognormal distributions.

It’s possible that preferential attachment isn’t even a good theory for the underlying principle, it’s just that the underlying principle gives fat tails in degree distribution and power laws give okay fat tails.

Sometimes, though, one doesn’t care if it’s a power law per se or just that it has fat tails. In that case why use a power law and not just a better fitting lognormal (or say kernel density estimation)? But power law seems sexy because of its importance in physics (eg scale free, renormalization stuff), so people ran with that when network literature blew up in the mid 2000s.

Forgetting about “official” rankings for now, Iirc uchicago has had more nobel prize winners passing through in some capacity than anywhere else, and its graduate programs have been among, or the best for a long, long time. It may not have had “kitchen table” renown but it was well known in academics.

For example, several years ago a couple friends I knew withdrew their undergrad applications to Harvard when they were granted acceptance to uchicago because of the mathematics curriculum (it wasn’t an objective choice necessarily, but it was a well thought out one that was academically motivated).

It was a little odd that its graduate programs were almost universally held at the pinnacle of academics, while most people didn’t think the undergrad was that good. That changed when uchicago accepted the common app (looks more selective) even though the rest didn’t change as much. Suddenly it skyrocketed in the rankings. It was always that good, though.