George Gilder simply reached an enormous viewers with an concept that may sound acquainted to you.
In a latest Wall Avenue Journal essay, he argued that the age of the microchip — the very know-how that constructed Silicon Valley — is coming to an finish.
Now, if you happen to don’t know George like I do, this may sound like utter nonsense.
However for many years, he’s been forward of the curve on calls like this.
George predicted the rise of the web lengthy earlier than Wall Avenue did. He warned Invoice Gates that internet browsers would upend Microsoft’s software program monopoly. He even foresaw a brand new computing universe based mostly not on quicker chips however on infinite bandwidth, lengthy earlier than most individuals thought it doable.
Now he’s doing it once more. And this time, hundreds of thousands of Wall Avenue Journal readers bought a glimpse of what we’ve been speaking about for months…
What simply could be the subsequent massive leap in computing.
A Pc the Measurement of a Dinner Plate
In his WSJ essay, George argued that the microchip continues to be extraordinarily essential to the U.S.
The U.S. authorities considers chips very important and strategic. The 2022 Chips Act approved greater than $200 billion to assist chip fabrication within the U.S. and hold it away from China. Microchips form U.S. international coverage from the Netherlands, residence of ASML, the No. 1 maker of chip-fabrication instruments, to Taiwan and its prodigious Taiwan Semiconductor Manufacturing Co.
However he additionally notes that the microchip’s design hasn’t modified a lot for the reason that Nineteen Seventies.
Engineers nonetheless carve a silicon wafer into tons of of smaller chips, bundle them individually and wire them collectively inside knowledge facilities.
That system has labored for half a century. Nevertheless it’s hitting its limits.
That’s why George and I are so enthusiastic about wafer-scale chips.
Picture: Cerebras
These revolutionary single-wafer computer systems flip the previous microchip mannequin on its head. As a substitute of slicing the wafer, the entire disk turns into one huge processor. Each transistor stays related on a single floor, letting knowledge transfer at lightning velocity.
It’s like a pc with out borders…
One large piece of silicon the place reminiscence, logic and communication all dwell collectively.
That’s the imaginative and prescient behind corporations like Cerebras Techniques, which builds 12-inch wafer-scale processors holding 2.6 trillion transistors and 850,000 AI cores. The Division of Vitality has been utilizing them for nuclear fusion analysis and superior physics simulations.
And as George and I mentioned just lately, it’s additionally what Tesla applied with its Dojo supercomputer, a custom-built AI coaching system utilizing wafer-scale tiles to coach autonomous-driving fashions.
That idea lives on in Tesla’s upcoming AI6 unified AI chip.
And George believes this sort of structure will finally change the microchips that dominate AI computing right now.
I agree with him. At the least in the long term. However for now, the fact is that wafer-scale chips have limits too.
They’ll deal with AI fashions with as much as about 100 billion parameters. That’s spectacular, however far smaller than one thing like ChatGPT, which runs on 1.8 trillion parameters. And it’s because wafer-scale chips can’t but pack sufficient reminiscence near the processor.
There’s additionally the problem of scale.
Conventional GPUs are made in batches. If one chip is flawed, you toss it and transfer on.
However a wafer-scale processor is one huge piece of silicon. One tiny flaw can destroy the whole system.
That’s why these methods are largely being utilized in specialised analysis environments for now.
As I instructed my crew final week, you possibly can completely use wafer-scale chips for particular, high-performance workloads right now. However not for full-scale cloud operations.
Not but, a minimum of.
However George has a approach of recognizing the place the puck goes earlier than anybody else sees it. And if you happen to take a look at historical past, most of his “too early” calls find yourself being proper on time a couple of years later.
I additionally agree with Geroge that the U.S. must cleared the path in what he calls “the post-microchip period.”
However as he warns within the WSJ piece:
By slicing off the Chinese language chip market, which incorporates nearly all of semiconductor engineers, U.S. industrial insurance policies have hampered American producers of wafer-fabrication tools—important for making chips—with out slowing China’s ascent. Within the wake of those protectionist insurance policies, launched round 2020, Chinese language semiconductor capital tools manufacturing has risen by 30% to 40% yearly, in contrast with annual development of about 10% within the U.S.
The paradox George is pointing to is what issues each of us. America invented the microchip, but we danger falling behind within the race to construct what comes after it.
As a result of wafer-scale computing isn’t simply one other technology of {hardware}. It represents a deeper shift in how intelligence and business will join sooner or later.
That’s what George and I imply after we discuss “Convergence X.”
It’s the second when AI, superior manufacturing and power methods cease evolving in separate lanes and begin merging into one unified ecosystem.
And wafer-scale structure is a path that may make this future doable.
These new processors blur the road between chip and pc. They transfer knowledge virtually immediately throughout a single floor. And so they can practice fashions domestically with out counting on cloud knowledge facilities midway all over the world.
In different phrases, they bring about intelligence nearer to the place issues are made.
That’s a giant issue of Convergence X: placing the “mind” of the digital world contained in the machines, factories and energy methods that drive the bodily world.
And you may already see it taking form throughout the U.S.
Whether or not with Intel’s new “Silicon Heartland” factories in Ohio, or TSMC’s superior facility rising from the Arizona desert, or Tesla’s Dojo supercomputer, constructed to coach hundreds of thousands of autonomous autos concurrently.
Every one is a component of a bigger sample.
It’s about bringing intelligence residence, embedding it instantly into manufacturing and lowering America’s dependence on international provide chains.
Right here’s My Take
Wafer-scale integration isn’t prepared to exchange the information facilities that energy right now’s AI fairly but.
However though George could be barely early, he’s not flawed.
When wafer-scale methods lastly overcome their manufacturing limits, complete server farms might shrink to the dimensions of a single disk.
Which means, the longer term he’s describing could possibly be simply across the nook.
Regards,
Ian KingChief Strategist, Banyan Hill Publishing
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