The original pre-print is available at: https://www.researchsquare.com/article/rs-3647379/v1 which is probably a less spammy source than the ResearchGate link.
What's wrong with Research Gate?
Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
11–20 of 59 posts
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#12> 460× less energy than digital computers 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
> and it has the best LLM
It takes many years to train it though
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#13Takes me back... There was significant hype around those things when they first managed to build them at scale (~15 years ago), because they were promising for low power, high density persistent storage and are also academically interesting: The "concept" of memristors was explored over 50 years ago (they are passive components that couple electrical charge and magnetical flux, just like a resistor does with current/…
Is that actually the case? Or have memristors just proven to be a 'boring' technology that's just quietly replaced other bits and pieces that we don't hear about? A bit like graphene was supposed to be this wonder material, and now it's found in the soles of trail and hiking boots.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#14> 460× less energy than digital computers 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
Nit: we take 20w of chemical energy not electrical one like computers, way worse efficiency compared to solar panels Id say
That's why the most efficient use of Superman would be to turn a giant crank generating energy
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#15> 460× less energy than digital computers 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
> and it has the best LLM It takes many years to train it though
And it's EoL after about 40 years too.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#16The original pre-print is available at: https://www.researchsquare.com/article/rs-3647379/v1 which is probably a less spammy source than the ResearchGate link.
What's wrong with Research Gate?
What value does it provide over linking to the original source?
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.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#17Earlier quoted context omitted.
What's wrong with Research Gate?
What value does it provide over linking to the original source? 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.
They also provide a central place to search things, with a richer interface than Google scholar, and have centralized a significant amount of good sources.
There's a reason millions of researchers have joined. That you don't find value or know what they provide is no reason others should not learn the value they add.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#18Takes me back... There was significant hype around those things when they first managed to build them at scale (~15 years ago), because they were promising for low power, high density persistent storage and are also academically interesting: The "concept" of memristors was explored over 50 years ago (they are passive components that couple electrical charge and magnetical flux, just like a resistor does with current/…
Is that actually the case? Or have memristors just proven to be a 'boring' technology that's just quietly replaced other bits and pieces that we don't hear about? A bit like graphene was supposed to be this wonder material, and now it's found in the soles of trail and hiking boots.
> Or have memristors just proven to be a 'boring' technology that's just quietly replaced other bits and pieces that we don't hear about?
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)
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#19The original pre-print is available at: https://www.researchsquare.com/article/rs-3647379/v1 which is probably a less spammy source than the ResearchGate link.
I'm surprised they chose Researchgate to publish their pre-print, instead of Arxiv
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#20Earlier quoted context omitted.
Nit: we take 20w of chemical energy not electrical one like computers, way worse efficiency compared to solar panels Id say
Our current society converts chemical energy to electrical, not the other way round. So its the electrical energy user that needs a lossy conversion step.
Fossil fuel plants are chemical -> heat -> mechanical -> electrical. The heat -> mechanical step is the inefficient one, sadly limited to ~40% efficiency even with very fancy machinery. Most other conversions can be above 90% efficient.