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Cerebras’ new monster AI chip adds 1.4T transistors

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Re: Cerebras’ new monster AI chip adds 1.4T transistors

#62

Earlier quoted context omitted.

It's very surprising what people with downvote power do but it's *** to downvote anyone that disagrees. Anyway expert systems were a precursor to the technology and they got replaced much like new physics replace old physics.

It's because you made a false analogy. AI isn't literally "the future". Billions of $ are being invested in deep-learning focused AI right now (which you call "the future"), and yes it could be a bubble and it could burst. You can disagree, but it's still a sensible thing to predict.

By bursting you mean humanity will never create artificial intelligence? Or you mean that there will be a cool off period as for example what happened with quantum physics at some point? Because it sure looks to me that there is no future without AI regardless of cool off periods. That makes my statement true. If you think humanity will never progress from where we are now then we pretty much are on very opposite schools of thought.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#63

Earlier quoted context omitted.

You do realize that AI crossed human expert performance in NLP / Vision tasks ?

Exactly how does one outperform a human expert in natural language processing?

Maybe the gibberish GPT-3 spits out is actually true, and our puny monke brains are just too weak to understand it.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#64
post #9

Earlier quoted context omitted.

They probably aren't bothering to. The extreme economics for producing this type of chip are likely acceptable to the stakeholders. Also, there is no reason they cant have some redundancy throughout the design so you can fuse off bad parts. It all really depends on the nature of the anticipated vs actual defects, which is an extraordinarily deep rabbit hole to climb into.

I wonder how much this "chip" costs!

According to Anandtech, an arm + leg. Also known as several million.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#67
post #18
post #9

Earlier quoted context omitted.

They probably aren't bothering to. The extreme economics for producing this type of chip are likely acceptable to the stakeholders. Also, there is no reason they cant have some redundancy throughout the design so you can fuse off bad parts. It all really depends on the nature of the anticipated vs actual defects, which is an extraordinarily deep rabbit hole to climb into.

How does this fusing work? I assume there are a bunch of wires than are either hot or ground and that determines if part of a chip gets run?

I believe you design special fuses on the chip that can be "blown" with a laser after testing and before putting the silicon in the protective packaging.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#68

Time for an AI winter I guess.

You do realize that AI crossed human expert performance in NLP / Vision tasks ?

GPT-3 is not even close to a minimal and coherent text adventure made with Inform6 from a novice, even if it's written by a non-native English speaker.

Those networks didn't match "Detective", a crappy story written by a 12yo.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#69
post #15

How do they do heat management and dissipation on such a big wafer? I can imagine some different parts heats up differently, putting a mechanical strain on wafer, and leading to cracks.

If you look at the die shots (wafer shots?), you'll notice small holes a few millimeters across spaced roughly at reticle spacing. Those are drilled holes to allow through-wafer liquid cooling. With liquid cooling not just around but through the wafer, the temperature differential is minimized.

Re: Cerebras’ new monster AI chip adds 1.4T transistors

#70

This thing needs a GraphBLAS[1] implementation yesterday. 100 billion edge graphs and up are the new norm. This monster could smoke the competition if the implementation was tuned right! [1] http://graphblas.org

Creating the ecosystem of both software and adjacent hardware for wafers this size is the real challenge for a company like Cerebras (which is doing amazing work). At first, they thought they just needed to make a chip 56x the size of its predecessor, and somehow get around the issue of defects and yield. After they solved those problems (which blocked Gene Amdahl, among others), they found they needed to bring an entire ecosystem into being to work with their hardware.
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