"I wish I'd supported the crazy folks who did carrot science in public and distributed seeds and allowed everyone to breed them so that we could all find better varieties for the common good! They still seem to be eating well."

(I see your very practical point, but I do think making the locally suboptimal choice in the hope of better long-term outcomes is a valid philosophical position.)

I wonder if this particular backdoor (front door?) has been used before; perhaps there are black-hat services that sell grade upgrades.

[1]: https://xkcd.com/1172/ [2]: https://xkcd.com/1053/

But the pattern of activity of thousands of voxels across cortex does contain reliable information! And a decent amount of it too, at least in sensory cortices.

Neuralink is doing interesting BCI research, with decent hardware, but it's not really a step-change above and beyond the rest of the field.

There's definitely a lot of promise in using BCIs for rehabilitation of patients with brain injuries but their input-output capabilities are still incredibly crude: for example, we can't reliably "write" to the brain to make people perceive things beyond very simple stimuli (e.g. a phantom touch sensation, or a visual phosphene).

This is understandable: the brain has a bajillion neurons and we only have ~1,000 electrodes that aren't particularly precise in how/where they zap the brain---and even if they were, we don't really know well enough how the brain works to "control" perception finely.

Other problems for BCIs include (i) "representational drift", where the brain's code changes over time, so you need to keep fine-tuning your interface in some sort of closed loop fashion and (ii) damage/scarring to neural tissue.

> Is there enough signal for this to really work?

I'm not quite sure what Neuralink's marketing claims are, so I'm not sure what you mean by "this" here. But intracranial electrodes do have a surprising amount of signal, especially relative to non-invasive methods (I'm currently collecting some iEEG data myself!)

I really want the sci-fi future where we have brain-computer interfaces that augment our cognition and perception, but we're nowhere close---though we're getting better.

I tend to think of fMRI data as some highly nonlinear transform of whatever neural activity is occurring in a particular region of the brain, at pretty coarse spatial resolution (~1-3 mm) and pretty bad temporal resolution (~5-15 s).

Sure, it's no direct measure of neurons firing, but that doesn't mean there isn't information in the signal that we can interpret and maybe use (see [1] for a recent example of reconstructing seen images from brain activity)

As a cognitive neuroscientist, I tend to abstract away a ton of the details (neurons, molecules) and focus on more general computational principles: how do we get complex behavior from many simple interacting units---voxels in fMRI, for instance?

Regarding the specific paper you posted, I saw some of the discourse around it but haven't read it carefully myself (it's not my area of expertise). I saw some recent re-analysis of that data [2] that argues that the result isn't valid, but need to look at it more carefully.

[1]: https://www.nature.com/articles/s41598-025-89242-3 [2]: https://www.biorxiv.org/content/10.64898/2026.04.21.719913v1

Specifically, using a linear approach (like PCA, but slightly fancier), we find that stimulus-related information is present along many, many dimensions of the neural response---much more than previously expected/reported.

[1] https://journals.plos.org/ploscompbiol/article?id=10.1371/jo...

> “I’m here to learn how to do things,” she adds. “I don’t think outsourcing it to a large language model is the goal of a PhD for me.”

I wanted my cognitive abilities and technical skills to improve, not just produce output more efficiently. IMHO, abstracting over these low-/mid-level skills and focusing on "high-level ideas" is worth it for experts who've already internalized the deep knowledge and know-how; for a novice like me, I need to suffer through the details before understanding things better.

Other more idiosyncratic reasons:

(i) I try to use only FOSS tools on principle, and frontier models aren't;

(ii) When I graduated, LLMs weren't quite as great as they are today and I wouldn't trust their output for anything important;

I would happily use LLMs to learn new things though! I've tried some local LLMs, but they weren't particularly impressive last time. I should re-evaluate now; it's been several months.

I know nothing about the NHS, so I have no idea if this is plausible.

This annoyed me until I realized pandoc supports separating [the link text] from the link location.

  [the link text]: 
      "`title` parameter of the  tag, if converted to HTML"

> “But COVID’s worse,” he added. A case of COVID-19 is about 10 times as likely to induce myocarditis as an mRNA-based COVID-19 vaccination, Wu said. That’s in addition to all the other trouble it causes.

I recall hearing about this as a low-probability potential side effect during the pandemic. What do you mean by "swept this under the rug"?