The rise of AI is creating new variety in the chip market, and trouble for Intel
1–10 of 58 posts
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#2The article is visible at first, but once the page loads entirely it disappears.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#3AI/ML/etc. may be part of it. But the other factor is that you can't just wait 18 months any longer for a new generation of x86 to be a lot [EDIT] faster. That was the big problem with specialized architectures historically. The volume architecture would catch up soon enough without you having to rewrite software to optimize for some different design of processor.
That's no longer the case so specialized designs for the compute-hungry workload du jour (which happens to be AI at the moment) are starting to look a lot more attractive.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#4The article is visible at first, but once the page loads entirely it disappears.
It happens to me too. I think it's The Economist's paywall in action. It's pretty annoying that this article is linkable but not-really on the web.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#5> Instead of making ASICS or FPGAs, Intel focused in recent years on making its CPU processors ever more powerful
If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation.
AI is not going to eat intel's lunch, all those computers still require cpus. AMD on the other hand may eat intel's lunch by releasing powerful multicore processors for half the price all because they don't waste space on the die for things like integrated graphics.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#6The article is visible at first, but once the page loads entirely it disappears.
It happens to me too. I think it's The Economist's paywall in action. It's pretty annoying that this article is linkable but not-really on the web.
That's a broken paywall, then. I'm on mobile, so not using any ad blocker, but there was no hint of explanation.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#7> Instead of making ASICS or FPGAs, Intel focused in recent years on making its CPU processors ever more powerful If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation. AI is not going to eat intel's lunch, all those computers still require cpus. AMD on the other hand may eat intel's lunch by releasing powerful multicor…
ASIC/FPGA or even GPU's aren't the future of neural computing. The future is analog(orders of magnitude perf/watt and perf/$). That require older fabs, optimized for analog, and having good embedded flash, which TSMC has and Intel mostly hasn't got.
And that same future applies not only for neural computing, but for a field called approximate-computing, i.e. computing where results aren't accurate.Some/many signal and image processing work well with that. I've also seen some research about doing scientific computing on approximate hardware and correcting errors.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#8> Instead of making ASICS or FPGAs, Intel focused in recent years on making its CPU processors ever more powerful If only, intel has been abusing their market position and pushing out "upgrades" that barely have a performance improvement over the previous generation. AI is not going to eat intel's lunch, all those computers still require cpus. AMD on the other hand may eat intel's lunch by releasing powerful multicor…
ASIC/FPGA or even GPU's aren't the future of neural computing. The future is analog(orders of magnitude perf/watt and perf/$). That require older fabs, optimized for analog, and having good embedded flash, which TSMC has and Intel mostly hasn't got. And that same future applies not only for neural computing, but for a field called approximate-computing, i.e. computing where results aren't accurate.Some/many signal an…
But analog computers do not permit error correction! Crosstalk of 10% does not affect digital data busses, but ruins analog. ECC memory is trivial with digital but not possible even in theory with analog. This (and programmability) is why we moved from super fast analog to slow digital half a century ago.
Given all these constraints I am actually quite excited to hear more of the dissenting view. Can you describe some of the research you mentioned in the last sentence? I have not heard of it and if true it would be at least interesting engineering, even if right now I doubt it would actually work.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#9Earlier quoted context omitted.
It happens to me too. I think it's The Economist's paywall in action. It's pretty annoying that this article is linkable but not-really on the web.
That's a broken paywall, then. I'm on mobile, so not using any ad blocker, but there was no hint of explanation.
I had the same thing happen, but it stayed open fine once I tried the link in incognito mode. Probably just a mis-coded "you've reached your article limit for the month" deal.
Re: The rise of AI is creating new variety in the chip market, and trouble for Intel
#10Earlier quoted context omitted.
ASIC/FPGA or even GPU's aren't the future of neural computing. The future is analog(orders of magnitude perf/watt and perf/$). That require older fabs, optimized for analog, and having good embedded flash, which TSMC has and Intel mostly hasn't got. And that same future applies not only for neural computing, but for a field called approximate-computing, i.e. computing where results aren't accurate.Some/many signal an…
But analog computers do not permit error correction! Crosstalk of 10% does not affect digital data busses, but ruins analog. ECC memory is trivial with digital but not possible even in theory with analog. This (and programmability) is why we moved from super fast analog to slow digital half a century ago. Given all these constraints I am actually quite excited to hear more of the dissenting view. Can you describe som…
A significant portion of any real-world AI system is dedicated to extracting relevant features from raw sensor information. Doing that digitally has proven to have a very high cost rated in both watts and operating temperature.
Most machine learning algorithms are by design resilient to random noise. They can even be learned to be resilient to systematic noise (due to say.. variable hardware performance in mass production).
In those cases; a low power analog device with lower reliability guarantees is 'ok'.
I suspect the "decision engines" (the computation enforcing complex logic based on sensor readings) will probably continue to be on CPU's for some time.