But I think the main problem was that they never managed to scale up the clock speeds sufficiently, even though structure size (=> density) was already highly promising from the start.
Maybe in a slightly different history with some discoveries in different orders these could have replaced flash memory in SSDs completely.
But that whole episode thought me that betting on early technology is hard, and always a risky business, because no matter how promising an approach looks, if it turns out that you can not find the necessary improvements in only a single dimension, then the whole thing is kinda doomed and will probably never be competitive (=> a highly relevant insight especially when speculating about things like novel battery chemistries or the like).
I don't know, we've been working on digital computers since at least the late 1800s. Sometimes technology just takes a while.
That does make it hard to gamble on it if the time horizon is longer than you need to make a profit.
But I don't think we should convince ourselves that a technology that takes longer than 15 years to become profitable is doomed. If we thought like that we'd still be subsistence hunter gatherers.
My point is just that even with research-tech that sounds absolutely amazing (low power, persistent, high density) you just need to fail on a single dimension for it to basically become irrelevant.
This is also why its so easy for media to overhype research results, which (predictably) results in continuous disappointments and loss of trust (of the public) in science reporting and/or even science in general...
- The effect first discovered: 1907.
- First prototype device built: 1927.
- First commercially viable parts shipping: early 1960s.
- Ubiquitous and cheap as an indicator device: 1980s.
- Highly efficient, used for lighting: 2010s.
The principle never changed along the way. The specific materials changed quite a bit.
> To address the challenge of EUV lithography, researchers at Lawrence Livermore National Laboratory, Lawrence Berkeley National Laboratory, and Sandia National Laboratories were funded in the 1990s to perform basic research into the technical obstacles. The results of this successful effort were disseminated via a public/private partnership Cooperative R&D Agreement (CRADA) with the invention and rights wholly owned by the US government, but licensed and distributed under approval by DOE and Congress.[3] The CRADA consisted of a consortium of private companies and the Labs, manifested as an entity called the Extreme Ultraviolet Limited Liability Company (EUV LLC).[4]
> Intel, Canon, and Nikon (leaders in the field at the time), as well as the Dutch company ASML and Silicon Valley Group (SVG) all sought licensing. Congress denied[citation needed] the Japanese companies the necessary permission, as they were perceived[by whom?] as strong technical competitors at the time and should not benefit from taxpayer-funded research at the expense of American companies.[5] In 2001 SVG was acquired by ASML, leaving ASML as the sole benefactor of the critical technology.[6]
>By 2018, ASML succeeded in deploying the intellectual property from the EUV-LLC after several decades of developmental research
As far as I know, they have no application apart from academic toy/reseearch subject right now. And you have to consider that there are a lot of niches for storage technology that they could have taken over (because there is a lot of tradeoffs to make, e.g. latency, bandwidth, persistence, density, power consumption).
We might be just a few breakthoughs from those things replacing flash memory in SSDs, or revolutionizing neural-network accelerator hardware, but I am quite skeptical for now.
Note: I still believe that this (and other stuff i'm skeptical about) is SUPER worthwhile to research and always a huge uphill battle, simply because we have invested hundreds of billions of dollars into improvements of CMOS technology and processes, and collected over half a century of experience with it...
But new tech is to me kinda like a startup-- not every technology is the future, just like not every startup is a unicorn. Investing is still the right move, but you have to be realistic about expectations (which modern media is absolutely not)
I mean, that's not because graphene has become a routine part of our material repertoire. It has no reason to be in those things, does nothing, and is just marketing fuel. We may put "graphene" in things, but we are not much closer to using its interesting properties.
Those things where hyped out of nowhere, with lots of blatant lies making into the popular discourse (like that high-density prediction). I don't even know why, because nobody was making any serious bet on them. They are a very interesting design, that may still get some real-world usage (the manufacturing problems are a showstopper right now), but won't ever compete with flash.
Of course, then the question becomes one of refreshing their state, like DRAM.
That said, I think this is something a bit different, or at least a different application. If my translation of the summary is correct (I'm not very fluent in sciencese), it's basically using them as some kind of matrix multiplier rather than memory. Whether they're making use of power-off data retention at all was unclear to me, but then I just skimmed it.
Interesting, but I was really hoping for fast, persistent memory to appear.
The brain is running on 20W of power and it has the best LLM, the best robotics control unit, very good sensor integration and all the other exciting stuff which we* want** AIs to have. I'd rather have that than nuclear powerplants feeding data centers.
* overreaching a bit
** also not really true for everyone
It takes many years to train it though
Now you know why you always see new doctors
What's even more shocking is that conversion of food to energy period is ~90% efficient, which is crazy to me. The fact that you can burn food and measure the energy given off, and that's very close to how much energy you get from eating it- that's insane.
The efficiency of the human body is all over the place. Muscles are only ~30% efficient, and the rest is waste heat... but humans walk using orders of magnitude less power than any walking robot. As far as I know we have never made a powered walking machine that is 10% as efficient as a person. The only way we can beat it is with a carefully balanced, specially-lubricated pair of legs that is leaned downhill on a treadmill and powered by gravity.
which is probably a less spammy source than the ResearchGate link.
Any website that constantly asks me to login is spammy in by book. It's a for profit website that adds little value other than duplicating information from primary sources and occasionally mangling pdfs with redundant information to advertise themselves.
