https://parekhnish.github.io/
Not much on there, but hey, something's better than nothing!
110 karma · joined April 20, 2018
Not much on there, but hey, something's better than nothing!
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...).
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!
[1]: Wikimedia Phabricator link: https://phabricator.wikimedia.org/T273741
[2]: HackerNews thread: https://news.ycombinator.com/item?id=26072025
www.ai/publicity
They provide links to 5 papers on their website [0], but they are either ArXiv links (so preprints, not peer-reviewed) or blog posts on a website that seems to only contain their own material. They do not cite any clients on their website, they do not showcase any product that they sell.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?
The only "bug" I see, if at all, is that the hue value does not wrap around, i.e. the colors shown at 360 are not the same colors shown at 0.
I am a non-native English speaker, and I have been trying songs from different countries. I did notice that English songs have a better match than songs from other regions and languages[0]. I wonder if their training dataset has "overfitted" to such music, or is such music inherently represented by some underlying features that are better distinguished than others.
[0]: E.g. English ("My Heart will Go On" and "Skyfall") fit with 78% and 85% respectively, while Japanese ("Tonari no Totoro") and Hindi ("Tum Hi Ho") fit with 42% and 48% respectively
Just an aside: Although common perception is that "weapons-grade" refers to the highest quality, in reality it refers to the lowest-possible quality that meets the bare minimum requirements!
They have a "curation"-method to selecting the articles to show. I am curious as to if this extension uses pre-selected websites (e.g. WSJ will always show the Right-leaning view), or is there something smarter than that
Also, not sure if genuine mistake or sneaky "clickbait": The video has its `video_poster` image that's eerily similar to a YouTube screenshot, though the video itself is hosted on Amazon's servers, not YouTube.