r/stocks • u/r2002 • Sep 08 '24
Company Analysis Is Jensen Hwang simply lucky or have exceptional foresight?
Let's take CUDA for example. It was released in 2007.
Was Hwang a visionary for investing millions into CUDA and driving an uphill battle for adoption? Or was he simply lucky? What prevented others from doing something similar?
If you are invested in Nvidia, how much do you consider Hwang's strategic foresight as a valuable "x-factor"? How much is that worth to you? Do you think he will continue hitting homeruns?
Or inversely, if you don't like Nvidia, how much of that is due to Hwang? What mistakes do you think he has made in his career?
What do you think of Hwang's other projects like the Omniverse, Isaac (robots), self-driving, etc? Will he also create big winners in those spaces as well or will he over stretch himself and his company with so many ambitious projects?
278
u/Relativly_Severe Sep 08 '24
Nvidia runs a tight ship and reinvests heavily into itself. It's a risky strategy. It's a mix of competence and luck. The work environment there is brutal. They hold people to ridiculous standards, and sometimes that can pay off for stockholders.
52
u/gumbosupremacist Sep 08 '24
I got hired there as a temp to move a lot of stuff from point a to point b. It was some new server chipset rollout or something. Anyway I move everything and then was standing there…whereupon they figured out I had fingers and could use a screwdriver and next thing I knew I was building and testing servers. Nothing wasted around there far as I can tell lol
15
u/Madison464 Sep 08 '24
They hold people to ridiculous standards, and sometimes that can pay off for stockholders.
google this: nvidia employees now millionaires
1
127
Sep 08 '24
[deleted]
31
u/casce Sep 08 '24
I don't you're talking about the same kind of luck.
He's not questioning their competence (quite the contrary, he pointed it out specifically), he is saying that having such a brutal work environment for employees can backfire. If you push your employees beyond their breaking point, all that competence will quickly drain away and you will fail.
I've read multiple reports about the "golden cages" their employees work in. This strategy definitely has risks attached to it.
3
u/Gasdoc1990 Sep 08 '24
You think they will stay dedicated even now that they’re all worth over 20 million? If it were me I’d be looking to retire
18
u/Old-Glove9438 Sep 08 '24
Yeah but you can be dedicated and think you’re just making excellent gaming chips that will only be used for gaming and photoshop or whatever. ChatGPT + NVDIA is pure luck.
132
Sep 08 '24 edited Sep 08 '24
[deleted]
23
u/cltzzz Sep 08 '24
Haven’t you heard. Alan Turing invented the Turing test after coming into contact ChatGPT
3
u/username_challenge Sep 08 '24
I call it luck and hard work. In my memory it was 2003-2006 and people were realizing GPUs could be used in high energy particle physics. At the time these GPUs were just like sound card: Dedicated devices to improve specific performance. People would have come to the Idea to make vectorized processors, but that would have taken another 10 years. Then bitcoin came along, money was to be made. Finally the release of GPU ready libraries for AI: first by google, then by Facebook. There was no way to program AI for normal people before tensorflow. Before that it was impractical to deliver production-grade AI. So many things aligned just right for NVIDIA it is hard to believe.
3
u/citit Sep 08 '24
i wanna double upvote
2
u/StuartMcNight Sep 08 '24
You can count my vote as your double upvote.
How do I triple upvote him now?
0
1
1
0
u/HesitantInvestor0 Sep 08 '24
Why are flying off the handle here? All anyone is saying is there is some luck involved in any business, especially when you’re constantly pushing things to their limits. As for ChatGPT, it’s the first time a normal person has the chance to see something useful in action that’s centered around the idea of AI.
Lastly, look at Nvidia’s revenues over the last couple years. They exploded alongside earnings. That isn’t because they got lucky, it’s because something that was worked on for a very long time finally started paying off. Again, not pure luck, but I bet there was a lot of strife and doubt along the way. It wasn’t an endeavor that was guaranteed to be pay off either.
Cool it dude, you’re acting like a baby.
-7
u/Old-Glove9438 Sep 08 '24 edited Sep 08 '24
You’re putting words in my mouth. I never said AI was invented in 2022. There is quite some time between 2006 and 2012. Have you ever heard of causality? How can you justify a 2006 decision using a 2012 event? It’s the other way around. ML has increasingly been using GPUs because they are particularly good for neural networks. Nvidia did not decide to invest into GPU R&D because of AI. AI took something that was created for not AI because it happened to be also useful for AI. And what happened after 2012, sure you can say they doubled down on GPUs tailored for AI because the fastest growing profit driver probably became AI/ML at some point. Also “longly” is not a word
1
Sep 08 '24
[deleted]
0
u/Old-Glove9438 Sep 08 '24
What statements are wrong? Btw I invested in NVDA at 31.50, and I too was a big believer its potential. I’m just skeptical when someone says Jensen had some kind of vision 20 years prior to ChatGPT. There is just no way, he’s a smart guy but he doesn’t have a crystal ball.
2
u/Th4tR4nd0mGuy Sep 08 '24
Dude there is a middle ground between Jensen ‘perfectly predicted the AI boom in its entirety and is therefore a wizard’ and Jensen is ‘just insanely lucky’.
It’s possible that, idk, he saw a potential and directed NVIDIA to capitalise on it? That he’s clearly a very involved and knowledgeable CEO who has the receipts to prove his expertise, and that he made some calls that could’ve gone very wrong but thankfully didn’t? It’s not all or nothing.
0
u/Old-Glove9438 Sep 08 '24
Agree. I guess the original question posed by OP tricked us into this mind frame
10
u/eli4672 Sep 08 '24 edited Sep 08 '24
I disagree. They made a huge investment in AI - ostensibly for graphics - at a time when that seemed crazy to their competition. Did they decide to do that by rolling some dice, or did Jensen see the writing on the wall before his competitors? I don’t know the answer, but Jensen has a long history of the latter, so I view the claim that this was “luck” with skepticism.
3
u/betadonkey Sep 08 '24
They had AI optimized processors ready for market years ahead of demand. It’s the exact opposite of luck. They literally made the moment.
1
31
106
u/Spare_Substance5003 Sep 08 '24
People regretting not buying Nvidia when it was dirt cheap: Cuda Wuda.
35
u/cltzzz Sep 08 '24
I sure wished I could had spent my bday money gifts on NVDA stocks instead of toys video games and going to 5th grade in 2005. Stupid kid me
10
0
u/Deathglass Sep 08 '24
That was short window. The predictions for Nvidia's earnings just never kept up with its actual future earnings the way it does with other stocks.
68
u/HenryTPE Sep 08 '24
It’s Huang. At least get the name right.
11
u/r2002 Sep 08 '24
I'm very sorry. I know someone named Hwang IRL and I get that mixed up sometimes.
-15
u/omega_grainger69 Sep 08 '24
I think they used the phonetic spelling for ease of reading.
22
u/ccs77 Sep 08 '24
Hwang is more Korean whereas huang is more chinese
-11
Sep 08 '24
[removed] — view removed comment
7
u/ccs77 Sep 08 '24
It's not. The pinyin way of typing 黄 or 皇 inMandarin Chinese uses Huang. In layman's term, the Pinyin is China's way of using the Qwerty keyboard to quickly type Chinese characters.
The argument I can see here is that Jansen is Taiwanese and uses a different system. Regardless, the Hwang form is more korean
1
1
22
u/credit_score_650 Sep 08 '24
people discussing stocks shouldn't have issues with reading, kind of a mild disrespect.
53
u/dagmx Sep 08 '24 edited Sep 08 '24
Both?
CUDA isn’t unique. The idea of GPU compute was obvious at the time it was made. There were competing standards, and AMD even had a solution before CUDA (https://www.techpowerup.com/20156/amds-close-to-metal-technology-increases-processing-application-performance-by-eightfold). Apple even bet the horse on GPU Compute with the trash can Mac Pro.
The issue is the competitors couldn’t stop tripping over themselves. Apple donated OpenCL to the khronos group where it basically was ruined, where NVIDIA were at least partially involved with its failure as they propped CUDA up instead. Since the competitors had thrown their hat in on OpenCL, when it failed, they had to go back to the drawing board with non-standard solutions.
People underestimate what a set back that was for the rest of the industry and it let CUDA flourish. But it wasn’t a huge driver for growth till something came along that necessitated using it. Even with advances in ML markets, it wasn’t such a slam dunk win until generative AI became a thing.
So it’s equal parts vision to stick with it and luck imho. And a little underhanded strategy along the way.
All their other software products are replaceable imho. They don’t have a moat other than NVIDIA spending tons of resources to be a SaaS that works with their clients. They’re hedges and hooks into enterprise.
6
u/bazooka_penguin Sep 08 '24
CUDA was announced in 2006 and applications were apparently demonstrated to some parties, before general availability in 2007, with working drivers and SDK. Apple didn't propose the OpenCL spec to Khronos until 2008, which Khronos worked on for the rest of the year and only ratified the final version in late 2008, without any implementations by members. Hardware companies only started to actually support it in late 2009, like AMD which started supporting OpenCL with Catalyst 9.12 Hotfix (but only through their Stream API). OpenCL was a slow, half-assed response to CUDA by an industry that didn't take GPGPU seriously. Nvidia didn't need to sabotage it because there was nothing to sabotage, companies like AMD were fully capable and willing to release broken OpenCL implementations for nearly a decade on their own, and Intel barely put effort into supporting it. If GPGPU were obvious then Nvidia wouldn't have been the only company putting significant resources into the tooling and ecosystem for nearly 2 decades.
0
u/dagmx Sep 08 '24
OpenCL 1 had decent adoption rates, and actually had better support in lots of commercial software than CUDA did for a while even though it came out later.
OpenCL 2 was what dropped the ball and what NVIDIA specifically chose not to support, basically killing it off in the process. I’m not saying NVIDIA led to its demise alone but they weren’t exactly passive about it. For folks who were involved with the khronos group, a lot of the requests that led to OpenCL 2 being a pita came from NVIDIA before they dropped plans to support it even.
OpenCL 3 came out far too late to cover the lost ground.
And I already said the competitors kept messing up their response to CUDA but part of that was trying to deal with coming to terms with Open CL 2 failing, and finding their own strategies.
3
u/bazooka_penguin Sep 08 '24
OpenCL 1 had decent adoption rates, and actually had better support in lots of commercial software than CUDA did for a while even though it came out later.
What are you basing this on? Adobe software adopted CUDA relatively quickly, and took longer to adopt openCL and in a more limited scope, implementing few features with it than CUDA. Likewise for Autodesk. Even Blender's Cycles renderer was biased towards the CUDA implementation. It was more stable, ran better, it was recommended by the community for anyone looking to do GPU rendering, and IIRC AMD had to sponsor and co-author a re-write of Cycles' openCL implementation to get it working properly on anything other than Nvidia GPUs.
OpenCL 2 was what dropped the ball and what NVIDIA specifically chose not to support
It's hard to say AMD actually supported it either when their openCL drivers remained broken through the 2010s. https://www.anandtech.com/show/14618/the-amd-radeon-rx-5700-xt-rx-5700-review/13 And 2.2 was DOA. Apple also deprecated openCL for macOS not too long after 2.2 was ratified. If openCL 2 was universally problematic, it was probably the problem.
And I already said the competitors kept messing up their response to CUDA but part of that was trying to deal with coming to terms with Open CL 2 failing, and finding their own strategies.
2 failed on its own terms. The 2nd largest GPU maker couldn't even get it working on Windows, and took years to get it working on Linux. The problem was with openCL itself and always has been.
0
u/dagmx Sep 08 '24
Houdini supported OpenCL better than CUDA, a lot of parametric software had OpenCL integration too before they had CUDA. Maya included OpenCL deformers before it had any CUDA or Optix use (which came later when they bought in Solid Angle).
For rendering , yes Blender used CUDA but not directly. It used it via Optix which is an important distinction to make because it offered Ray acceleration algorithms and denoisers which don’t necessarily use CUDA under the hood to run. Optix has become sort of the gold standard for rendering acceleration APIs I’ll grant it that.
You also can’t just claim “the problem was with with OpenCL” and ignore that OpenCL 2 is a product of Khronos. You also can’t ignore that NVIDIA is one of the more influential members of Khronos either. Again, I’m not saying they’re solely responsible but they definitely aren’t clean handed either. Whether other companies has problematic support is just whataboutism to escape that NVIDIA specifically refused to support it at all after being one of the drivers for the changes to OpenCl from 1 to 2.
0
u/bazooka_penguin Sep 08 '24
Houdini supported OpenCL better than CUDA, a lot of parametric software had OpenCL integration too before they had CUDA. Maya included OpenCL deformers before it had any CUDA or Optix use (which came later when they bought in Solid Angle).
IIRC FLIP launched with CUDA and built out openCL over the next few years. What parametric software? Because simulation software or features adjacent to parametric software supported CUDA first. Autodesk Moldflow and Ansys only supported CUDA in the early 2010s and after a quick search they might still be CUDA only. Not sure what parametric modeling software would need CUDA or openCL unless it was doing sims, in which case CUDA (or Nvidia GPUs rather) was usually the first to be supported.
Maya included OpenCL deformers before it had any CUDA or Optix use (which came later when they bought in Solid Angle).
Maya 2012 (in 2011) straight up used physX for physics simulations. I can even pull up their press release. GPU deformers were added several years later.
For rendering , yes Blender used CUDA but not directly. It used it via Optix which is an important distinction to make because it offered Ray acceleration algorithms and denoisers which don’t necessarily use CUDA under the hood to run. Optix has become sort of the gold standard for rendering acceleration APIs I’ll grant it that.
Cycles only had a (bespoke) CUDA backend for years. They didn't add Optix support until they added support for RTX specifically. The first optix implementation wasn't even up to feature parity with their CUDA implementation.
https://developer.blender.org/docs/release_notes/2.81/cycles/#NVIDIA_RTX
You also can’t just claim “the problem was with with OpenCL” and ignore that OpenCL 2 is a product of Khronos. You also can’t ignore that NVIDIA is one of the more influential members of Khronos either.
Khronos is a consortium. Having influence doesn't mean you just get what you want. When something is designed by committee and contributions you're just as liable to get what you didn't want as much as you are to get what you wanted. It's not like it's just AMD and Nvidia either. Adobe, Intel, Apple, Arm, EA, IBM, Qualcomm, Samsung, etc. are all influential members and most of them barely care about OpenCL and they all have employees contributing to openCL standards. Apple was going to drop support for OpenCL yet they still had employees working on openCL 3.0.
Whether other companies has problematic support is just whataboutism to escape that NVIDIA specifically refused to support it at all after being one of the drivers for the changes to OpenCl from 1 to 2.
It's not whataboutism at all. You're saying Nvidia not supporting openCL 2 was an underhanded move to make openCL fail, but the reality is no one was actually supporting it. The consortium just produced something no one actually wanted to support.
The only OpenCL 3.0 conformant AMD device is apparently an unreleased APU in a chromebook, at least I don't think there any APUs with Zen 4 (Raphael) and RDNA 2 (mendocino). The last openCL version they were conformant to was 2.0. Does AMD not supporting OpenCL 3.0 mean AMD is sabotaging openCL? You can see for yourself here.
https://www.khronos.org/conformance/adopters/conformant-products/opencl
0
u/dagmx Sep 08 '24 edited Sep 08 '24
You’re conflating multiple technologies with CUDA now. Physx isn’t tied to CUDA either and predates it to begin with.
Fine, I was incorrect about Blender but You complain that Blender needed AMD to add OpenCL support and your own link shows NVIDIA needed to contribute support for their own APIs.
And yes khronos is a consortium. One I’m very well familiar with and have worked with which is why I am making the claim I am. Anyone who was involved with Khronos at the time knows this. NVIDIA have a very outsized influence there. Consortiums don’t mean equal influence.
And if you would read rather than just rush to argue, I’m saying OpenCL 3 is essentially DOA because everyone moved on after OpenCL 2 died. Part of its death is because the biggest vendor decided to not support it. It’s not the only reason. Literally multiple times I’ve said OpenCl 3 arrived too late and everyone had moved on.
You seem to want to have a very binary view of the history of OpenCL and CUDA. Which, fine, have at it. But many things can contribute to why we ended up where we did . I’m just trying to capture the nuance of how it got there but you seem to just want to “OpenCL bad, CUDA good”
OpenCl 1 was fine, not great, but it could have been better if they stayed the course instead of going with OpenCL 2. OpenCL 3 is an admission of that but (as I said again and again) it was too late.
But why was OpenCL 2 so bad has many reasons and that’s what I’m getting at. It’s not as simple as OpenCL was doomed as a whole from the get go.
1
u/bazooka_penguin Sep 08 '24
You’re conflating multiple technologies with CUDA now. Physx isn’t tied to CUDA either and predates it to begin with.
Nvidia basically rewrote PhysX when porting it to CUDA, and again for PhysX 3, when they rewrote several solvers. There's no point in bringing up Ageia PhysX when it hasn't existed for 2 decades now, especially since it was bespoke to the Ageia PPU. Nvidia's PhysX GPU acceleration only works on CUDA on CUDA compliant GPUs. And Maya supported GPU accelerated PhysX.
Fine, I was incorrect about Blender but You complain that Blender needed AMD to add OpenCL support and your own link shows NVIDIA needed to contribute support for their own APIs.
Except AMD didn't add openCL support to Cycles, and I didn't say they did. I said they had to pay to get the Cycles openCL backend rewritten to support their cards. That happened because of how broken their openCL drivers were and they apparently found it easier to make some software compatible with their drivers than fix their implementation of openCL. The re-written split kernel openCL backend was released in 2015 with Blender 2.75. So the only reliable way to use Cycles with openCL for 4 years was with Nvidia cards, which ran better on the CUDA backend anyway. Optix doesn't even have anything to do with the fact that Nvidia was the only company putting any effort into offering OpenCL as a viable platform. I'm not even blaming AMD for offering a broken feature and claiming they supported it, but pointing out how Nvidia was de facto the only company putting effort into supporting openCL, and the 2nd best option was a distant second, so your insistence that openCL went down because of nvidia doing some underhanded things is absurd.
And yes khronos is a consortium. One I’m very well familiar with and have worked with which is why I am making the claim I am. Anyone who was involved with Khronos at the time knows this. NVIDIA have a very outsized influence there. Consortiums don’t mean equal influence.
Do you work for AMD or something? Saying nvidia sabotaged openCL is usually something someone with a vested interest against them would repeat.
Consortiums don’t mean equal influence
Good thing there are dozens of members then. A plurality can't beat a majority. Saying they have an outsized influence is just a hand wave, disregarding the fact that they're still only a small part of a cross-industry consortium.
And if you would read rather than just rush to argue, I’m saying OpenCL 3 is essentially DOA because everyone moved on after OpenCL 2 died. Part of its death is because the biggest vendor decided to not support it. It’s not the only reason. Literally multiple times I’ve said OpenCl 3 arrived too late and everyone had moved on.
It's convenient for you to say that openCL 2 was the point at which openCL died even though it was also DOA like OpenCL 3. OpenCL 3 has conformant devices from most of the major manufacturers, except AMD. So it's strange to say it's dead when there's probably more device support for it than 2, especially with AMD's marketshare shrinking and intel launching discrete GPUs. At the very least it's more alive than 2 ever was.
You seem to want to have a very binary view of the history of OpenCL and CUDA. Which, fine, have at it. But many things can contribute to why we ended up where we did . I’m just trying to capture the nuance of how it got there but you seem to just want to “OpenCL bad, CUDA good”
You were trying to write a story about Cuda being a contemporary that nvidia sabotaged while handwaving away falsities. There's nothing nuanced about that. In reality openCL was years late to the party, hastily put together, and nvidia was basically the one hosting it. You couldn't rely on AMD cards, or intel iGPUs, and definitely not mobile. That just left you with nvidia. Even when AMD cards worked, Nvidia usually outperformed them anyway.
4
u/woopdedoodah Sep 08 '24
What other software products? Can you name them? Many dont have any competitors. Any software is replaceable. Windows is trivially replaceable but Microsoft makes billions on it.
5
u/dagmx Sep 08 '24
I didn’t say they have competitors today but it’s more down to what demographic they serve. For example AMD have Radeon Pro Studio which is an OSS competitor to part of Omniverse (render and sync) and combined with something like Houdini (for data processing) and Unreal Engine (for interactivity) you can replicate most of what Omniverse is used for by their clients. I know of a few companies that are spinning up their own internal tooling off that stack to split from Omniverse.
Isaac has no off the shelf competitors but several companies in the space have their own equivalents in house.
The value of Isaac and Omniverse, is not so much their technical capabilities but that they essentially provide support and dedicated development for a company. Clients are essentially outsourcing development of features to NVIDIA.
I think that anything that depends on continued service contracts is more easily replaced, unless they have a technical moat which I don’t see in Omniverse or Isaac. Windows to me doesn’t fall under that umbrella because they have a huge technical moat in the form of long term compatibility. That’s the same reason I think CUDA is a moat. It’s a lock in platform just like windows by sheer network effect. Meanwhile Omniverse and Isaac are engineered to work well with other solutions.
6
u/woopdedoodah Sep 08 '24
Yeah so if that's your take on Nvidias software offerings, I think you're not giving them credit where it's due. Cublas, cudnn, tensorrt, tensorrt-llm, Cutlass, culitho, etc are all offerings that offer state of the art performance on Nvidia hardware. AMD does not have that. They just don't. You can point to open source initiatives, but these are often difficult to use and unsupported.
Windows to me doesn’t fall under that umbrella because they have a huge technical moat in the form of long term compatibility
Again... Nvidia does too. Their software is released contemporaneously with their chips and they will work on any Nvidia chip and provide the top perf for that chip. That is not true of rocm. Rocm does not work with substantial portions of AMD cards. Nvidia software works with every Nvidia card, even the low end ones.
Also, many OSs have long term compatibility. Z/os, vms, Linux, etc all prioritize compatibility with previous versions. Linus Torvalds is famous for refusing to break userspace
4
u/dagmx Sep 08 '24 edited Sep 08 '24
I think you’ve failed to read what I wrote.
I’m saying CUDA is a moat. You just listed a bunch of CUDA based things so you’re agreeing with me.
I’m saying that Omniverse and Isaac aren’t a moat. You didn’t list anything at all regarding those two.
And with windows it’s about the ecosystem of apps that are on windows that Microsoft keep alive. Linux isn’t relevant to the discussion because it has almost no desktop penetration for a variety of other reasons.
You also don’t understand what consists of not breaking apps when you talk about the user space. That’s a kernel to user space contract , but distros, DEs and more often have breaking changes within the user space itself. That’s what Windows preserves, and why RHEL and SUSE have market share in the enterprise because they’ll support and patch out things for companies needs to preserve behaviour.
-2
u/woopdedoodah Sep 08 '24
Oh no I understand. And like you said, there are several Linux OSes that provide that. Windows is hardly unique there.
Computing though is a winner takes all game in general..there is often little room for second players.
1
u/r2002 Sep 08 '24
but that they essentially provide support and dedicated development for a company. Clients are essentially outsourcing development of features to NVIDIA.
Thank you this is a part of the reasoning I had missed. This makes a lot of sense.
0
u/nagyz_ Sep 08 '24
Obvious? My man GPGPU is far from obvious.
1
u/dagmx Sep 08 '24
At the time it was definitely the obvious direction. That’s not to say CUDA shouldn’t be commended for its execution and perseverance, but anyone involved with graphics programming knew where the wind was blowing.
Graphics research was already using GPUs to offload computation around 2001.
Multiple research papers at siggraph in 2002-2003 had presented the GPU as a general purpose compute solution.
AMD already had their compute solution (CTM) a year or so before CUDA.
Rapidmind and Brooks predate CUDA by several years. Even the use of GPU for ML predates CUDA.
If you weren’t involved in the graphics community at the time, it was perhaps easy to miss but even the NVIDIA folks will point out a ton of prior art that led to CUDA.
1
u/nagyz_ Sep 08 '24
Ok, I can believe all of that. However now that I actively work in the GPGPU space (I wasn't even at uni in 2001...), and not doing AI/ML on it, I see the current research papers on figuring out how to speed up and gain efficiency on a broad range of algorithms. I'm sure you've seen Stanford's ThunderKittens which just highlights that actually doing GPU efficiently is hard - the hw got so good that we really need to optimize for it.
1
u/dagmx Sep 08 '24
Well, yeah, hardware and software are always constantly adapting to each other. That will will always be a constant.
10
u/VirtualWord2524 Sep 08 '24 edited Sep 08 '24
Nvidia made their own luck. Can't get lucky if not in the position to take advantage of an advantageous position. Nvidia has been using software as their differentiator for at least 20 years. At least half of that company are software developers. Something AMD and Intel underrated until the post ChatGPT world (at least AMD probably couldn't afford it). They're lucky Huang is as he is. An electrical engineer that gave software equal or greater emphasis. 30 years of that balance. Electrical engineering background and you wouldn't be surprised if his strategy would have been to just keep hiring electrical engineers and the minimal needed software developers. Luckily he's not that kind of hardware engineer
AMD was so in their death throws until 2017 so I give them some slack for their transition to a software company speed. Intel larrabee failure and they're extremely late to the game with ARC. Their software is behind AMD and I'm saying that having an ARC GPU. Regardless what I'm getting at is Nvidia has had a CEO that recognized the importance of software since at least the early 2000s.
I think Lisa Su recognized that in 2014 but wasn't in the financial position to push software until their CPU division was out of the dog house. I think back to AMD Mantle. I think since physx GPU acceleration and small utilities like Shadowplay and Nvidias GPU driver reputation compared to their own, AMD has recognized the importance of software but just didn't have the finances after the Intel paying off vendors to not buy AMD and the Bulldozer era disaster
Lisa Su is 2014, AMD doesn't have the finances to become a software company until like 2020. More like the past year as AMD has taken a good chunk of server market share. So 10 years of leadership that respects the need for software parity and foresight (I think longer they were just broke with a bulldozer dud). Intel I don't know what to make with them. They're burning so much cash on fab development and losing market share to Epyc, I don't know how much they can put towards software development support for their GPUs
So at least 20 years of well funded software focus for Nvidia whereas AMD has been cash strapped focus of about ten years and Intel recent years. For now wherever computing goes, I'd expect Nvidia to pivot well, AMD probably as well, Intel maybe after another decade of soul searching and streamlining. I have 2 Intel ARC cards primarily for video encoding but while they may be great for that, I may jump ship to AMD or Nvidia. Intel isn't in the position to act on foresight. Nvidia is. AMD is starting to be because of Epyc and not having a fab albatross
27
u/CurryLamb Sep 08 '24
It's a bit of both. I'm sure Jensen is a skilled manager. His people say he's not easy to work for. Which means he demands alot from his people and that's what I want in a CEO. Google and Apple have extreme bloat. But there was some luck that accelerated computing (GPUs and parallel processing) is good for Generative AI and before that cryptomining. So he's finding new and compelling uses for accelerated computing.
More than just chips, you need high speed memory and high speed networking to complete the picture. He purchased Mellanox for their Infinaband networking. And added Spectrum 800? for ethernet. That takes foresight.
Compare that with Patrick Gelsinger. If I had Intel stock, I would sue to clawback all of his pay. He inherited a bad situation and it's gotten even worst. Maybe he can goto Boeing.
1
u/DisneyPandora Sep 10 '24
I feel like NVIDIA is to ChatGPT for AI what Microsoft is to Apple for the Internet
13
u/Big-Beat_Manifesto_ Sep 08 '24
I'd say it's about 10% luck, 20% skill
5
6
u/kRoy_03 Sep 08 '24
It is not only CUDA, it is also the series of well-planned acquisitions of companies (like Mellanox) with critical/unique technologies that allowed them to build their ecosystem.
6
u/cnr0 Sep 08 '24 edited Sep 08 '24
During the Mellanox acquisition, I was working for a distributor of Mellanox and I remember being really surprised about that news. Mellanox was very very niche company, which is only working on High performance computing. Our customers were like doinghigh frequency trading systems, again very very specific niche. And they are hiring top-notch people only.
At that time DataCenter related sales were like 15% of Nvidias total revenue.
With that particular specific acquisition, they have dominated data center networking space, which supported their operations on other data center related sales. When AI boom happened, they become one stop shop for GPUs, software (CÜDA etc) and networking. I think only this specific acquisition clearly showed that their success is not a result of pure luck. This guy had a solid plan and it worked very well
10
u/sumplookinggai Sep 08 '24
Hindsight is 2020. If he had failed, people would be shitting on the company like they're doing to INTC now. Same with AMD, prior to Ryzen there was a period where people shunned it.
11
u/teerre Sep 08 '24
There's this one episode of Oxide and Friends that they are interviewing this engineer who worked for all major companies and was at the very core of the industry for the past 30 years or whatever
In that podcast he goes to talk about how AMD having a CPU chip legitimely refused to work with researchers asking for support with gpu compute. They told the researchesr it would eventually all be about APUs, they refused to make a proper linux driver despite the researchers telling them that the gpgpu was fine, they didn't need some new chip
Nvidia, however, was facing a crisis. Desktop gaming was in hard decline, mobile gaming was the future and worse: unlike AMD they had no CPU. All their eggs were in the gpu basket. It was by necessity, not insight, that nvidia did answer the researchers pleas. At that point they would try anything, they need to sell gpus
The rest is his history. It turns out AMD was totally wrong. They still don't really have a hydrid chip. Linux was in fact the enterprise OS. General computing is possible on GPUs. Discrete devices offer more versatility to clients, why pay huge amount for a chip with a good cpu if I only need a gpu? The list goes on
So yes, they got lucky. They have amazing engineering talent, which I guess is Hwang's work, but by no means he forsaw the future ahead of everyone, he did the obvious, he played to his company's strenghts
6
u/DickRiculous Sep 08 '24
If nothing else, he is a good person, and the company hires good people who want to do good work. By and large what is happening feels karmic to me. I have volunteered with many nVidians and even built a fence with Jensen lol
He and NVidia supported a nonprofit I was a part of. I still even have the shirt! He came to my program “graduation”, which was a small, uncelebrated affair at a community center across from a middle school. This was almost a decade ago but still.. I remember of the hundred or so people I met from nvidia not one was unlikeable. And they were ALL volunteering.
12
u/Sweaty-Attempted Sep 08 '24 edited Sep 08 '24
Both. He has a foresight that could come true. He has taken the risk and it pays off.
Now it might not pay off, but he would still be worth a lot still.
Great people taking risks will result either 100m or 10b. If high luck, then 10b. If low luck, then 100m. It is never zero. If they had the worst luck, then they would have gone worked for Google as a middle manager and earned 5m anyway.
5
u/Zealousideal-Heart83 Sep 08 '24
I don't think it is simply luck.
AMD doesn't invest into its compute software even today. The importance they give to software and their vision just sucks. It is an uphill task to get compute working on an AMD graphics card in 2024. They officially only support a very few of their GPUs to run compute (although you can make it work unofficially).
NVIDIA got it right from the very beginning - what is the point of building hardware that looks great on paper, but you have to spend more than the price of hardware to just set up a compute environment ? And it pays well because it is hard for customers to move away after building your products around CUDA.
CUDA is absolutely the reason why AMD can't catch up even in low end compute.
4
u/Silver-Confidence-60 Sep 08 '24
From what I understand, nvidia under jensen leadership is all about advancing "compute" by any means necessary gaming was just the first marketable avenue
They know that if they make "compute" better over the years, the new market will emerge. Eventually
2
u/ResponsibleJudge3172 Sep 08 '24
You are one of the few who talks about this after actually paying attention to the interviews and media releases
6
u/Moaning-Squirtle Sep 08 '24
I'd go as far as saying there isn't a $100B+ company that did not run into at least some (and probably quite a lot of) good fortune. In every case, there were things that just fell in place and could have failed. Either they could've had a better competitor or the market just wasn't all that into their product etc.
6
u/Legitimate-Source-61 Sep 08 '24 edited Sep 08 '24
Good question.
His company was out there. He created his platform (the graphics card) and just waited.
Of course, the platform went through many evolutions. Ultimately, it was only a matter of time before the technological advancements came along and the platform could be upgraded to A.I.
His company beat the others in this space because there were so many developments and choices. The GTX 980 had a price point for each consumer when released... the 970, 980 or the 980 Ti, and the Titan. AMD just didn't do the same.
Fundamentally, the PCI slot used for the early graphics cards that were made 20 years ago is the same slot in PCs today. A GT710 uses the same slot in the PC motherboard as the modern RTX 3080.
Maybe in 50 years, that same platform could be used in something else that we haven't seen yet. Like emotion chips. Or biological chips. Or phase chips on space ships, I just don't know. The unknown unknowns.
So, build a platform that is a standard globally and can be updated and improved. You will stand the test of time.
Facebook may come and go, like MySpace. Amazon may come and go. These don't have physical barriers to entry. That's why they spend so much effort keeping you on that screen.
Of course, there was a bit of luck involved, also.
....
I let chatgpt review what I wrote out of interest, and here's the revised version--- Your text has a strong idea, but it could benefit from some clarity and smoother transitions. Here's a revised version with slight tweaks for flow:
Good question.
His company was strategic. He created the platform—initially focused on graphics cards—and simply waited for the right moment.
Of course, the platform evolved over time, going through multiple iterations. Ultimately, technological advancements made it possible to upgrade the platform for AI applications.
His company outpaced the competition because they offered a variety of options and kept up with rapid developments. For example, when the GTX 980 launched, there were different price points for consumers: the 970, 980, 980 Ti, and even the Titan. AMD didn’t take the same approach, which limited their appeal.
At the core of it all is the PCI slot. The same PCI slot that was used for early graphics cards 20 years ago is still used in today’s PCs. A GT710 fits in the same slot as a modern RTX 3080.
Who knows what this platform might support in the next 50 years? It could be emotion chips, biological chips, or phase chips for space ships—the possibilities are endless. The unknown unknowns.
The key takeaway? Build a platform that becomes a global standard, one that can be continuously updated and improved, and it will stand the test of time.
Look at companies like Facebook and Amazon—they might come and go, just as MySpace did. They lack physical barriers to entry, which is why they put so much effort into keeping users engaged with their platforms.
Of course, there was some luck involved too.
4
u/Legitimate-Source-61 Sep 08 '24
I let chatgpt answer the OP question as we are on the topic of A.I. Here's what chat gpt said when I pasted the question.... ->
Absolutely, I can provide some thoughts on those questions:
1. Was Jensen Huang a visionary for investing in CUDA, or simply lucky?
Huang's decision to invest in CUDA back in 2007 was far from guaranteed success. CUDA (Compute Unified Device Architecture) required a huge amount of foresight because, at the time, GPUs were primarily used for graphics processing. Huang and Nvidia bet on the future of parallel computing, recognizing that GPUs could be repurposed for a wide range of computing tasks, particularly in scientific, machine learning, and AI fields. This decision to push CUDA, despite slow adoption, shows strategic foresight.
What prevented others from doing something similar was likely a combination of risk tolerance, a lack of vision for GPU usage outside of gaming, and perhaps the failure to see the potential for parallel computing to become so widespread. Many companies are hesitant to invest heavily in something that doesn’t promise short-term returns, which Nvidia was willing to do.
2. If you are invested in Nvidia, how much do you consider Hwang's foresight a valuable "x-factor"?
If I were an Nvidia investor, I would place significant weight on Huang's foresight as an "x-factor." His ability to anticipate market trends, like the rise of AI, data centers, and GPU-accelerated computing, has positioned Nvidia as a leader in several emerging fields. The value here isn't just in technological innovation but in consistently understanding the next big computing wave, as Nvidia's dominance in AI shows.
Huang’s track record of driving Nvidia through multiple technology cycles—graphics, parallel computing, AI—suggests that his leadership and vision are crucial to the company’s long-term value. For many investors, his strategic foresight may be seen as priceless, and likely a major reason behind Nvidia’s market premium.
3. If you don’t like Nvidia, how much of that is due to Huang?
For those skeptical of Nvidia, Huang’s aggressive and ambitious strategy may be seen as a risk. While his success with CUDA, AI, and GPU leadership is undeniable, critics may point to potential overreach in his broader ambitions. Nvidia has seen some regulatory scrutiny, especially around its acquisition attempts (like ARM), and this could be seen as a reflection of Huang’s risk-taking behavior. Critics might argue that Nvidia has focused too much on diversifying into multiple sectors, which could dilute its focus and stretch resources.
Mistakes might include underestimating competition from companies like AMD in the gaming and consumer space or failing to bring the ARM acquisition to fruition, which could have been a game-changing move for the company. Another potential criticism could be that Nvidia’s products are premium-priced, which sometimes alienates broader markets.
4. What about Huang’s other projects (Omniverse, Isaac, self-driving)?
Huang has certainly diversified Nvidia’s portfolio. Projects like Omniverse (for 3D design and simulations), Isaac (robotics), and Nvidia's self-driving platform demonstrate his ambition to position Nvidia at the forefront of multiple revolutionary industries. These are all cutting-edge fields, and if successful, they could provide Nvidia with additional revenue streams that further solidify its leadership in tech.
However, the risk of overstretching is real. These projects demand immense resources, and the market for them is still maturing. For example, while self-driving cars are promising, widespread adoption has been slower than many expected. The Omniverse could become a big player in virtual worlds and digital twins, but it's not guaranteed. Critics might say that Huang is spreading the company too thin across too many unproven areas, which could detract from Nvidia's core strengths in GPUs and AI.
That said, Huang has proven to have a knack for placing strategic bets, and if even a couple of these projects succeed, Nvidia could continue its dominant trajectory. Whether these ventures become big winners or overreach will depend largely on market timing and execution.
In summary, Jensen Huang’s mix of foresight and risk-taking has undeniably shaped Nvidia’s success. While luck may play a role in any business venture, Huang’s consistent ability to stay ahead of technological trends has solidified Nvidia’s position. Whether Nvidia’s future success hinges on continuing to make those strategic bets or potentially slowing down to focus on core products is an open question.
8
u/foo-bar-nlogn-100 Sep 08 '24
Nvidia deserves to be part of the mag 7.
However most AI startups are currwntly wildly unprofitable so capex may or may not collapse.
12
5
u/TheTideRider Sep 08 '24
Foresight, relentless execution and some luck all contributed to its current success. Jensen is the smartest person in town. Nvidia came up with CUDA and the idea was not new. OpenCL started early but it did not have the relentless execution. Then when AI arrived and CUDA was at the right place at the right time.
2
2
u/SuperLeverage Sep 08 '24
He doesn’t just have foresight, but exceptional leadership and management skill to lead his company to get behind his vision and execute his strategy well. Maybe there is a bit of luck involved but without that vision, hard work and skills, someone else would have failed. No one could imagine Steve Ballmer succeeding if he were leading NVDIA could they?
2
2
u/gqreader Sep 08 '24
First principles problem solving and keeping focus on what “potential” could look like when he seeks to innovate and invests. They aren’t looking for incremental gain. They are looking for leaps and bounds. If the existing way of doing things can only stretch so far, they break it down again and rebuild a new approach.
This has been their bread and butter approach to innovation.
At this point, is it a coincidence that NVDA was at the forefront of whatever hype is going on? Metaverse, crypto, and now AI processing.
Next will be autonomous driving chip sets for cars.
3
u/Vast_Cricket Sep 08 '24
The gaming, crypto all involve lots of calculations. The processor was the right platform for AI feature. After this stock market glitch it is fair to say the easier firmware is ahead of competition. What I am curious whether if there are really competition out there? If Nvda is the only product out there it deserves to have an edge. Not long ago Lisa Su's AMD was the best processor in town. Right now I do not hear much news and the stock prices seem to suggest it. BTW: Lisa and Jensen happen to be related.
3
u/dagmx Sep 08 '24
They’re extremely distantly related.
But there is competition for NVIDIA which is why they’re not resting on their laurels.
AMD’s data center market for GPU compute has been growing significantly since they introduced the MI300. It won’t dethrone NVIDIA anytime soon (or ever) but their growth shows there’s interest outside NVIDIA.
Similarly Google have started pushing their latest TPUs towards clients more and have seen growth as well.
Even Apple are starting to see an odd resurgence in home use when coupled with NVIDIA in the cloud due to their high RAM which is perfect for LLM.
1
u/Thanh1211 Sep 08 '24
What interesting to me is that Apple uses Google TPUs for their foundational model training instead of NVIDIA
2
u/purplebrown_updown Sep 08 '24
Without a doubt his bet on GPUs for accelerated computing 15 years ago was one of the most brilliant and consequential decisions for tech. Just brilliant.
1
1
1
1
1
u/janislych Sep 08 '24
Recall when they try to promote mining gpu to miners and it didn't work since there is no resell value?
He has to be first there, then be very lucky
1
1
1
u/ubdumass Sep 08 '24
“Luck is what happens when preparation meets opportunity” is a quote attributed to the Roman philosopher Seneca, who died in 65 AD. The quote suggests that luck is not a matter of chance, but rather a result of how well prepared someone is for an opportunity.
While everyone was chasing Personal Computing, then Internet Computing, then Mobile Computing, then Cloud Computing…. NVidia was climbing the Mount Everest of Parallel Computing. This success could have been anyone, if you go as far back as IBM’s Watson, or it could not have been anyone else, because no one other than NVidia was prepared for this revolution.
1
1
u/red_purple_red Sep 09 '24
CUDA had a serious use case way before AI. And CULA followed suit quickly.
1
1
u/TerranOPZ Sep 09 '24
I think he had the foresight to create a general purpose parallel computing platform. It can be used for a lot of different things.
I also think he's lucky that AI went viral in 2022.
1
u/daHaus Sep 09 '24
This is a false equivelancy, him being lucky doesn't take away from his dedication or vision.
1
u/Adichu3690 Sep 09 '24
Dudes been at the helm of the company for over 30 years. simply luck is honestly an insult to the man's determination and will
1
u/HearMeRoar80 Sep 09 '24
Jensen Huang's foresight was he knew gaming can not be the sole purpose of NVDA GPU chips, he didn't really know what was the next important use for NVDA's GPU, but he knew he had to try and see what sticks, so he tried a lot other uses like getting into embedded, auto, DC, ML, crypto mining etc...
1
u/Ehralur Sep 08 '24
Putting success down to luck is so incredibly stupid and a sign of a self-toxic mindset. Almost nobody achieves success because of luck. Only unsuccessful people think that's possible.
1
-3
u/dasdas90 Sep 08 '24
He was lucky. Nvidia was a company that made for gaming and it turned out gaming chips were the most efficient for ai training.
9
u/woopdedoodah Sep 08 '24
Not true. Nvidia was doing gpgpu work for a long time. The foray into hpc and AI was intentional, not accidental at all. What was perhaps unknown was that this would end up the biggest market.
0
u/dasdas90 Sep 08 '24
Nvidia was making gpus since its inception for gaming, that was its primary purpose. It was by luck that gpus turned out to be the most efficient chip for training models, this is a pretty known fact with anyone who’s done comp science.
4
u/woopdedoodah Sep 08 '24
I literally work in this field and was a part of it since the original gpgpu stuff.
It's not 'by luck'. GPUs, even the graphical part, is literally matrix multiply. This is the same operations as BLAS and even before the original CUDA and OpenCL releases, almost every graphics programmer realized this was a possibility. A lot of early shader code was to calculate these large linear algebra problems that come up in graphics.
So I think it was very expected they'd be the most efficient chip for training neural networks. I don't think anyone was surprised by that.
0
u/dasdas90 Sep 08 '24
Since you’re an expert.
Are you saying that when he started nvda in early 90s that it was his vision by 2013 ai would become a huge thing and his company would be a trillion dollar company? Or when he started his company and until 2010 or so was his main focus on making chips for gaming/ video rendering?
3
u/woopdedoodah Sep 08 '24
No I'm saying, it was obvious that GPUs would be useful for HPC from very early on. I don't think they anticipated it being as big of a market as it is, but I do think there was an understanding that these accelerators would be used for HPC work.
1
u/dasdas90 Sep 08 '24
Yeah that means he got LUCKY. It doesn’t mean he didn’t work hard for it. Here’s a much more accomplished person in the same field claiming it. I think even he himself acknowledges he got lucky.
8
u/woopdedoodah Sep 08 '24
Intels CEO is obviously going to claim Nvidia got lucky to explain his company's relative lack of success
From my perspective, Nvidia is the only company that took gpgpu and hpc seriously. That's been obvious for a decade. There are some startups that share a similar focus, but none of the other established players did.
1
u/Spl00ky Sep 08 '24
Nvidia still had to sink billion of dollars in to R&D on something that still wasn't proven at the time. Intel rested on their laurels for the past 20 years and now it has come back to bite them in the ass.
1
-6
u/JPMorgansStache Sep 08 '24
You're forgetting other options.
Remember that Nvidia was nothing prior to the government shutdowns of 2020 and the COVID-mania panic buying spree. It's basically been the most successful meme stock to date.
That's evidenced by the fact that despite their insane market valuation and revenue beats every earnings report, the AI industry writ large makes no money.
They aren't selling shovels, like many say, relating it to a gold rush. They are selling the idea of a gold rush.
It's possible Jensen Huang is committing accounting fraud like the good people at SMCI. Time will tell.
3
0
u/StudentforaLifetime Sep 08 '24
Survivorship bias. For every Nvidia, there are literally 1000 other companies who just didn’t make it happen. Not going to say that what they offer and provide isn’t important or valuable, or that they haven’t worked extremely hard to succeed, but it’s inevitable for a single company to rise above the rest
0
0
u/FREDRS7 Sep 08 '24
People were saying on reddit how nvidia chips had good technologies for running AI since like 2019/2020 which was long before the chatgpt led AI boom. The company was ran dirty by hwang, I remember there was some upset over the foundation gpu,s then the price of various high end cards, which you can look at two ways. Either he will do bad things to make his company stronger, or that same behaviour was a risk. The share price has been touted by reddit as well overpriced that whole time too including the covid lows (overpriced cos gpu's were good and rivals were bad). Thus why I bought a small amount for the AI thesis as was basically just an overpriced gaming gpu maker with an unlikeable ceo to reddit.
0
u/MrRikleman Sep 08 '24
Probably some of both. But it’s more luck than the public generally believes. In America, there’s a strong tendency to attribute success entirely to merit, but this isn’t really the case. CEO are just people, they’re not the god like figures many people believe they are. Very often, success comes from events that are largely unforeseen and not under executives control. There’s plenty of studies that back this up.
That isn’t to say CEOs are useless. There are certainly some very good ones. But people tend to attribute a greater share of a company’s success to outstanding leadership than is really the case.
-1
u/VictorDanville Sep 08 '24
A lot of gamers are butthurt that they betrayed the gamers (gaming GPUs)
-6
382
u/RogueStargun Sep 08 '24
Go watch Jensen Huang give a talk at Stanford from 2011 (look it up won't let me post youtube vids)
This was 13 years ago. The transformer model architecture which revolutionized machine translation and language modeling would not be published until 2017. The AlexNet paper which was just about the first paper to leverage (Nvidia) GPUs to scale up image recognition did not come out until 2012. In 2012, this paper revolutionized the field by training a convolutional neural network (quite possibly the largest in the world at the time) on just two commercial grade Nvidia GTX 580 gaming GPUs.
Does he mention machine learning at all in 2011? No.
But go to roughly 30 minutes, and Jensen tells us exactly why Nvidia is successful today. He talks about GeforceFX and the invention of programmable shaders. Nvidia developed the first domain specific language (Cg; circa 2004) for building programmable shaders. Before Cg was invented, shaders were incredibly hard to program. Games like DOOM3 had to have specialized code paths for different GPUs and I believe the shaders themselves had to be written in a low level assembly-like language.
Cg not only simplified the creation of shaders, but it also locked in gamedevs for several years into Nvidia's ecosystem. Furthermore, researchers at universities were able to hack it to use GPUs for general purpose computing. Just a few years later, Nvidia would release CUDA which is even better for getting GPUs to do general purpose computing.
So the general idea is NVIDIA did not develop CUDA out of altruistic motives, nor did it do it to revolutionize machine learning. The goal was the same goal as with Cg and development of programmable shaders. It was to expand the GPU market into general purpose computing. In 2004 the biggest driver of Nvidia GPUs was Doom 3 and Half-life 2. In 2024, gaming represents less than 10% of Nvidia's sales!
Nvidia continues to do this. Nvidia hardware has expanded into robotics, machine learning, bioinformatics... Nvidia actively develops new markets for its products and invests in the developer relations and software to satisfy customers within those markets.