I remember 1998, Windows 98, monica lewinsky. Pentuim 4 processors, big fat pc monitors. The RnB song Too Close by Next.

the science is also just hype

Interesting, hadn't heard about this. Thanks for mentioning!

Not to mention maybe because diamond is a good insulator for electricity maybe it would help to control noise and drift

Very cool thought. I didn't even think of that. Those double bonds sure come in handy! Great job SimEon!@@SimEon-jt3sr

We've been using diamond for at least 10 years now at the macro level in avionics to control the heat. The ridiculous hardness and expense makes it extremely fiddly to work with. For instance, you cannot tune a coil in a filter even a tiny bit without first removing the diamond paste. 100% guaranteed to rip the pad right off your board.

We've also had diamond being used as detection medium in some particle physics detectors for awhile now

Thanks for going into details about this, I was wondering how it worked

She's corrected it in the notes

Sabine may have been thinking of earlier bipolar junction transistors, but modern digital electronics relies on unipolar voltage switched metal oxide semiconductors.

​@@Liberty4EverYou and Sabine have both used phrasing associated with distorted descriptions of popular transistor types used in microchips . Neither is the defining characteristic of semiconductor materials, merely what was built from them .

Not everyone is an engineer or a scientist here

Thank you for clarification re Tianjin...

don't get too hyped. Universities and tech groups have been finding new methods to speed up computers in the lab for 70 years. Just cos it works in the lab doesn't mean it will mass manufacturable and cheap enough to be market competitive. Only a small fraction of inovations in the lab make it to mass consumer market. Graphene + silicon carbide sounds too fiddly to use to produce billions of transistors per chip. Ok they got one working in the lab. Took manufactureres 50 years to go from one silicon transistor to 134billion per chip.

​@@plasmaastronautexcept now we have the manufacturing technology that we used to mass produce chips with billions of silicon transistors. If we can repurpose or reinovate some of those techniques and ideas, then it may not take 50 years before graphene replaces silicon.

It's Georgia Tech, not Georgia, and Republican politicians in Georgia work overtime to damage this world-class institution.

Yee haw buddy, we got dem darn transistors stackable no problem y’all.

Wherever there is a law, somebody tries to break it. 😂

Someone ask Florida Man . The answer may not be practical, but , it should be a hell of a show .

Well, Moore's law is dead. A new technology requires new laws in development. It will be a decade for the prototype, 5 years till production, 2 years to become profitable, 1 year until everybody and his dog know, how to make it "more efficient". So i expect this to be available to consumers in 20 years. And from this point onward, a new version of "Quantum-Moore's Law" COULD be applied. But i think, that's like "go faster" stripes on a car. They don't really make the car go faster.

Not to mention diamond is only expensive due to a monopoly/cartel. If diamond became the new oil, I'd imagine some heads would start rolling (perhaps literally) to dissolve it and reduce the artificially high cost.

​@@WhiteDragon103the diamond they'd use would almost certainly be lab grown, to ensure uniformity and impurity control.

Moore himself is now dead too .

​@@johndododoe1411💀💀💀

@@Ornithopter470 >almost certainly > i.e. there's a chance they won't what unlikely circumstances do u foresee whereby chip manufacturers would require natural diamond imported from African mines?

What became of the idea?

Also, early '90s Motorola was building chips vertically to increase surface area of gates to increase power levels, while conserving horizontal space.

And my comment is on the same topic. It seems like a certified quantum theoretical physicist can always say whatever he/she wants.

@@cavesalamander6308 Gates require a current even if only femto amps. Otherwise DRAM chips would be non-volatile ! Where do you think the charge goes ?

Luis Aldamiz Why you need to wait, how old are you ? Don't wait, that is never any productive, why you need quantum computing in the near future, are you able to emulate it now, run it on today hardware ?

@@lucasrem - WTF?! I don't think quantum computing will ever live to its promise, I'm very skeptical of all these pseudo-science passing as "science", "The Emperor's New Clothes" of our day, not just quantum computing but even more so like nuclear fusion. Now, said that, the challenge to make computers more efficient, either by extending Moore's Law with new materials like this one of by developing new approaches to computing, is probably important and I respect that. I'm 55, but when I say "we will have to wait" I mean "we" as Humanity, not you and me.

Very good. What kinds of dopants would you put into the graphene? What percentage of impurities would you put in to form the PN junction?

@@JoshtMoody That's the problem. Graphene's unique physical properties arise from its unique crystalline structure, not the carbon atoms themselves. You can't dope it without disrupting the structure.

​@@GoSlash27all dopants are imperfections that effect the structure, see boron-graphene and graphene oxide

Its not a semiconductor, it's a semi-metal

​@@eoingriffin3517half empty = half full?

It's now written in the errata. Thanks for your explanation!

Uhh... is increasing the power and heat while breaking CPUs into more parts really something to brag about? You do realize that what everyone was excited about not that long ago was being able to integrate more and more functionality into a smaller space while using less power. So of course some performance was being left on the table that we can "get back" if we are willing to push more power through and ditch some of the integration for separate parts. At the rate we're going, CPU manufacturers will have to stop integrating GPUs to get more die space, then they'll have to push more and more tasks off to the motherboard chipset, until finally maybe we wind up with separate physical dies for floating point and integer tasks...

@@jeremyandrews3292 Interesting thing to say because AMD is makes BY FAR the most power efficient chips at the moment, and they are using the chiplet design. (Though I have a Steam Deck which I think is a single chip and at the same time is the king in power efficiency so maybe the gains are elsewhere) So I don't think it's the case of pushing more power and more heat it's just having more transistors overall without huge risk of the whole unit having to be thrown away because of a single defect. Maybe there's some more compartmentalization on the chip into the chiplets and maybe even specialization but not to my limited knowledge, not yet anyway. Basically instead of doubling the ammount of transistors on a 4 squared cm chip they just double the ammount of transistors by making the chip bigger and they don't suffer from the single point faliure during manufacturing. That's what I'm thinking anyway

Splitting CPUs into chipsets. only helps with manufacturing costs. Although AMD has been desperately working to bring their experience in chiplet design to the GPU manofacturing, they have not been able to do so expect for the I/0 controllers part of the silicon, which does saves a lot of money, not having to spend engineering time shrinking the design of something that could be handled on a different chip. For now chiplet design has only been possible on the CPU manufacturing because it is easier for CPUs to run in parallel. The reason chiplet design reduces costs is that during lithorgraphy, printing errors are possible, having a monolithic die, means if you have a printing error, you wasted a lot of silicon. Also chiplet design allows modularity, so you can decide what to do with those chiplets better, do sell a lot of cheap 8 cores 8 threads CPUs or combine them to sell a 32 core 32 thread monster. Chiplets design does not help in keeping the Moor's law alive, problem here is, like. mentioned in the video, we are getting too close to the side of an atom, at those sizes we start to see quantum tunneling, so an electron can jump to the other side of a gate( the door turning off a transistor) there for preventing any computational calculation. Moor's law also stated that the number of transistors doubled every two years, yet the production costs were cut in half. And if we consider that second part, that's were Moor's law has been dead for years and years, the production costs have been getting more expensive each generation because is becoming harder and harder to print wafers, chiplet design helps a little bit to mitigate this but in no way allows manufacturing costs to be halved, same for 3D stacking, AMD has been experimenting and researching 3D stacking for years, but manufacturing is just too expensive. Single silicon atom, is 0.2 nanometers, hour chips are capable of 2, which is means have probably 3 generation before things fall apart unless 3D stacking becomes a thing. A different semiconductores is great, but to create the labs and machines to mass production and for engineers to figure out their designs that not only are equivalent in performance but are actually better at it, can take decades. So yeah Moor's Law is dead, and it has been for a while.

As 2 others essentially mentioned already, Moore's Law never addressed the doubling of speed by adding chips... it was solely speaking to the fact that things were getting smaller and faster. Of course, there is obviously a finite limit to this process so Moore must have known it wasn't really ever capable of being a "LAW"... only a temporary observation until we get to the point we've been at for the last 5-10 years now... SPEED INCREASES are almost non-existent and certainly nowhere near doubling every 2 years... Here's an article from 24 years ago (almost) that says Intel is claiming they are going to be the first to release a 1Ghz processor that year. (Obviously we don't have TERAHERTZ chips today... hell, we don't even have any 6Ghz chips available for retail purchase at anything close to affordable, barring insane overclocking and water cooling tricks): www.zdnet.com/article/1-ghz-intel-claims-it-was-first/

@@oohwha My point was that real performance still does follow roughly Moore's law despite the chips keeping about the same Ghz speed for many years now. Paralelizing is being properly used by virtually all applications now and the number of cores can be increased arbitrarily if you have chiplets (on a single chip you hit a wall where a single fault is so likely to occur on the chip to make it non-viable as a design) Stacking of cashe on top of the logic in the "3D" is apparently the thing to do now INSTEAD of just adding more cores because that's where the bottleneck is. If you had a 100Ghz single core CPU (which should be possible on Graphene actually) it would be nice for a VERY narrow usecase but for gaming (which is the driver for performance let's face it) the 3D chips with large and fast cashe would outperform it simply because of the memory read and write bottleneck. So you need to carry over the "anciliary" advancements which still follow the Moores Law in order to introduce the new technology anyway. That's why I would personally count these improvements in Moores Law especially because they roughly follow that rate of improvement of overall performance.

Apply gold so it has an atom supported by 2 nitrogen atoms on the hexagonal ring and 3 boron atoms on the ring above and you have a quantum transistor that can shift states by absorbing light using a phenomenon called tunneling. 😮

There is just so much momentum behind Silicon. The promise would have to be overwhelmingly amazing to blossom beyond niche applications into something a TSMC or Intel (or NewCo) would value enough to implement at scale. Moore’s Law is a technical law…that is really a law of economics.

It was really Chinese researchers at Tianjin University and Chinese researchers at Georgia Tech.

Yeah, what about a switch that can handle multiple signals at the same time wired into a 3D matrix? Oh, we already have human brains… Well if brains can do it, we can also do it!

Pardon the confession. That’s something like how I manage my telepathic network. But it’s 5D, at least.

@@andoreanesnomeo1706 5D gives much more bandwidth than 3D. 😊

Have you heard of the Anton supercomputer? It's quite a typical approach, to use 3D positioning to reduce routing.

@@vitalyl1327 I haven’t heard of the Anton super computer. I tried to get into super computers in grad school back in the 80s, but went into more theoretical approaches to physics. I think my brain was more like Dr Hossenfelders.

Go for it! If it excites you, then dump your effort into your passion! I have a PhD in accelerator physics from UCLA in 2014 and I love my job!

@@JoshtMoody thanks for the encouragement I appreciate it

Biology >> Physics

As someone who studied graphene in their PhD I would push you more toward gallium nitride and silicon carbide. Graphene is great in theory but even now there are only two industrial scale applications (these semiconductors and batteries). But if you find graphene interesting, go for it.

To pass my exam, I was in several groups with one person for a specific subject. We worked on a few problems in every section of upper level UG and beginning level grad books. We worked for a year. I worked separately to get my lower level class books and solved every homework problem in them. I still remember a couple where I never did solve them…

She needed to have a million members, then she could finance her experiments on superdeterminism.

Weirdly even the cheap ones you can do at home (like Technology Connections' flash graphene-reinforced polymers) don't seem to be common on shelves yet. Even in premium segments. Not sure what's up tbh

Thank you from the entire team!

We'll probably get a hell of a lot better if we can prove that graphene based computing is that much better. The problem with graphene isn't that we can't make it, it's that it's expensive to make a lot of it and so funding for research isn't super easy.

Radix-4 floating-point arithmetic can be done quicker than radix-2. Radix-60 arithmetic is more accurate than radix-2 in long computations.

Dr. John Gustafson, of Gustafson's Law, has published a book targeted at exactly this problem. Entitled The End of Error, it describes a new and better way to do floating point...or not do most of it, and far more efficiently.

Circuit optimization has been happening for 20+ years, as the fab cost have been increasing rapidly.

They're already having these problems, that's why we need a new material.

Georgia Tech has been an academic research powerhouse for almost as long as MIT has. It's not at all surprising if a technological breakthrough were to happen there.

@@johncate9541 Absolutely!

It was not just Georgia tech researchers. They were collaborating with researchers in Tianjin University in China. Funny how that got left out of the story

@@hdhdhshscbxhdh4195 And the fact that only the last three authors were from Georgia Tech, the first like 5 authors were all from Tianjin University.

GT has a 20% admit rate for undergrad, the most non-medical research expenditure of all US universities, and consistently is in the top 100 for world rankings. Not quite the same as if this came out of a state flagship.

The hype is not created by the things themselves, but by the University publicity departments. Arrrgh PR.

Arrays of those (barium strontium tantalate) were used in earlier thermal image devices. The sensor chips were incredibly well made. One was soaking in water inside the imager for over s decade and though the read out electronics were total scrap, the imaging chip itself still worked.😮 These were made by Raytheon and used in firefighter cameras, but the module itself was a surplus heat seeker camera module from the Gulf War. Go figure.

Ack, you're right of course! Sorry about that.

100% has not been promised, nor has any specific number. And no promises have been made for current AI systems. For example OpenAI made no claims about how chatGPT-3.5 could be used in businesses. Businesses realised it might be useful themselves and started testing it. OpenAI then responded by trying to make it easier for businesses to do this, but again made no claims about how good it would be (beyond "better" and stating that they hoped it could be used in the ways businesses wanted). The "promise" (which I mean in the sense of "shows promise" rather than the industry making such a promise) of AI is that it will continue to develop and improve, potentially very rapidly, and that these improvements will lead, in maybe 10-20 years, to massive reworks of many industries' operations. No one in the industry is under any delusions that today's AI should be able to revolutionise anything (though arguably it is already revolutionising protein research and drug discovery), so testing showing that it doesn't isn't surprising. The point is that AI seems to be progressing rapidly, so we need to prepare for the effects it may have. Not that those effects are already here. You're disproving a claim that the industry has not made. And as Sabine said, from prototype to full deployment is a very long path. It's been less than 18 months since AI fully entered the public conversation with the advent of chatGPT. And since then research and discoveries have exploded, not slowed as one would expect from something that is just hype.

Depends on the type of companies reporting. Recommendation systems are based on machine learning and falls under the AI category, and it has been significant for sites like Amazon and KZfaq.

Any single thing doing 5% is a lot IMO.