Both Meta & Microsoft have said they're shedding staff explicitly to free up cash flow to invest in AI;
-
Yes. I've mentioned this before, but US foreign policy is heavily biased towards US big tech and cross-border data transfers to the degree that it's becoming a geopolitical tool akin to hosting US military bases.
@ReggieHere @HarriettMB @ChrisMayLA6
Nice analogy
-
@HarriettMB @TCatInReality @ChrisMayLA6 @ReggieHere our coward new (last year) banker-prime-minister cancelled the DST (it’s Canada). What have we gained from it a year after? Austerity. More threats from the Orange shitstain.
@hub @HarriettMB @ChrisMayLA6 @ReggieHere
Time to bring back the tax then
-
@graydon @david_chisnall @linuxgnome @ChrisMayLA6 More to the point: the end is in sight for the annual gains Moore's Law accustomed everybody to—you can't build circuits smaller than atomic orbitals—but it has run for over 40 years, so everybody in a decision-making position has grown up expecting it to continue. Not so much in semiconductors, but everyone *else*: VCs, PE firms, software, the general public.
The cluetrain is bound to run off the track and derail in an unploughed field.
@cstross @graydon @linuxgnome @ChrisMayLA6
Well, kind of. Moore's law is about the size of IC you can build assuming a fixed investment (the latter isn't explicitly stated in the law, but it is an underlying assumption in the paper. Increases in yield contribute as well, as do more mature processes coming down in price over time. So do things like 3D stacking and chiplets (chiplets, in particular, let you build smaller chips and get the yield benefits, but assemble them into more complex complete chips).
Moore's second law is a bit more relevant because it discusses the doubling of fab costs for each new process node. That's predicated on making enough money from the previous generation to justify the investment. That's why we've seen so much consolidation: you need enormous economies of scale to be able to afford the R&D costs. Once you hit 'good enough' performance for 90% of use cases, funding the R&D for the next process out of the 10% that needs the higher performance is hard, if not impossible. Once you reach 99%, it's definitely impossible.
Somewhere, I have a copy of the issue of BYTE where the cover story is the new 1nm process (note: nm, not µm). It confidently predicts the end of Moore's Law within a little over a decade.
We hit the end of Dennard Scaling around 2007 and that was a far bigger shock than slowing of Moore's Law. Prior to that, shrinking a die had given you a commensurate decrease in leakage current. Your clock frequency is determined by the signal propagation delay (one clock cycle at the maximum frequency supported by the part is the time taken for a signal to propagate along the critical path). As you make transistors smaller, the amount of stuff you can do in one cycle is much more because you can fit more logic in.
This is how we're able to run our first test chip at 512 MHz on a 22nm process, even though it's a microcontroller with a three-stage pipeline, whereas Intel needed five stages (and a lot of engineering work) to break 100 MHz with the 800nm process.
But back prior to around 2007, that increase in clock speeds came for free with respect to power. With newer processes, the leakage current is higher and that means that you need to increase the voltage more to increase the clock speed. And that is what gives us power problems.
There are a few interesting experimental processes that look like they might get back to much lower leakage, which would allow chips of similar sizes to todays to run at hundreds of GHz in the same power budget, if they work. We've had some initial discussions with some folks who built a small fab around one of these. That has no impact on Moore's First Law as it's actually written, but it would have a big impact on the common informal understanding of Moore's Law.
-
@TCatInReality @HarriettMB @ChrisMayLA6 the machines will decide for us. Obviously.
@mgleadow @HarriettMB @ChrisMayLA6
Early tests show AI making some very dangerous decisions
King's study finds AI chose nuclear signalling in 95% of simulated crises | King's College London
Artificial intelligence (AI) models used for a simulated war game escalated conflicts by threatening nuclear strikes in 95% of scenarios, according to new research from King’s College London.
King's College London (www.kcl.ac.uk)
-
I think the final post may be right - one last throw of the dice in a bid to avoid a 'correction' in their share price (see the warning today from the BoE about UK share prices, which is just as applicable to US ones, in my view)
@ChrisMayLA6 yes, I have seen today an economist talk about the Wile E Coyote effect (in relation to the Iran war and the oil crisis). People seem to want to have their stock market party go on forever, decoupling it from annoying reality.
But in the end, forecasting is hard, especially when it is about the future
. A tech bubble burst has been predicted several times already. The monopoly position of those companies does give them remarkable resilience... -
@cstross TSMC is working on going from 3 nm to 2 nm fabrication.
On the one hand, that's a big change, percentage-wise.
On the other hand, only TSMC is doing this because the entire world economy can afford at most one fab.
On the third hand, it's not clear there's any actual advantage to making the change. There's almost certainly better things to do with that money. But line must more tinyness! is built into the whole process.
@graydon @cstross @david_chisnall @linuxgnome @ChrisMayLA6 The percentage is only in marketing. There are only small improvements in power, performance, etc (like 10-15%) but with a doubling in mask costs. SRAMs and wires are not scaling and logic gates are no longer getting any cheaper to print.
-
@mdm @graydon @david_chisnall @linuxgnome @ChrisMayLA6 Well you *can* if you use muons instead of electrons but then you have to do your computing inside a particle accelerator and everything is radioactive and on fire
@cstross that almost feels like an improvement after /wave at all of this
-
@graydon @david_chisnall @linuxgnome @ChrisMayLA6 More to the point: the end is in sight for the annual gains Moore's Law accustomed everybody to—you can't build circuits smaller than atomic orbitals—but it has run for over 40 years, so everybody in a decision-making position has grown up expecting it to continue. Not so much in semiconductors, but everyone *else*: VCs, PE firms, software, the general public.
The cluetrain is bound to run off the track and derail in an unploughed field.
@cstross
fortunately, *various new developments* in computing have really focused minds on efficient computation and elegant algorithmic solutions... -
@beemoh @linuxgnome @ChrisMayLA6
It's a weird thing because Microsoft made a really nice mobile GUI, and then rolled it into a desktop OS where it made no sense and everyone hated it. As a result, everyone also hated Windows Phone because they thought the UI would be as bad on the phone.
It's a weird product where everyone I know who actually used it loved it, but everyone else hated it.
-
@graydon @david_chisnall @linuxgnome @ChrisMayLA6
The logical end-point after the node size bottoms out is going to be for the inherent deflation to become evident—fabs get amortized over time, so the product stops being premium and becomes a cash cow, and prices have to drop.
Nvidia can't survive that. Intel can't survive that. They need something like the AI hyperscalers to keep demand high, but the demand is artificial, and actual consumer demand is soft if not soggy.
Crash is inevitable.
@cstross @graydon @david_chisnall @linuxgnome @ChrisMayLA6
An AI crash will absolutely happen, just like the Internet crash happened in 2001!
Right now, the game is to position yourself as the Google or Amazon of AI, not the Excite or Pets.com
-
@graydon @cstross @david_chisnall @linuxgnome @ChrisMayLA6 The percentage is only in marketing. There are only small improvements in power, performance, etc (like 10-15%) but with a doubling in mask costs. SRAMs and wires are not scaling and logic gates are no longer getting any cheaper to print.
@kurtmrufa @graydon @cstross @david_chisnall @linuxgnome @ChrisMayLA6
Vertical stacking and the ability to wick away heat are where it's at now!
And maybe quantum will start a new scale curve?
-
@mdm @graydon @david_chisnall @linuxgnome @ChrisMayLA6 Well you *can* if you use muons instead of electrons but then you have to do your computing inside a particle accelerator and everything is radioactive and on fire
@cstross @mdm @graydon @david_chisnall @linuxgnome @ChrisMayLA6
TBH that sounds metal A F !
-
@david_chisnall It is, once again, a solution looking for the right problem.
LLMs seem to have some uses where they're better than other solutions (translation might be one) but those are too niche to sell them to everyone on the planet.
So they try to sell them as search engines, copywriters, programmers and a dozen other things just to attract more companies even if LLMs are a poor choice for their needs.
@dfyx @david_chisnall or translation might not be one: I learned of an example today (English -> French where the word "digit" got translated as "chiffre" (numerical digit) instead of "doigt" = "finger" that the original was talking about (in the context of workplace safety).
-
R relay@relay.infosec.exchange shared this topic
