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Hydroponics and Aquaponics are two methods of sustainable agriculture that might just shape the future of agriculture.
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Intel Optane storage SSD cacheing
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD ,Intel, AMD
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Ryzen AMD
AMD Ryzen, Faster Memory, and the Infinity Fabric
AMD Ryzen AMD Ryzen AMD Ryzen AMD Ryzen AMD Ryzen AMD Ryzen AMD Ryzen AMD Ryzen
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following the initial release of AMD
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Rison there was a ton of discussion
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regards to using higher clocked system
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ram particularly in games the
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performance benefits of having higher
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clock memory was something that we
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didn’t necessarily see an Intel side
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it’s just not now the architecture is
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made it’s not made to benefit from
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higher clock memory but rise ins
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architecture is and that’s what I want
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to talk about in this video if it’s
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worth buying really expensive high clock
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RAM out of the box for the sake of a
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rise in CPU and a lot of the people who
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spend you know 400 bucks on an 1800 X
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are probably gonna buy a higher clock to
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rise in memory anyway at least a memory
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that’s capable of reaching 3000 or 3,200
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maker it’s on the rise in platform which
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is difficult to do we’ll talk about that
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as well but for those who are in the
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mid-range Rison five-tier should you
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still consider fast memory and why does
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it even matter in the first place I talk
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about all that in this video now when it
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comes down to it all rise in CPUs on a
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fabrication level are basically the same
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there are a few imperfections in some of
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the cores and that is ultimately
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differentiates a rise in three cpu from
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a rise in seven cpu so of the eight
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cores that are packed into every Rison
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chip no matter if you have a rise in
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three up to Horizon seven CPU if four of
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those aren’t doing too well then AMD is
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gonna just disable and they’re just
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gonna turn them off it’s better than
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making an entirely new fabrication
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process for a four core chip this way
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they can save money makes perfect sense
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I don’t blame them for doing that so a
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before remaining course if these can
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handle power loads pretty well and the
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the performance degradation isn’t too
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substantial then these might be arisin
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five 1400s or 1500 X’s if they aren’t
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doing too well with handling a lot of
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power and the schedulers aren’t doing
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that great a job at increasing the
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performance level then they might be
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rising three CPUs with multi-threading
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and disabled so it really comes down to
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what AMD deems as acceptable on both
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power delivery and execution levels now
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the difference between AMD and Intel
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because Intel does this too with bidding
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is that AMD decides well if these four
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cores aren’t going to cut it we’re gonna
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disable two of the cores in one cc X
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which is a four core cluster in a Rison
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CPU and two cores in the other CC X
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which is the other cluster of
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horizon CPU every rise in CPU has to CC
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x’s per die the red Ripper has four
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which is why you can get up to 16 cores
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in those CPUs maybe this diary shot will
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help explain things a bit better so if
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two cores are activated in one cc X and
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two are activated in the other there has
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to be some sort of efficient way for
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them both to communicate because these
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are essentially two separate dies they
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might not be that physically but each
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core cluster has an own set of resources
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including l3 cache which means that when
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you’re in especially intense situations
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on a computational level and they have
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to share information and process
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information simultaneously and exchange
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resources there has to be an efficient
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Highway a way for data to be transferred
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super quick between the cores to
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eliminate that latency this highway is
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called the Infinity fabric as Tom’s
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Hardware puts it the large amount of
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data flowing through this pathway
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requires a lot of scheduling magic to
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ensure a high quality of service it’s
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also logical to assume that these six
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and four core models benefit from less
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cross CCX traffic compared to the eight
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core models
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so they’re actually hinting at here is
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the dual CCX design is a blessing in a
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way and a curse it’s a blessing for AMD
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from a financial standpoint because all
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they have to do is slap multiple CC exes
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into the same chip and just run infinity
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fabric all between them which saves them
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money because they can control how many
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CC exes are in each dial without
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completely redoing the fabrication
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process but the curse involved is the
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latency involved between the CC X data
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transfers so the Infinity fabric itself
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is not the most efficient means by which
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data is transferred from one CC X to
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another this is where the faster memory
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comes into play it’s but this whole
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video is about why rise and benefits
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from faster memory we hear people say
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that maybe they don’t know what they’re
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talking about but they are correct in a
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sense it really depends on the number of
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cores enabled per cc X but ultimately
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Rison will benefit more from faster
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memory than Intel will and the reason
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why is because the Infinity fabrics
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speed this the rate at which it can
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transfer data is directly tied to the
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frequency of your system memory Intel is
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independent on the same variable because
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their consumer-grade CPUs are reliant on
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the ring bus design two rings share
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information between let’s say 4 cores
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and basically you have less traffic
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being dispatched between cores so the
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the congestion isn’t as great as it
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would be on an 8-core Rison cpu because
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then you have four cores trying to share
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information down let’s say a single
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pathway with the Infinity fabric so
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there can be quite a bit of congestion
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and lag I shouldn’t say lag it’s more or
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less a gamer term but latency it’s the
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delay in data transfer and we see a huge
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difference between the rain bus design
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with Intel a comparable Intel CPU and
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the Infinity fabric whereas cores on an
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i7 7 700 K rely on the latency roughly
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between 30 and 40 nanoseconds cross
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quartic or latency on a cc x-ray for
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Horizon is somewhere in the realm of 200
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nanoseconds almost 10 times the latency
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just because data has to be transferred
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across an infinity fabric not to be
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frank we’re talking nanoseconds here not
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even milliseconds but it does add up
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over time as huge computational
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workloads bottleneck that infinity
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fabric you can imagine how things get
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pretty backed up in the long run and you
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might even be able to tell a difference
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in things like games and also in render
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times if you do have heavy workloads
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being pushed to rise in CPUs they might
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not be able to handle them as well with
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that lower clocked system Ram so there
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you have it yes AMD rice and CPUs do
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benefit from higher clock memory it’s
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not a myth and the reason why is because
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AMD employs infinity fabric which is
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directly dependent on the speed of your
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RAM now getting too much into detail
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that’s really all you need to know
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something else worth noting is that rise
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in 3cp is because they only have two
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cores activated per CCX aren’t going to
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benefit as much from the higher clocked
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Ram only because the data transfer rates
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between CC X’s are going to be as high
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because only two cores per CC X are
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actually sending information whereas in
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horizon 7 1700 700 X or 800 X CPU get
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four cores on each side sending a ton of
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information things can get pretty
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congested in there for more info on this
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maybe you’d like to read an article
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about the Infinity fabric I invite you
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to check out the link at the top this
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video’s description sometimes it helps
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to just read something over and over
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until it clicks each it takes me 5 or 6
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times I’m like I’m like you’re bringing
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the sentence until till something clicks
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you get that light bulb go off now ok I
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get it now
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it’s harder to do that with a
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videocassette to keep hearing me say it
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over and over again it’s less annoying
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when you’re doing it yourself in your
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head and invite you to check that link
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out by the way it’s linked to Tom’s
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hardware and they have a great article
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breaking down the Infinity fabric and
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why it behaves the way it does also is a
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pretty cool benchmarks in there to back
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up the claims made in this video if you
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like this video be sure to give it a
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thumbs up I appreciate it thumbs down
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for the opposite click to subscribe but
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if you have any stay tuned for more
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content like this this is science studio
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thanks for learning with us
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[Music]
Quantum Computers Explained – What are Qubits
Quantum physics in and of itself is no simple subject. Explaining how a quantum computer works is no different. But this video’s here by popular demand. I hope you enjoy.
Trusty white board here. In order to understand quantum computing, we’ve gotta run through binary computing. 1s and 0s. Only two possible outcomes. We have transistors in on and off states to control the flow of voltage; basically closing and opening circuits like valves control the flow of water through pipes. It’s always easier to picture circuits in this way.
If the circuit is open, then no pathway exists and current (or, in this case, water) does not flow. But if the circuit is closed, the pathway is completed and water flows unhindered. Transistors are these “valves” or “on/off” switches. For binary systems, like the computers and phones you’re using to watch this video, binary transistors open and close to indicate 1 and 0. I explain it a bit more in this video right here. For now, just know that, if threshold voltage is not reached, a gap in the current is created indicating a “0 for FALSE.” Whether it’s a 1 or 0 really depends on the algorithm being used. They’ll always be opposites. For our examples in this video, 1 = True = closed circuit, and 0 = False = open circuit.
This is how all data in modern computing systems is transmitted and processed. And you can imagine how billions of transistors opening and closing at billions of times per second can amount to some serious data computation. But quantum computers make PCs like this one behind me seem like basic calculators. They aren’t binary systems per se, although we often use 1 and 0 to denote the range of values quantum bits, or “qubits” can denote.
In a nutshell, “quantum,” in the term “quantum mechanics” defines the energy levels of small particles. And thanks to research done by Werner Heisenberg, Serge Haroche, and David Wineland, we now know that it also describes how an electron can be in two places at once. This is from where quantum computing is derived.
Instead of 1s and 0s, regular bits, qubits can represent an infinite range of values between 1 and 0. And unlike the classical counterpart, qubits can be physical objects like electrons and photons. Imagine a compass with one pole denoted 1 and the other pole denoted 0. The needle of the compass can swing wherever it wants within the system – but it can never point to anything higher than one and lower than zero. Instead, it can point to areas in-between the two poles and represent the likelihood of either becoming a 1 or 0 once the qubit is processed. This area in-between is what’s known as “superposition.”
When we read and interpret classical three-bit binary data streams, we understand that eight outcomes are possible. Since there are two possible states and 3 bits, 2 raised to n (where n is 3) = 8. So eight possible outcomes here; all probabilities of which must equal 1. So there’s a 100% chance that a three-bit binary system will yield one of these values (since they’re the only values possible with three digits and two numbers).
A quantum three-bit system works a bit different, however. Since each qubit can denote any complex number between 0 and 1, then the sum of the squares of each complex probability must equal 1 for a 100% probability. When we make a measurement of a 3-bit quantum system, the values of the particles in each orientation collapse to a classical state of binary. But the computational power of a three-bit quantum computer far-exceeds that of classical systems. Where binary systems require 2 raised to the power N bits, quantum computers can express the same amount of information in just N qubits.
For scale, just a 30-bit computer is capable of nearly 10 teraflops of floating point performance. That’s 10 trillion floating operations per second which, in the real world, would require billions of transistors.
But like I said in this video right here, quantum computers aren’t as practical for every-day users as you might think. Streaming, editing, and even gaming won’t benefit much from quantum PCs in the current state; and they get extremely hot. They have to be cryogenically cooled. They must also be shielded from the outside world, since even the smallest magnetic disturbances can offset a qubit’s reading and promote decoherence. They’re extremely large, expensive, and difficult to maintain, and are more-or-less used for large probability and research operations today.
The viability of these quantum computers will change as our technology and infrastructure does, but I expect we’ll still be relying on the binary system for many years to come. They just work. We don’t have to worry about quantum decoherence, overheating, and insane shielding. But much like early binary computers, quantum computers today are very large. Who knows? In fifty years, we may have shrunken an entire system to the size of this. If we had enough computational qubits in this as we do classical transistors, imagine the potential.