kcoul

I love how the "pseudoscientific" word gets busted out anytime an understudied area of research is presented. Keep in mind that the state of science in 1000 years from now will prove all sorts of things that hyper-rationalists might scoff at today.

I'd say this is a bit akin to whether people can feel the weather in their bones - biometeorology. The only difference is that the airplane creates a temporary, highly artificial "weather" environment. But I think it's important to include the physical interactions between that environment and the one outside of it, and not only account for interior conditions like air pressure, etc.

We'll probably learn a lot more about this if we ever make it far enough as a civilization to have a shot at long distance space travel, i.e. to Mars.

This gets into how advanced the prompt engineering actually is. I anticipate discussion around what "state-of-the-art" prompts look like, since, as the OpenClaw founder suggested, Prompt Requests may well replace Pull Requests when a set of small tweaks to the prompt may yield vastly improved output.

This of course needs to be coupled with actually staying accountable for what the entirety of the codebase looks like. I imagine many people are unwilling to slow down enough to actually do that accounting/review, and the architecture might gradually shift towards entropy.

Has anyone else found a similarity between how you feel at the end of a long AI coding session, and getting off of a long haul flight? I think the reasons are similar.

On the flight, it's not exactly like you directly feel the wind going through your hair as you travel 1000km/hr, but your body still knows that you did. You feel the lag immediately, not really due to a time zone difference but due to how unnatural it is to move so far in so short a time.

I feel the same way after a highly productive AI coding session. I used to anecdotally mention to others that I liked to maintain and use older machines because it felt nice to get little breaks here and there while the machine took longer to open a browser/app, return search results, render a file, etc. This is the opposite of that. Everything is happening so fast, your mind is taxed differently than if you are responsible for typing everything yourself... no matter how fast you could type code.

That said, I don't think it's entirely my increased cognitive load that makes me feel drained after a session, it's as though you can somehow feel the token burn, the water/electricity use, just as you somehow felt the wind shear on the airplane you were just in for many hours.

This must be a multithreaded port right?

How did you deal with the difficulty (security-wise) of handling C++ threads in a WASM context?

https://news.ycombinator.com/item?id=27905555

Maybe they wanted to see if any individual efforts piqued the interest of the reader base. In my case, it was FlipCTL that did so. I definitely think a generic library for hardware button interfaces to a menu system not requiring windowing is a great resource for resource-constrained embedded projects, so I'm looking forward to contributing to this.

In the meantime, what would you recommend (if there's anything off-the-shelf that would work in a plug-and-play manner?)

I had a project in mind that was waiting for something like this! :)

I wouldn’t call this 3blue1brown video a reference, but until I watched this (coming from an audio background), I didn’t quite grasp that a continuous stencil of any complex silhouette could be described in terms of a set of contributing vectors. Helped click that there is a perfect visual analogy to the deconstruction of complex audio to sine waves.

https://youtu.be/r6sGWTCMz2k

Exactly - I have done a number of research studies focused on how musicians do or do not develop robust memory models of the pieces they learn, based on how they practice, and the data consistently pointed to a correlation between robustness and practice approach.

Anyone who has taught piano for example knows the most common mistake of novice students is to omit sharp or flat notes (the black notes) when learning notated music which begins to include them. In this case, the student will practice the wrong notes for long enough before their next lesson that the wrong notes become engrained in their memory model, resurfacing under duress such as in recital. There are similarities for other instruments (strings: intonation, woodwinds: embouchure, percussion: rhythmic accuracy, etc.)

The most talented students seem to gravitate consistently towards robust memory models for their respective instruments technique as a way of freeing themselves up as quickly as possible for the more enjoyable aspects of perfecting a piece of music: refining expression.

Perhaps one day there will be tools which can assist those less naturally predisposed to developing robust memory models, before it's too late for their brain, the way the most talented students do.

I have been studying this problem as it developed over the past decade (mobile revolution), and am torn between the two perspectives on it.

What desktops and laptops afforded that mobile takes away, 8 usable fingers aside, is the factor of dedicated computer use (reduced context switching with non-mobile), providing a much better opportunity to keep predominant brainwave patterns away from the "fight or flight" state historically associated to rapid context switching.

Therefore there is one categorical problem (excessive computer use) that is indeed shared across mobile and non-mobile computational platforms alike, and we can point to the people who used their desktops or laptops so much that it could be considered unhealthy, all well before the mobile revolution.

At the same time, the modern epidemic exacerbates the problem by not only summing total computer time between mobile and non-mobile, but there is added the additional factor or rapid context switching which is nearly unavoidable with mobile platforms.

If that wasn't enough, there is also evidence that these newer behavioral patterns are bleeding back from mobile into non-mobile computing, meaning that people are now using desktop/laptops as though they were mobile platforms, rapidly context switching when 10+ years ago they simply did not do this.

Altogether, the evidence indicates that you are right overall, the smartphone was a catalyst to a change in how the internet is interacted with which is the real problem by and large, but conversely, we might be able to use both mobile and non-mobile platforms in a way which minimizes context switching and in so doing restores healthy beta brainwaves rather than encouraging the unhealthy "fight or flight" patterns indicative of this modern (first world) epidemic.

What the fork!

95 theses on this topic: http://95theses.co.uk/?page_id=21 Background: https://www.theguardian.com/technology/2017/oct/29/why-we-ne...

Location: Vancouver BC Canada; San Jose CA USA

Remote: Yes

Willing to relocate: Yes

Technologies: C#, Java, Python (scientific), C++, Unity, Unreal Engine, Computer Graphics, Digital Audio/DSP, Virtual Reality, Augmented Reality, Android

Résumé/CV: https://www.linkedin.com/in/kieran-coulter-a8248153

Email: kcoulter.dts@gmail.com

I'm of two minds on that note:

On one hand, I somehow feel it's appropriate that an open online course limit itself to methods that are accessible outside of medical research labs and hospitals.

On the other hand, I agree completely that someone could walk away after taking this course, never understanding that they would be dealing with a quality of data of considerably lower fidelity, to the point where failing to take that variable into account could easily lead to false conclusions.

Maybe this is why part of me is "glad" I cracked my head open at a young age and still have a significant gap there in the skull bone - I can get higher amplitude signal placing an electrode there than anywhere else on my head!

Sounds good.

This was what I was referring to above, seemingly the most hacker friendly EEG of them all, and shipping in January: http://www.openbci.com/

My research indicated that monaural and isochronic patterns are more effective than binaural.

However, if binaural beats were synchronized with optic driving (an audio pulse arrives in the given ear at the same moment a photic pulse arrives at the corresponding eye), then this kind of integrated approach could certainly trump them both (and simple optic driving as well).

I agree. The emerging field of data science can help us to make more sense of the patterns and lack thereof that can become apparent after high fidelity capture of our brainwaves.

On that note, I would have to say I was a bit disappointed by the Neurosky Mindwave Mobile unit I received - despite being able to bypass their simplified attention/meditation/blinking reduction of the raw input signals and capture the {delta, theta, ..., gamma} filtered bands for further processing, many people (myself included) complained about the apparently low quality of the data, specifically showing large amounts of delta band activity and little else. I resigned that the low-cost interface was simplified to the point where it was a novelty and little else.

Now I am narrowing it down to OpenBCI vs. Muse vs Emotiv. Picking the right one for the handful of projects I want to use an EEG for is proving to be difficult. I'm simultaneously attracted to the ability to take matters more into my own hands with OpenBCI, and the ability to just get started right away with a product like Muse or EPOC.

I'm curious if you were planning to use the Rift for photic entrainment. I haven't seen anyone else intending to get into photic stimulation with the Rift besides a project or two that never seemed to take off like Ocunaut, so if you do plan to, it would be great to collaborate somehow.

Some research has indicated that photic entrainment might be even more effective than the various kinds of aural entrainment (binaural, monaural, isochronic).

http://www.mindalive.com/articleone.htm (1/3rd of the way down, Frederick, Lubar, Rasey, Brim, & Blackburn, 1999)

My impressions from that study are that eyes-closed photic-only worked best for two reasons:

1. Closing the eyelids blocks out extraneous light which reduces interference. 2. No one knew how to properly combine the entrainment modalities yet.

However I believe that if a proper theoretical model is applied, AVE techniques might then become more effective, perhaps even more so if tactile audio were involved as well. http://en.wikipedia.org/wiki/Audio-visual_entrainment http://en.wikipedia.org/wiki/Tactile_sound

To me, a unit like the DK1 is not really usable for anything besides this sort of thing. After all, panning anywhere nearly as quickly as would be needed in a game on a DK1 would get most nauseated fairly quickly. (The DK2 is much better in this regard, and Crystal Cove hopefully even more so)

But the one saving grace for the DK1 was things done very slowly and deliberately, like a relaxed exploration of the Tuscany demo or something like this: http://guidedmeditationvr.com/

I've been looking for a good modern overview like this since I became interested in the OpenBCI project that finally has some devices shipping.

During my CS degree I wrote one paper with numerous citations from the field of neuroscience, as I was trying to make a case for ways to change the way we teach and learn so as to build more robust memory models of the things we are trying to memorize. The case I used in my paper was pieces of notated sheet music, but I believe the same principles could hold in areas like language learning (whether computer languages or human) or mathematics equally well.

I'd like to build/buy a good enough EEG to show that specific patterns emerge when we achieve the specific kind of focus that allows for this optimally efficient kind of learning to take place. (The implication being that if we are able to induce this type of brainwave pattern rather than expect the individual to achieve it on their own, then we might be able to make a significant step forward in the field of educational neuroscience).

http://en.wikipedia.org/wiki/Educational_neuroscience

I must admit I enjoy the (intentional?) typo of "Forward" rather than "Foreword". Forward!

Busted though, reading this specifically to review for a final CS exam in hardware/OSes.

This book might pair nicely with a current Coursera (which, yes, I'm also using to review for the final): https://www.coursera.org/course/hwswinterface