51–58 of 58 posts
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I think memristers are an HP thing. Intel's competing product is 3D cross point, which, according to marketing is a persistent memory technology that's higher density than DRAM and faster than flash.
There are a bunch of companies with memristor based products, HP is just the loudest about it.
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No, researchers use whatever is fastest for development and flexible. Otherwise we'd all be using neon.
i agree. development speed is more important. is there any benchmark that compares neon to other systems?
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Cars, especially the sort that will need to do self-driving, will have massive batteries in them. I'm talking about Roomba-sized devices where they can't power a full GPU worth of gear.
Where did you get the nonsensical idea that they are going to use desktop GPUs in cars? The board they specifically designed for self driving cars merely needs a few watts for 500 GFLOPS. Why would this not be suitable for a "Roomba-sized device"? https://m.f.ix.de/scale/geometry/1280/q50/imgs/18/1/6/4/4/6/...
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It really depends on how the market shapes up. You might see one software company rise to dominance where they interoperate with different platforms interchangeably, or you might see a single hardware vendor come to dominate a number of much smaller software vendors. NVidia is the horse to bet on now, but it remains to be seen how they can can expand beyond their current model of leaning heavily on their GPU technolo…
There's the Jetson boards, which are ARM + an NVidia GPU wrapped into one small package.
Also can't remember the last time I saw a USB port jammed on sideways.
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If Intel is smart they will invest heavily into library development. Researchers use whatever is fast and right now cuda is fast, not just because nvidia has the best GPUs (it's about even) but because the primitives in cuda are so much faster. Matrix multiplication on the same hardware is like 3x faster in cuda than opencl or competing libraries and using the neutral networking primitives is even faster. Intel needs…
I bought both NVIDIA and AMD. AMD has a big GPU patent portfolio as well. AMD trades at about 1/5th NVIDIA and could be a takeover target for a bigger player trying to move into AI. In my opinion NVIDIA needs a moat. CUDA is a good start but they need proprietary data that's hard to create. I thought they should buy Yahoo which would give them a large and unique data set that NVIDIA users could tie into through an AP…
NVIDIA needs to become more efficient and build deep learning hardware instead of graphics cards that do faster computation than CPU. If only they could create a small form AI processor for robotics that could do vision at 500+ frames per second. Take a look at this video from 7 years ago which does 1Khz vision: https://youtu.be/-KxjVlaLBmk?t=158
We need that.
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As someone who works in the semiconductor industry, I'm worried that joining an AI hardware company is a risky move that will falter just like General Magic and other hyped hardware startups.
Thankfully none of the major players are startups.
Hardware battle over AI platforms is heating up. Will be interesting if Intel can catch nvidia, or GPUs in general.
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>using memristors to compute artificial neural networks What does that mean?
That means memristors are used to store neural network weights, and a signal passing through a memristor would be effectively multiplied (scaled) by the weight value.