(Disclaimer: I worked in retinal imagery AI for a few years)
I understand why this seems like pseudoscience, but I'd like to explain the assumption better.
As the article states,
> a scan of the retina is the only non-intrusive way to view layers of cells below the skin’s surface.
As an extension, you could also make the case for being able to view the nervous system via such imagery. As stated in [1],
> Despite its peripheral location, the retina or neural portion of the eye, is actually part of the central nervous system.
The theory is that such a non-invasive of visualizing crucial parts of the inner body opens up a "window" into noticing such biomarkers well before the common-but-late-stage symptoms are noticeable.
As for your gripe about:
> let’s dump medical records and retina images into a neural network and see what correlates
, I agree that this requires more careful analysis, but I assume that will happen as part of clinical trials of any such technology. The first foray, which is more experimental than anything concrete, is what this article seems to suggest.
Generative AI for images and music produce pixels and waveform data, respectively. I wonder if there is research into "procedural" data; so in this case, it would be SVG elements and, perhaps, MIDI data respectively.
I know training data would be much more harder to get, (notwithstanding legal ramifications), but I think that creating structured, procedural data will be much more interesting than just the final, "raw" output!
I've thought about this too. The instruments themselves can be synthesized for extremely high quality audio. All we need is the musical structure - the MIDI.
Right, I think the hotel room use case helps a lot with the intuitions here. And it helps to see the COUNTER EXAMPLE:
* Hotel A [Jan 10, Jan 13] means 4 nights; same as [Jan 10, Jan 14).
* Hotel B [Jan 13, Jan 15] means 3 nights; same as [Jan 13, Jan 16).
These intervals overlap! That is, if I try to get them together I book Jan 13 on both Hotel A and Hotel B.
With the half-open interval is really easy to spot: you cannot concatenate unless the open-end and the closed-begin are the same.
So you can concat [Jan 10, Jan 14) with [Jan 14, Jan 16); BUT you have an overlap if you see this [Jan 10, Jan 14) with [Jan 13, Jan 16) as in the previous examples.
With the closed interval this is hard to see. As in the example by @parekhnish; it seems that [Jan 10, Jan 13] and [Jan 13, Jan 15] are concatenable and there's no overlap. But the final operation ends up booking on Jan 13 twice.
They raised $580M in this Series B round, which is interesting:
They provide links to 5 papers on their website [0], but they are either ArXiv links (so preprints, not peer-reviewed) or blog posts on a website that seems to only contain their own material. They do not cite any clients on their website, they do not showcase any product that they sell.
For a company with 40 employees, only over a year in existence, and with little to no "verification" of their work, I wonder how do they raise such a huge amount?
Good point, thanks for pointing it out. I think I was trying to deal with it, but for some reason I just let it be this way. Also contributions are welcome! :)
I understand why this seems like pseudoscience, but I'd like to explain the assumption better. As the article states,
> a scan of the retina is the only non-intrusive way to view layers of cells below the skin’s surface.
As an extension, you could also make the case for being able to view the nervous system via such imagery. As stated in [1],
> Despite its peripheral location, the retina or neural portion of the eye, is actually part of the central nervous system.
The theory is that such a non-invasive of visualizing crucial parts of the inner body opens up a "window" into noticing such biomarkers well before the common-but-late-stage symptoms are noticeable.
As for your gripe about:
> let’s dump medical records and retina images into a neural network and see what correlates
, I agree that this requires more careful analysis, but I assume that will happen as part of clinical trials of any such technology. The first foray, which is more experimental than anything concrete, is what this article seems to suggest.
[1]: https://www.ncbi.nlm.nih.gov/books/NBK10885/#:~:text=Despite...).