Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
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Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#2But 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).
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#3Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#4Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#5Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#6Takes 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/…
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.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#7The 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
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#8which is probably a less spammy source than the ResearchGate link.
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#9> 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
Re: Linear, symmetric, self-selecting 14-bit molecular memristors (2023)
#10> 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