For anyone confused what "RAG" is: it stands for "Retrieval Augmented Generation", which is where the LLM model is paired with some sort of "database" (often a vector database) where LLM looks up additional data when performing the task.
Use the 'continue from this clip' feature. Next, merge the newly generated segment with the existing one using the 'get whole song' feature.
Or just get creative, use the vocal remover to extend the background sound, cut and paste different parts of it using the good old DAW. By using this method, i managed to make several "full" songs :
Our models support full 2+ mins of coherent generation but generating a couple of verses at a time through continue gives good results you can keep picking the continuations that sound best!
Bit late to the party, but this person is very much correct. I also do BMI work and optics is undoubtedly the future for neuroscience. The optics book you want to get is Hecht:
It's much more than the optics chapter you'll get in a physics textbook. It goes over the classical ray optics in good detail, does a great job with traditional matrices and that formulation of optics (the one that the design programs like Zemax use), goes well into the real meat-n-potatoes of wave optics (including birefringence, a huge part of biological optics), gives you a good accounting of how lenses and other optical devices are actually Fourier transformers, and also dives into the more esoteric optical devices (a must for practical neuro-optics).
It's an upper-division/graduate level book, fyi. So I'd back-load it in your study course. Though in terms of neuro-optics it's more of a keyhole book.
If you are particularly interested and really want to know what's actually going on with EM, then you need to go through Jackson:
This is the book on EM, but is very much physics graduate student level. And honestly, I don't think you's need it for BMI stuff. But if you don't go through it, you'll just be trusting other people when they say your ideas won't work and they can't really explain it to you. Just going through Jackson is a bit of a hazing experience and will earn respect.
That's a good point. The project-first approach worked very well for me when learning new software frameworks/libs/etc.
My main concern with EE is that once I'll get to the brain-computer interfaces, I'll be in a situation where there aren't many off-the-shelf components/solutions available, and at the same time I'll likely need to know how I can push physics closer to the edge. I suspect I may need a better theoretical foundation to do that.
That said, I definitely like the idea of focusing a lot on hands-on projects.
You are not going to start anywhere near the area where you have to go "full custom". That is, you won't be spinning custom ICs, you'll be assembling custom PCBs from off-the-shelf components. Possibly expensive ones. But that $1000 OTS part is an insane bargain compared to any chip fabbed just for you.
First make your thing do something, anything at all. Second, make it do something useful. Third, make it do the right thing, the thing you need, your goal from the beginning. Only then should you optimize it, making it smaller or cheaper or lower power or prettier or.... This is the road to success in the "R" phase of R&D.
About 1/2 of the textbooks came from the old course outlines (e.g. https://ece.uwaterloo.ca/~ece207/) and class shopping lists on UWaterloo book store. About 1/4 were guesses, and the other 1/4 I don't know where to even start looking.
The higher the course the lower the confidence of having the right book.
OP here. Nice, thanks! I didn't put math down because my undergrad was in applied math and I got to use it a lot early in my career. But sounds like I'll definitely need a refresher.
Yeah, my first guess is the movement of that faint inner line triggers the Parasol cells or some other movement detection cells in our retina (https://en.wikipedia.org/wiki/Parasol_cell).
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