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Semiconductor in general is going bust, too much supply. All semiconductors companies invested more because of Covid (and the sudden huge demand). Only CUDA/Nv

Semiconductor in general is going bust, too much supply. All semiconductors companies invested more because of Covid (and the sudden huge demand). Only CUDA/Nvidia managed to build something profitable with it, a competitive advantage that could also go down the drain once more investment is put into CUDA alternatives. And this is counting on AI hype to continue (likely, but maybe demand for hardware might eventually stabilise). Even though semiconductors is a highly specialized industry, it's a CAPEX heavy business, you need both fabs and research and you also have too many players in the market. People talk a lot about TSMC and the bleeding edge business(computers, phones), but that's just one part of it, but there's a whole industry of embarked software that will likely be much bigger. I don't doubt that the sector will grow(in revenues), but I doubt they'll be able to produce a profit as high as some companies in the tech sector like advertising etc, that are much more asset-light. I really fail to see what people see even in Nvidia/Cuda, it won't take long until others catch up, and they'll likely move back to margins closer to the industry, which are extremely low. There's even more money to be made in sectors like energy drinks.

throwoaaoekae 3y ago
[dead]
ckastner 3y ago
> Semiconductor in general is going bust, too much supply. All semiconductors companies invested more because of Covid (and the sudden huge demand). Semiconductors are cyclical in general, and most sources that I trust believe that the bottom is already behind us. Many of the big players have already begun guiding revenue growth again, though not as massive as Nvidia's windwall, obviously.
- MayeulC 3y ago
  I think I've really picked the worst time to finish my PhD thesis and go on the semiconductor job market... Though I think it will delay me by a few months at worst.
  - dboreham 3y ago
    After a couple decades you won't remember if you graduated during a boom or a bust.
    - bigfudge 3y ago
      I thought the evidence was that this did actually have a substantial impact on lifetime earnings and employment. The data I saw actually related to unemployment, but I would be surprised if it didn't have an impact. There are more opportunities to shine when things are on the up, and that benefit will persist into the bad times later. It's kind of like taking steroids as an athlete early on... you might stop later, but the muscle mass is still there.
    - lawlessone 3y ago
      I graduated 2012. The only people hiring were institutions that kicked off the 2008 recession.
    - jbm 3y ago
      I graduated with my Comp Sci degree in 2003ish, and my life was awful for at least 5 years post-graduation. I know it wasn't just me too. (This is also because of where I graduated, and the fact that I didn't feel comfortable moving to the US post-9-11)
    - ghaff 3y ago
      In a bust period, a lot of people end up taking whatever job will help pay the bills and, at some point, getting into the field they studied for means competing with new grads with more current knowledge and connections. I don't mean to imply your life is over if you graduate during a downturn but you can easily end up derailed and with a potential hit to your earnings going forward.
ethbr1 3y ago
I'd have said there was substantial unserved AI demand at less than current Nvidia prices, but hardware-via-cloud upsets that, given they can hit higher utilization. Of everyone, you'd think Microsoft would have the most incentive (and ability) to improve tooling/stability on not-Nvidia. > I really fail to see what people see even in Nvidia/Cuda, it won't take long until others catch up, and they'll likely move back to margins closer to the industry, which are extremely low. Looks like analyst predictions are that Nvidia growth will start flattening in Q1 2025. And when even Cathy Woods is selling because of over-valuation concerns, everyone should be looking for the exits. Part of Nvidia's strategic problem is that they made too much money recently: they needed lower profits in their primary markets to disincentivize competitor investment and retain their moat. Instead, AMD and Intel saw a cash cow. And those aren't small, ignorable competitors.
- mewpmewp2 3y ago
  I don't mean it as a commentary or opinion on Nvidia, but hearing Cathy Woods talking about Nvidia is as if she's just doubling down on her bad decision based on her initial gut feeling which she is too stubborn to admit that was wrong. To me it just seems like she happens to pick some stocks based on gut feeling because of some random detail she liked about it and then will say whatever to justify her positions afterwards.
  - webninja 3y ago
    Yeah Cathy Wood publicly said that she’d back off into more reliable cash flow positive businesses better PE ratios or even cash if the valuations got too high — which she didn’t do. Instead, at the peak, and the trough, she bought more Teladoc and Docusign instead! Both still have a negative PE ratio! They’re no-moat, no-profit, no-dividend, hype companies. The problem was, her ETFs are not paid and incentivized by performance. She’s paid and incentivized by AUM. So her team spends their time writing speeches and on Twitter writing hype posts instead of shutting up, being heads down buried in a laptop analyzing stocks, and performing analysis quietly. She might’ve been worried her AUM could drop if she made big changes like liquidating to cash.
- 3y ago
wslh 3y ago
Don't forget about the crypto scene that generated a lot of demands for GPUs. One day Ethereum moved, finally, to PoS.
- thiago_fm 3y ago
  It's the same story being played over again and nobody is seeing it. AI has a lot of similarities to the crypto bubble, but people keep repeating this "ah, but now it is useful!", sure it is. I like ChatGPT, but will people really use all those new AI products being built? Most things in the real world need an accuracy beyond what AI can offer and will likely offer in a few decades ahead, go learn about AI and any expert will show you that for example, LLMs can't solve some basic problems. I'm not saying AI will never be as smart as human, but rather that, it will take longer until we've figured out stuff that people are already pricing in into markets as if it will happen in a year.
SuchAnonMuchWow 3y ago
> I really fail to see what people see even in Nvidia/Cuda Cloud providers are choosing nvidia today as the gpgpu platform on the cloud, driven by neural network needs. So lots of software will be written with the platform in mind, aka. for nvidia arch / in cuda. This will add friction preventing users to easily change platform (see how long it took for people to switch their workloads to arm for example). It will drives more cloud providers to use nvidia, more software to be written for cuda, and the moat will build itself.
- l33tman 3y ago
  But there is really nothing that "normal" AI requires that is bound to CUDA. pyTorch and Tensorflow are backend agnostic (ideally...). Sure some hardcore people write some of their own cuda extensions but the vast majority don't. If there was a competing pytorch/tensorflow-supported backend at half the price, AI companies would quickly fix the quirks and run on that instead. It will be a race to the bottom eventually. Even more so on the cloud where you have a higher tendency to run value added services on top, that in turn are price sensitive.
  - brucethemoose2 3y ago
    Some popular ML projects ship with hand optimized CUDA kernels for performance. It is, unfortunately, the standard. If you get around that, sometimes projects will use dependencies that include an odd CUDA-only library. I ran into this a lot with GANs (which often use some weird loss metric with a random hard CUDA dependency) or media libs. Of course there are plenty of solutions, and some are theoretically transparent. But the issue is getting people to use them. Academic ML researchers in particular seem incredibly impatient, looking for the absolute easiest way to prototype something (which usually means coding what they already know). Ease of installation on a wide range of HW is about their last priority.
    - l33tman 3y ago
      Yeah I write CUDA kernels for my own projects as well. There won't be a shift if someone launches something that is 10% better, but if someone launches something that is twice the performance for the same price the companies with huge GPU-bills will pay to port those kernels pretty fast. The kernels I wrote I hand-optimized using Nsight for a specific usecase, and sure they saved me like 200% compared to pure pyTorch and it took a few days, but when your company spends $10M for a single training run, you have quite many of "my days" to spend if another HW platform would save you $5M (but you need to have the calendar time as well to spend, which is another factor in this space that moves crazily fast). If/when the field stabilizes a bit people will start looking at that bottom line I think but right now everybody just "has" to get those H100 cards before someone else gets them I guess...
sgerenser 3y ago
Energy drinks you say? Fun fact, Monster is one of only a small number of stocks that outperformed NVDA over the past 20 years: https://www.portfoliovisualizer.com/backtest-portfolio?s=y&sl=v0L77PTKrmG9xdgNq61w5 https://www.portfoliovisualizer.com/backtest-portfolio?s=y&s...
- deleted 3y ago
  [deleted]
- 0cf8612b2e1e 3y ago
  That’s amusing. Although, Monster had explosive growth in its first few years (starting from nothing). Do it over 17 years and NVidia wins.
  - boringg 3y ago
    That and construction slowing down. I see a lot of construction guys downing Monster energy drinks. TBH I'm always a little surprised -- but it does give you energy when you need it.
    - ComputerGuru 3y ago
      Aside from the caffeine boost the bigger issue is just that They burn through calories.
  - eigenvalue 3y ago
    Monster is a classic "capital lite" business model with a large and growing addressable market, and management has been extremely successful reinvesting the substantial free cash flow generated by the business into organic growth and acquisitions. There are really only a handful of businesses of that calibur in the entire public market. Of course, people have realized all of this by this point, so Monster stock trades a large multiple of earnings (nearly 40x), while prospective growth will never match what they did historically from inception, otherwise they'd end up the largest company in the world after not too long!
jncfhnb 3y ago
So… why though? Is the market really not mature enough to anticipate the bull whip?
- pjc50 3y ago
  The business cycle in general is an unsolved problem, and I think enough companies were investing during COVID to meet the shortages that they over-invested for the demand impacts of the Russia-Ukraine war and its effect on Western inflation.
c7DJTLrn 3y ago
>Semiconductor in general is going bust, too much supply. TSMC literally can't make chips fast enough. Companies are competing for wafers. >you also have too many players in the market How? There are a handful of companies on the planet that can do 7nm process chips and below. Western Digital had an issue with its fab in 2022 and that alone was apparently enough to increase NAND flash prices by 10%.
- rowanG077 3y ago
  I almost can't believe this comment. TSMC literally has an entire paragraph in parents comment that addresses it. The comment is about the much larger semiconductor business, not bleeding edge. I fail to see from any perspective how you can read that comment and post this.
  - jonwachob91 3y ago
    Parents Comment >> People talk a lot about TSMC and the bleeding edge business(computers, phones), but that's just one part of it, but there's a whole industry of embarked software that will likely be much bigger. Your comment >> TSMC literally has an entire paragraph in parents comment that addresses it. That looks like a single sentence, not an entire paragraph... And it's a paragraph without supporting evidence. No shocker c7DJTLrn wasn't convinced about parent commenters weak claim.
    - rowanG077 3y ago
      The sentence is obviously delineated by two newlines. A paragraph made of a single sentence. The paragraph is so obvious that I would never expect anyone to question it. TSMC is a mere 12.5% of global semiconductor market in 2022.
      - reisse 3y ago
        There is no global semiconductor market. Saying it exists is the same thing as saying that global vehicle market exists and Boeing competes with Ford in making the best selling vehicle. There is, however, "consumer chips foundry market", which is dominated by TSMC with 55%+ market share. And TSMC's market share is limited only because of their production capacity.
scarface_74 3y ago
It’s not just a matter of catching up with Nvidia hardware - and who is going to do it? One of the major cloud providers? AMD? Apple? Say they do catch up with the hardware, are they also going to convince the entire industry to switch from CUDA.
- ElectricalUnion 3y ago
  > and who is going to do it? One of the big-enough generative/LLM AI users would be my guess. OpenAI for example seems to be even going towards making it's own chips as an alternative to Nvidia things being too expensive. > are they also going to convince the entire industry to switch from CUDA. Statistically unlikely, for example ARM definitely disrupted MIPS in several embedded networking niches uses, but didn't convince the entire industry to switch from MIPS.
  - scarface_74 3y ago
    You realize the type of expertise and money needed to design a processor? That’s not even to mention the loads of money you need to back up to TSMC to even get capacity. For cutting edge fabrication, you’re still going to be behind, Apple and Nvidia to get capacity
    - jlokier 3y ago
      OpenAI doesn't need a general purpose GPU like Nvidia. It has too major tasks that could benefit from custom ASiCs that we know of: training and inference, for which efficient designs are different. Designing a specialised ASIC is much easier and cheaper than a general-purpose, public use processor for a wide range of applications. You don't need most of the programmability or even half the compute and fancy memory and scheduling units. You also don't need the to develop a rich API (like CUDA or Vulkan) for third parties to use. This holds even for state of the art intensive calculation engines with minimised energy consumption. Think of all the crypto-mining ASICs that were built a few years ago. They were relatively cheap to design and optimised for calculations per energy unit.
da_chicken 3y ago
> I really fail to see what people see even in Nvidia/Cuda They're a nice middle ground between a GP CPU and ASICs that is well suited to the kinds of workloads that venture capitalists are, for the moment, interested in investing in. And it's possible that there are enough applications that benefit from GPU architecture that it's more efficient to force a GPU to pretend to be a CPU instead of having a CPU. Most likely it's just another cycle of the RISC vs CISC pendulum. Like cloud vs desktop, physical vs virtual, serial vs parallel, monolithic vs micro, etc. We'll stick with CUDA and use it to solve as many problems as we can with that method, and then as we discover new ways to create or organize GP CPUs, we'll shift back to those until we find that problems get hard to solve again.
reaperman 3y ago
> there's a whole industry of embarked software that will likely be much bigger. What in embarked? Genuinely curious if this is a misspelling of embedded or if it's something else entirely.
- airstrike 3y ago
  Embedded but on a boat rather than a bed
mattnewton 3y ago
> I really fail to see what people see even in Nvidia/Cuda, it won't take long until others catch up, and they'll likely move back to margins closer to the industry, which are extremely low I thought that would happen by now too, in 2016, so I started slowly selling much of my NVDA stake after a few years. This was wrong. It turns out they have created an ecosystem effect where everyone makes their papers and code work in CUDA and everything else is best effort. AMD hasn’t even really been seriously trying from my point of view, but once they do they’re still trying to bail water with a leaky bucket - new models come out every day where the researchers have run and tested on CUDA only.
- thiago_fm 3y ago
  There wasn't much money on the table back then. Now there is.
k7sune 3y ago
When the governments see that their investments or subsidies could not break the monopoly of TSMC, I wonder if they’ll change their geopolitical strategy. Instead of protecting Taiwan for silicon supply stability, they’ll encourage an all out war between Taiwan and China. By destroying the head of the monopoly, the fabs in their countries can compete against the market again.
tortoise_in 3y ago
Nividia because of bitcoin?

throwoaaoekae 3y ago

[dead]

ckastner 3y ago

> Semiconductor in general is going bust, too much supply. All semiconductors companies invested more because of Covid (and the sudden huge demand). Semiconductors are cyclical in general, and most sources that I trust believe that the bottom is already behind us. Many of the big players have already begun guiding revenue growth again, though not as massive as Nvidia's windwall, obviously.

MayeulC 3y ago
I think I've really picked the worst time to finish my PhD thesis and go on the semiconductor job market... Though I think it will delay me by a few months at worst.
- dboreham 3y ago
  After a couple decades you won't remember if you graduated during a boom or a bust.
  - bigfudge 3y ago
    I thought the evidence was that this did actually have a substantial impact on lifetime earnings and employment. The data I saw actually related to unemployment, but I would be surprised if it didn't have an impact. There are more opportunities to shine when things are on the up, and that benefit will persist into the bad times later. It's kind of like taking steroids as an athlete early on... you might stop later, but the muscle mass is still there.
  - lawlessone 3y ago
    I graduated 2012. The only people hiring were institutions that kicked off the 2008 recession.
  - jbm 3y ago
    I graduated with my Comp Sci degree in 2003ish, and my life was awful for at least 5 years post-graduation. I know it wasn't just me too. (This is also because of where I graduated, and the fact that I didn't feel comfortable moving to the US post-9-11)
  - ghaff 3y ago
    In a bust period, a lot of people end up taking whatever job will help pay the bills and, at some point, getting into the field they studied for means competing with new grads with more current knowledge and connections. I don't mean to imply your life is over if you graduate during a downturn but you can easily end up derailed and with a potential hit to your earnings going forward.

ethbr1 3y ago

I'd have said there was substantial unserved AI demand at less than current Nvidia prices, but hardware-via-cloud upsets that, given they can hit higher utilization. Of everyone, you'd think Microsoft would have the most incentive (and ability) to improve tooling/stability on not-Nvidia. > I really fail to see what people see even in Nvidia/Cuda, it won't take long until others catch up, and they'll likely move back to margins closer to the industry, which are extremely low. Looks like analyst predictions are that Nvidia growth will start flattening in Q1 2025. And when even Cathy Woods is selling because of over-valuation concerns, everyone should be looking for the exits. Part of Nvidia's strategic problem is that they made too much money recently: they needed lower profits in their primary markets to disincentivize competitor investment and retain their moat. Instead, AMD and Intel saw a cash cow. And those aren't small, ignorable competitors.

mewpmewp2 3y ago
I don't mean it as a commentary or opinion on Nvidia, but hearing Cathy Woods talking about Nvidia is as if she's just doubling down on her bad decision based on her initial gut feeling which she is too stubborn to admit that was wrong. To me it just seems like she happens to pick some stocks based on gut feeling because of some random detail she liked about it and then will say whatever to justify her positions afterwards.
- webninja 3y ago
  Yeah Cathy Wood publicly said that she’d back off into more reliable cash flow positive businesses better PE ratios or even cash if the valuations got too high — which she didn’t do. Instead, at the peak, and the trough, she bought more Teladoc and Docusign instead! Both still have a negative PE ratio! They’re no-moat, no-profit, no-dividend, hype companies. The problem was, her ETFs are not paid and incentivized by performance. She’s paid and incentivized by AUM. So her team spends their time writing speeches and on Twitter writing hype posts instead of shutting up, being heads down buried in a laptop analyzing stocks, and performing analysis quietly. She might’ve been worried her AUM could drop if she made big changes like liquidating to cash.
3y ago

wslh 3y ago

Don't forget about the crypto scene that generated a lot of demands for GPUs. One day Ethereum moved, finally, to PoS.

thiago_fm 3y ago
It's the same story being played over again and nobody is seeing it. AI has a lot of similarities to the crypto bubble, but people keep repeating this "ah, but now it is useful!", sure it is. I like ChatGPT, but will people really use all those new AI products being built? Most things in the real world need an accuracy beyond what AI can offer and will likely offer in a few decades ahead, go learn about AI and any expert will show you that for example, LLMs can't solve some basic problems. I'm not saying AI will never be as smart as human, but rather that, it will take longer until we've figured out stuff that people are already pricing in into markets as if it will happen in a year.

SuchAnonMuchWow 3y ago

> I really fail to see what people see even in Nvidia/Cuda Cloud providers are choosing nvidia today as the gpgpu platform on the cloud, driven by neural network needs. So lots of software will be written with the platform in mind, aka. for nvidia arch / in cuda. This will add friction preventing users to easily change platform (see how long it took for people to switch their workloads to arm for example). It will drives more cloud providers to use nvidia, more software to be written for cuda, and the moat will build itself.

l33tman 3y ago
But there is really nothing that "normal" AI requires that is bound to CUDA. pyTorch and Tensorflow are backend agnostic (ideally...). Sure some hardcore people write some of their own cuda extensions but the vast majority don't. If there was a competing pytorch/tensorflow-supported backend at half the price, AI companies would quickly fix the quirks and run on that instead. It will be a race to the bottom eventually. Even more so on the cloud where you have a higher tendency to run value added services on top, that in turn are price sensitive.
- brucethemoose2 3y ago
  Some popular ML projects ship with hand optimized CUDA kernels for performance. It is, unfortunately, the standard. If you get around that, sometimes projects will use dependencies that include an odd CUDA-only library. I ran into this a lot with GANs (which often use some weird loss metric with a random hard CUDA dependency) or media libs. Of course there are plenty of solutions, and some are theoretically transparent. But the issue is getting people to use them. Academic ML researchers in particular seem incredibly impatient, looking for the absolute easiest way to prototype something (which usually means coding what they already know). Ease of installation on a wide range of HW is about their last priority.
  - l33tman 3y ago
    Yeah I write CUDA kernels for my own projects as well. There won't be a shift if someone launches something that is 10% better, but if someone launches something that is twice the performance for the same price the companies with huge GPU-bills will pay to port those kernels pretty fast. The kernels I wrote I hand-optimized using Nsight for a specific usecase, and sure they saved me like 200% compared to pure pyTorch and it took a few days, but when your company spends $10M for a single training run, you have quite many of "my days" to spend if another HW platform would save you $5M (but you need to have the calendar time as well to spend, which is another factor in this space that moves crazily fast). If/when the field stabilizes a bit people will start looking at that bottom line I think but right now everybody just "has" to get those H100 cards before someone else gets them I guess...

sgerenser 3y ago

Energy drinks you say? Fun fact, Monster is one of only a small number of stocks that outperformed NVDA over the past 20 years: https://www.portfoliovisualizer.com/backtest-portfolio?s=y&sl=v0L77PTKrmG9xdgNq61w5 https://www.portfoliovisualizer.com/backtest-portfolio?s=y&s...

deleted 3y ago
[deleted]
0cf8612b2e1e 3y ago
That’s amusing. Although, Monster had explosive growth in its first few years (starting from nothing). Do it over 17 years and NVidia wins.
- boringg 3y ago
  That and construction slowing down. I see a lot of construction guys downing Monster energy drinks. TBH I'm always a little surprised -- but it does give you energy when you need it.
  - ComputerGuru 3y ago
    Aside from the caffeine boost the bigger issue is just that They burn through calories.
- eigenvalue 3y ago
  Monster is a classic "capital lite" business model with a large and growing addressable market, and management has been extremely successful reinvesting the substantial free cash flow generated by the business into organic growth and acquisitions. There are really only a handful of businesses of that calibur in the entire public market. Of course, people have realized all of this by this point, so Monster stock trades a large multiple of earnings (nearly 40x), while prospective growth will never match what they did historically from inception, otherwise they'd end up the largest company in the world after not too long!

jncfhnb 3y ago

So… why though? Is the market really not mature enough to anticipate the bull whip?

pjc50 3y ago
The business cycle in general is an unsolved problem, and I think enough companies were investing during COVID to meet the shortages that they over-invested for the demand impacts of the Russia-Ukraine war and its effect on Western inflation.

c7DJTLrn 3y ago

>Semiconductor in general is going bust, too much supply. TSMC literally can't make chips fast enough. Companies are competing for wafers. >you also have too many players in the market How? There are a handful of companies on the planet that can do 7nm process chips and below. Western Digital had an issue with its fab in 2022 and that alone was apparently enough to increase NAND flash prices by 10%.

rowanG077 3y ago
I almost can't believe this comment. TSMC literally has an entire paragraph in parents comment that addresses it. The comment is about the much larger semiconductor business, not bleeding edge. I fail to see from any perspective how you can read that comment and post this.
- jonwachob91 3y ago
  Parents Comment >> People talk a lot about TSMC and the bleeding edge business(computers, phones), but that's just one part of it, but there's a whole industry of embarked software that will likely be much bigger. Your comment >> TSMC literally has an entire paragraph in parents comment that addresses it. That looks like a single sentence, not an entire paragraph... And it's a paragraph without supporting evidence. No shocker c7DJTLrn wasn't convinced about parent commenters weak claim.
  - rowanG077 3y ago
    The sentence is obviously delineated by two newlines. A paragraph made of a single sentence. The paragraph is so obvious that I would never expect anyone to question it. TSMC is a mere 12.5% of global semiconductor market in 2022.
    - reisse 3y ago
      There is no global semiconductor market. Saying it exists is the same thing as saying that global vehicle market exists and Boeing competes with Ford in making the best selling vehicle. There is, however, "consumer chips foundry market", which is dominated by TSMC with 55%+ market share. And TSMC's market share is limited only because of their production capacity.

scarface_74 3y ago

It’s not just a matter of catching up with Nvidia hardware - and who is going to do it? One of the major cloud providers? AMD? Apple? Say they do catch up with the hardware, are they also going to convince the entire industry to switch from CUDA.

ElectricalUnion 3y ago
> and who is going to do it? One of the big-enough generative/LLM AI users would be my guess. OpenAI for example seems to be even going towards making it's own chips as an alternative to Nvidia things being too expensive. > are they also going to convince the entire industry to switch from CUDA. Statistically unlikely, for example ARM definitely disrupted MIPS in several embedded networking niches uses, but didn't convince the entire industry to switch from MIPS.
- scarface_74 3y ago
  You realize the type of expertise and money needed to design a processor? That’s not even to mention the loads of money you need to back up to TSMC to even get capacity. For cutting edge fabrication, you’re still going to be behind, Apple and Nvidia to get capacity
  - jlokier 3y ago
    OpenAI doesn't need a general purpose GPU like Nvidia. It has too major tasks that could benefit from custom ASiCs that we know of: training and inference, for which efficient designs are different. Designing a specialised ASIC is much easier and cheaper than a general-purpose, public use processor for a wide range of applications. You don't need most of the programmability or even half the compute and fancy memory and scheduling units. You also don't need the to develop a rich API (like CUDA or Vulkan) for third parties to use. This holds even for state of the art intensive calculation engines with minimised energy consumption. Think of all the crypto-mining ASICs that were built a few years ago. They were relatively cheap to design and optimised for calculations per energy unit.

da_chicken 3y ago

> I really fail to see what people see even in Nvidia/Cuda They're a nice middle ground between a GP CPU and ASICs that is well suited to the kinds of workloads that venture capitalists are, for the moment, interested in investing in. And it's possible that there are enough applications that benefit from GPU architecture that it's more efficient to force a GPU to pretend to be a CPU instead of having a CPU. Most likely it's just another cycle of the RISC vs CISC pendulum. Like cloud vs desktop, physical vs virtual, serial vs parallel, monolithic vs micro, etc. We'll stick with CUDA and use it to solve as many problems as we can with that method, and then as we discover new ways to create or organize GP CPUs, we'll shift back to those until we find that problems get hard to solve again.

reaperman 3y ago

> there's a whole industry of embarked software that will likely be much bigger. What in embarked? Genuinely curious if this is a misspelling of embedded or if it's something else entirely.

airstrike 3y ago
Embedded but on a boat rather than a bed

mattnewton 3y ago

> I really fail to see what people see even in Nvidia/Cuda, it won't take long until others catch up, and they'll likely move back to margins closer to the industry, which are extremely low I thought that would happen by now too, in 2016, so I started slowly selling much of my NVDA stake after a few years. This was wrong. It turns out they have created an ecosystem effect where everyone makes their papers and code work in CUDA and everything else is best effort. AMD hasn’t even really been seriously trying from my point of view, but once they do they’re still trying to bail water with a leaky bucket - new models come out every day where the researchers have run and tested on CUDA only.

thiago_fm 3y ago
There wasn't much money on the table back then. Now there is.

k7sune 3y ago

When the governments see that their investments or subsidies could not break the monopoly of TSMC, I wonder if they’ll change their geopolitical strategy. Instead of protecting Taiwan for silicon supply stability, they’ll encourage an all out war between Taiwan and China. By destroying the head of the monopoly, the fabs in their countries can compete against the market again.

tortoise_in 3y ago

Nividia because of bitcoin?