I've been working on AR and related technologies for almost the last decade and I've been part of the first handful of people working on Google Glass. Bottom line I've seen a lot of promising AR technologies come and go. My personal take on this is that they may indeed have some very good, if not revolutionary, display technology. However : The big, big obstacle to delivering credible AR is latency. Contrary to VR, t…
The first iteration of a good AR system could simply sidestep the latency issue by embracing layers. Magic Leap should skip the fancy stuff (mixing virtual scenes with real), at least at first, and focus the many other useful features of a great head-mounted display system - think mobile notifications, video calls, web browser, etc. It could easily replace smart watches and later cell phones and computer monitors wit…
Magic Leap raises $827M in Series C
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Re: Magic Leap raises $827M in Series C
#152Glaciers are melting; forests are burning; coral reefs are blanching; ocean levels are rising, water tables are dropping. The ecosystems that sustain our food supply chains are collapsing; those that aren't collapsing, are being poisoned; and the tiny niches relatively immune from these threats are being bought by hedge funds and private equity firms. Our education system is being gutted; so are our retirement plans.…
Re: Magic Leap raises $827M in Series C
#153Earlier quoted context omitted.
Training an ANN is computationally intensive, using a trained ANN is not. No context switching for system calls, no memory management, just matrix math.
well, first you need to know what image regions feed to ANN, and that can involve some segmentation and pre-recognition, otherwise you're going to evaluate the net at all feasible subwindows — and that's a LOT of matrix math for you. Very big GPU can help, but they have latency in themselves, and FPGA at such performance levels are inordinately expensive. Done at scale though ASICs seem to be the sure-to-work way.
I remember reading a while ago about how smart tvs were using ANNs for upscaling, so it has been done at scale. rimshot
Re: Magic Leap raises $827M in Series C
#154Earlier quoted context omitted.
No. The important thing is keeping your sensory inputs in sync with your vestibular system. There were some research questions about hacking the vestibular system a few years ago.
rsp1984 says that what seperates AR from VR is the need to have latencies zipppy says "what if AR was delayed 15ms to make it equiv. to VR". Zipppy's intent was to make AR compete with VR, not HVS.
Because we have the head tracker recent history, we use prediction on pose trajectory, and can effectively know where the head pose will be at the time the current rendered frame will be displayed. And use that predicted pose to render the scene. That type of optimization won't be possible with see-through VR or AR.
The second optimization is timewarp, where the rendered scene is distorted in screen space after the fact, based on post-render tracker data (just a few ms before display). I wonder if that type of optimization would create artifacts in AR.
Re: Magic Leap raises $827M in Series C
#155Earlier quoted context omitted.
The 10-15ms motion-to-photon latency is pretty vital in VR too so that users don't get sick.
It's a spectrum, but VR can do with more like 50 and be very good.
Re: Magic Leap raises $827M in Series C
#156Earlier quoted context omitted.
Oculus got acquired without having released a product to be fair, and that looks like a phenomenal acquisition. By the way, how good has Facebook been at acquisitions? Instagram alone has already paid off in gains all the total dollars spent, and they also have WhatsApp and Oculus which are both huge, important "companies". Good for Zuck.
The DK1 was already available when they got acquired.
Re: Magic Leap raises $827M in Series C
#157Earlier quoted context omitted.
Definitely true (the Segway is a great example of this), but I've also talked to people who were involved in developing the technology academically and have studied their patents in-depth, and I'm pretty certain they're the real deal.
Recently on the voices of vr podcast, Dr. Thomas Furness mentioned that he also tried it, and it was based off his (Human Interface Technology Lab)'s virtual retinal display technology/patent. I'm guessing this is what you're referring to?
Re: Magic Leap raises $827M in Series C
#158Earlier quoted context omitted.
Along these lines - is there an example of a technology company that succeeded after raising so much money without proving their product in the market?
Screw the market. Personally, I don't care if this even sells (to make the general population buy it, they'll have to invent most silly possible applications imaginable). The question is - does it really work as advertised? Both Magic Leap and HoloLens look way beyond the state-of-the-art, I'm still not convinced that what they show us isn't just plain marketing fabrication.
Re: Magic Leap raises $827M in Series C
#159Glaciers are melting; forests are burning; coral reefs are blanching; ocean levels are rising, water tables are dropping. The ecosystems that sustain our food supply chains are collapsing; those that aren't collapsing, are being poisoned; and the tiny niches relatively immune from these threats are being bought by hedge funds and private equity firms. Our education system is being gutted; so are our retirement plans.…
I think AR and VR along with lab grown animal protein of multiple varieties will reverse a tremendous amount of our planetary fleecing. This vision is at least 20+ years away ,but it is definitely a good answer to many of our problems.
Re: Magic Leap raises $827M in Series C
#160Earlier quoted context omitted.
well, first you need to know what image regions feed to ANN, and that can involve some segmentation and pre-recognition, otherwise you're going to evaluate the net at all feasible subwindows — and that's a LOT of matrix math for you. Very big GPU can help, but they have latency in themselves, and FPGA at such performance levels are inordinately expensive. Done at scale though ASICs seem to be the sure-to-work way.
I'd be very surprised if a modern cpu couldn't handle the task, especially if you were clever about detecting regions of interest, predicting head movement and cache maintenance. But I'd also be surprised if they go to market with an x86 under the hood. I remember reading a while ago about how smart tvs were using ANNs for upscaling, so it has been done at scale. rimshot
(2) Upscaling ANNs process rather small image neighborhood radius, and required processing power is on the order of O(r² * log r), and if a minimally recognizable cat is 50x50 px and for upscale you use a very large window of 16x16, that's 14 times already.