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Taalas will be one of the great disaster investments of the early AI era. It'll be a near total write-down.

The absolute worst market time to etch a model to a chip is right now (very rapid iteration). There is no scenario where they can keep up. The Taalas approach will be viewed as comically foolish within just a few years.

Cerebras will win in terms of approach.

It's 1998: hey, I can drastically speed up your web service, let's etch it right to silicon.

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I would still pay ~500 for a chip that runs 10kt/s of a ~100b model on my machine even if the half life is 6months. I m sure my employer would too.

Qwwen3.5 122b was released 6 months ago and is still best in class overall 100-140 B param model.

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> I would still pay ~500 for a chip that runs 10kt/s of a ~100b model on my machine even if the half life is 6months.

....

:T

Considering the 8B model uses 53 billion transistors, that's 6.625 transistors per parameter.

https://taalas.com/products/

Assuming they can get it down to 3 (somehow), that's still 300 transistors, or 5.565 RX 9070s.

https://www.techpowerup.com/gpu-specs/radeon-rx-9070.c4250

You're looking at

1) waiting for another 3-5 generations of transistor improvements before it can fit into a single conventional chip, or

2) another generation before getting a monster of a chip (1000+ mm^2), and prices for flawless etching scale quadraticly (likely $1000+ for manufacturing costs alone).

Could happen, but it's a long shot for a market that could be satiated by specialized accelerators.

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In Taalas HC2 a chip embeds 20b parameters, and the declared idea is linking the chips. A card with two of them chips and you can already have a dense Qwen at staggering speeds.
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500 what? You’re missing the unit
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> The absolute worst market time to etch a model to a chip is right now

Slightly disagree. It really depends on the price-point at which they can do that etching. ~1k usd / ~30B model in a hdd-sized case that fits on your desk? I'd buy one right now, even knowing that I'm "stuck" with whatever model of the day is.

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Time to market also matters a ton. If they can start shipping chips <1 month after the weights drop that's much more compelling than if it's a 6+ month development pipeline.
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In the case of Taalas, the pipeline was said to be 2 months:

> From the moment a previously unseen model is received, it can be realized in hardware in only two months ( https://taalas.com/the-path-to-ubiquitous-ai/ )

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> It's 1998: hey, I can drastically speed up your web service, let's etch it right to silicon.

I distinctly remember 32-bit/33 MHz PCI accelerator cards for SSL being a real thing (for use on OpenBSD or FreeBSD), in an era when something like a single core 700 MHz Pentium 3 1U system was a relatively powerful individual bare metal httpd box.

http://www.aster.si/partnerji/compaq/atalla/axl200.html

The CPU load of doing a lot of SSL purely in software was a problem in terms of scaling things up, so this was one attempt at a (very short lived) solution. Note that this predated TLS1.0.

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The 500x efficiency gain makes their approach a no brainer. Just make a new chip every 6 months, you still win.
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I just want to but hardware so I can run a model at home that is fast. I don't see myself installing a server that burns almost two hundred kilowatts but maybe a card which runs a 27B Qwen...
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At 250w when it's working (I understand), and it works for tiny amounts of time per query...
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maybe AMD wants the IP to deploy it once ai model development slows down in a few years. Or, their large cloud customers do want to burn through silicon, basically paying rent to AMD for models etched on silicon.
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It's 2026: let's etch nginx into silicon and get 10,000,000 rps at a cost of 0.1 US/day.

Yes, please!

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Most people probably don't care about nginx performance. It shouldn't be your bottleneck unless you serve massive amounts of static data.
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In the case of needs to process natural language, instead, massive efficiency (esp. time) can be a game changer. It's like "you have two years to complete the project" vs "you have two hours to complete the project": if you can squeeze that "two years worth" into a negligible delay, it's a game changer.
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Ok, how about postgres?
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Etched model into a chip? A… mobile chip eventually? Seems prescient.
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