Huh? Nvidia got lucky. First with crypto, then covid and then AI. I can give them credit for CUDA, because that was a true example of long term thinking, but to say they saw AI wave coming.. that is a stretch.
Nvidia has been powering the AI(ML) progress for the last 10 years and it's because they have the best hardware/software combo for processing vectors. There's nothing lucky about being continuously dominant in a space (GPUs) for 15+ years.
Hard disagree. Like with everything, there are multiple factors at play, but at certain size, decisions almost don't matter, because there is no one to upset the apple cart.
As a counter, look at MS, they have been around for more than 10 years and there is plenty of luck, hubris, good decisions, bad decisions that did not matter, because they effectively held a dominant position.
Well in that particular case they became dominant in the gpgpu space because they had a vastly superior offering ( cuda ), which they then capitalized on, while their competitors produced inferior products. I read my first gpgpu papers around 2005 I think , but the one company that ran with it was Nvidia. I don’t see this as luck.
Once you are dominant though, you can stay that way for a long time.
We disagree, but that is ok. I am admittedly a little biased against nvidia. FWIW, your arguments are good. I think here it is a matter of perspective on what constitutes luck.
This is true, but they’ve been lucky because a gigantic new market appeared which is very friendly to their hardware ( and they make sure it is like you said ). That market could also never have happened at all.
Well it could have happened but have required a non gpu-friendly architecture, it could have happened in 80 years from now and nvidia be long gone, etc.
So from their perspective, it wouldn’t have happened at all. But I understand my comment was ambiguous.
No that doesn't make sense because NVIDIA physically built this field with their own hands. So there's no way it could have "not happened" or "not been GPU friendly" lol.
Gpgpu dates back to the early 2000s, and it happens that deep learning as a computational problem is very well suited to GPUs.People figured this out around 2012-2013, and just like with cuda a few years before, nvidia figured out there was a huge market for them, because the underlying compute problem was well suited to their hardware.
Ai could have used different models which are not computationally friendly to gpus ( or may not even require a lot of computational power ) and nvidia wouldn’t have been so successful at ai, much like intel’s cpus are not well suited to current deep learning models.
I remember discussing with friends in the hpc community what was going to happen to nvidia - we were wondering how they could grow their compute business. And bam, massive compute needs for ai, problem solved.
"Could have not happened" means without hindsight, you could see the possibility that it might not have played out.
nVidia didn't know for a fact that deep learning architectures would have been so successful in the past couple years. GP's point is that maybe deep learning would have worked 80 years later, and not have the great breakthroughs around 2016~now.
The video from 2015 proves nothing. nVidia was deeply invested into this bet by then, and the mere fact that the video exist is evidence that they already betted heavily on AI by 2015 -- before the big results we know of today came about.
People worked on ML more than forty years ago. In fact, very little has changed in terms of ML. 90% of it is still the same. Using different activation functions and network architectures, etc that happened in the last ten years doesn't change the fundamental idea. What you are saying is so incredibly wrong it has to be in bad faith. There was always going to be a market for machine learning accelerators, the question is merely how big. ChatGPT et al merely change the calculus from profitable to extremely profitable.
No, Nvidia just found themselves in a lucky situation.
They were already building GPUs mainly for gaming. Crypto then came along and swiped up a bunch of GPUs. When the self mining craze somewhat waned the AI craze started as the boundaries on its ethicality were broken down in an uncertain economic environment where corporations started racing to see who will get to the top.
You are right. Even more interesting, is the timing itself:
The crypto craze waned just as LLMs were picking up. Any more delay with LLMs, and perhaps nvidia would have been overextended with no demand to take their inventory. There may in fact , be no nvidia in that future depending on the level of the bet.
Or take it 1 step further . if COVID hadnt happened, the crypto craze would never have occurred, and nvidia would have only been a bit-level player in the LLM craze we are now in.
I still remember nvidia ads in pc game magazines. That and 3dfx. Who knew?
How are you pinning the crypto craze to COVID? People were mining long before 2020, and that demand was so high putting pressure on GPU inventory that the manufacturers were artificially crippling their performance when used as miners.
Crypto prices really took off when speculation went thru the roof due to govt "stimmies". Look at the increase in $ nominal pricing of non-standard crypto (everything not BTC, ETH, xmr), the largest upward move recorded in history will be the period 20-22 in the aggregate
NFTs at 100K , etc.
Thats the "craze"
Before that it was still a speculative play, but hardly pervasive and available to so many.
As Seneca is said to have quipped- “Fortuna est quae fit cum praeparatio in occasionem incidit." or "Luck is what happens when preparation meets opportunity.”
Nvidia has been doing the hard work in preparing to succeed in this market. CUDA has been meticulously developed and maintained, creating an adhesion to their hardware that would not otherwise exist in the AI market.
It also has been willing and capable of creating lines of business hardware aimed at maximizing utility for their customers.
They also have hired and maintained a roster of the best engineers in their specialties, including the software part of the equation.
There is no part of their success that they weren't prepared to take advantage of when the opportunity presented itself. They didn't control the size of the opportunity itself, but no greatly successful company does.
Nvidia in the past made only GPUs, CUDA is used to program GPUs and get use out of them. It doesn't take any magical foresight to want to invest in CUDA, it is the most obvious way to expand your TAM.
AMD does not just make GPUs, and pre-2008 their resources were spent on their fab, post-2008 they simply had no resources. They did not need to expand the TAM, just try to increase their revenue share. CPUs did not need the same level of investment for return.
> pre-2008 their resources were spent on their fab, post-2008 they simply had no resources
this underplays the AMD board refusing a merger with NVIDIA (because jensen wanted to be CEO of the resulting company and hector ruiz didn't like that), and then overpaying for ATI and leaving themselves depleted of funds.
Bulldozer/etc could have gone very differently if they hadn't been broke and forced to underinvest. They might not have ever been in the position of "consoles having to carry them" if they had simply done a merger-of-equals with NVIDIA, or if they had simply walked away from the graphics market afterwards instead of rushing to buy ATI.
A lot of people just can't bring themselves to admit that good decisions had a large role in putting NVIDIA where they are today, and that bad decisions had a large role in putting AMD where they were in the late 2000s/early 2010s. It wasn't just bad things happening to AMD - the bad things happened because of bad decisions, they were consequences of actions.
People overfixate on the Intel thing as being the root of all of AMD's woes, as opposed to the other 75% of the problem that they could control. Like hector ruiz was just an utter disaster all around, not just even this one thing. And even today, AMD does discounts/rebates for bulk purchases. And the best rebates come if you buy all of your hardware from them (and thus, none from your competitor) - same as Intel did, which is why the decision was eventually significantly reduced. The eventual finding was - like many things, it may or may not be anticompetitive, depending on how you use it - but volume rebates and even outright exclusivity agreements are not inherently illegal in the way AMD fans generally imply they are. Ask Pepsi.
Matrox and 3dfx never came close to making general purpose GPUs, they just got completely outcompeted in the regular PC graphics market of the late 90s. Matrox and 3dfx last tried to compete on architecture in 2002 [1] and 1999 respectively, while the first GPUs capable of general purpose computing were released many years later at the end of 2006 (by Nvidia) and mid 2007 (by AMD/ATI). High performance GPUs have been a completely Nvidia and AMD/ATI affair for two decades until Intel entered the fray last year, since before people even conceived of GPGPUs.
Matrox and 3dfx were gone before they could even conceive of a general purpose GPU strategy.
[1]: The Matrox Parhelia itself being out of date tech on release to boot, lacking a Direct3D 9.0 class architecture that ATI launched two months later.
This. Jensen (Nvidia CEO) is being a bit humble here given the massive investments the company has made into CUDA for the past decade. Now they're simply reaping the benefits. Sure, ChatGPT's arrival last year was the spark but arguably it was inevitable sooner or later.
Case in point: Nvidia has been hosting "GPU Conferences" annually to build awareness and drive adoption of CUDA. These events surely aren't free to host but necessary to build momentum and give an edge to your custom stack.
Luck is more applicable to the cryptomining boom and bust cycles that Nvidia also profited from. Their gaming GPUs (along with AMD's) just happened to be the best available at the proof of work.
and yet, if they had chosen to go in a different direction they wouldn't have been ready for ML/AI.
The point isn't that they didn't invest in the direction that ended up being right, it's that they didn't do it specifically with ML/AI in mind years before it was even a twinkle in google's eyes.
> No, Nvidia just found themselves in a lucky situation.
Well yes and no. They were certainly lucky to be at right place in the right time. But they were also consistently investing into CUDA and the AI/ML ecosystem while their competitor(s) ignored it to such an extent that NVDIA became the only real option (and deservedly so).
This is why they can effectively behave like a monopoly these days and just almost inconceivably high margins.
IIRC were on CUDA 5 or something when imagenet came out and changed the world.
They might not have imagined LLMs when they decided to invest in making their GPUs programmable but I guarantee you they extrapolated the future compute potential of vector programmable machines and decided it was not a huge risk to enable it as it is simply betting that some important application would be around to tap into it.
Didn't even need to extrapolate future potential. The world of supercomputing was massively sunsetting the old vector processors (Cray, Sparc etc.) and switched to commodity x86 hardware back in that timeframe when CUDA came out. Perfect opening for a new vector processor on steroids, for which the chip development was already payed by gamers...
IIRC people were already converting their data into texture maps and writing their SIMD instructions as shaders operating on those textures before Nvidia released CUDA.
you're missing the software part, which is essential to this story. Nvidia was the only GPU maker betting the farm on positioning for GPGPU/HPC all the way back in ~2007. What is happening now and since the last couple of years is just payoff for that massive R&D and software maintenance cost they've been fronting. They bet big and won big.
I think that's oversimplifying things. The acquired podcast has covered Nvidia's different growth periods in depth. I highly recommend anyone interested to give them a listen:
Chalking it up to dumb luck is kind of ridiculous. They invested massively in developing an ecosystem for GPU driven computing, which was a well reasoned gamble, and it paid off.
>I'm a great believer in luck. The harder I work, the more of it I seem to have.
Nvidia has been working hard(er than their competition) on the software side for almost 2 decades to be in the position they find themselves today. 16 years ago, they released CUDA for general-purpose computing on GPUs, and then 9 years ago they followed that up with cuDNN. They have a consistent pattern of making a intentional, long-term bets to diversify their market exposure and unlock new product areas while building a software ecosystem moat.
Yes, they obviously got super lucky with the cryptocurrency frenzy, but there's a reason all the miners were mostly buying Nvidia cards instead of AMD cards.
Yeah, I'm going to be honest: I'm a cryptocurrency doomer so I've not followed things super closely, but a quick Google search turned up this article[0] from 2022:
>While it is true that Nvidia cards are generally preferred by miners due to better price-to-performance, AMD GPUs such as the Radeon RX 6600 XT could still be mined on profitably until recently. […] So yes, carefully consider the condition of all used graphics cards—Nvidia or AMD.
Yes, they bought any supply they could get their hands on. Also, it's not true that Nvidia cards were generally better for (Eth) mining. The Radeon VII for example outclassed Nvidia cards sold at the same time. It's just that Nvidia was able to supply more cards, since they had won the bigger gaming marketshare a while ago and thus were producing more.
If it was pure luck why did they build CUDA over a decade ago?
Think you're just looking at this from the angle of a gamer and not someone who's been paying attention to GPGPU compute earlier than the past 6 months.
Then this luck should have equally found AMD, who even today are struggling to pick up the ball they've been dropping for a decade now. My last PC had a Radeon, and I waited the life time of that PC assuming AMD support was just around the corner, all the while renting Nvidia cards in the cloud for any serious projects.
I've been in the ML space long enough to remember when people were just speculating about doing ML/computation on GPUs. Nvidia made that much easier and has continued to improve support and features for the past decade+ There insane success is certainly part luck, but I wouldn't be so quick to dismiss all of it as merely happenstance.
I'm watching nvidia researchers doing a TON of AI at a wide spectrum, that your 'lucky situation' is a hard understatement what nvidia is doing on Research & Development area.
Not really. They did push CUDA and GPGPU on their own hardware while AMD and Intel offered a barely functional OpenCL. Of course they had no idea about how big AI and crypto would become, but they were there offering their cards to whoever wanted to run calculations on them.
No, Nvidia has spent considerable resources to support ML for I think a decade now? They certainly got lucky in the crypto craze and of course the timing of AI off the failings of crypto is extremely lucky but you are wrong in the rest of the argument.
No, Nvidia decided to change their GPU architectures to be more suitable for neural networks, so they did have to bet that this shift would have to pay off. They spoke to many leading AI experts and came to this conclusion. They should be commended for the risk they took. If Nvidia solely ended up being "lucky", then how come AMD didn't take off?
Because they were broke and didn't have the resources to invest properly even if they wanted to.
That's not quite true -- they bet the farm on Zen, and that bet paid off. Which means that now they have the resources to also invest in AI. I'm fairly sure if they had bet the farm on AI instead of Zen or if they had tried splitting that bet they'd be bankrupt now.
> In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs. Ian Buck later joined NVIDIA and led the launch of CUDA in 2006, the world's first solution for general-computing on GPUs.
This timeline seems completely wrong to me. Nvidia’s cudnn has been the only game in town for NN research since I have been in the field, and predates ethereum and the crypto bull run by a few years. If anything they didn’t waver and jump too hard on the crypto bandwagon when the craze was at its height.
It wasn't luck. For example, the book "Good Strategy/Bad Strategy" has a chapter about the NVidia strategy in its early days. You'll find a lot of similarities to what happened with CUDA.
In its early days, NVidia focused on its delivery speed by having a unified software driver/integration strategy. The TNT video card was meh, the TNT2 a little better but inferior to 3Dfx... by the time they launched GeForce, 3Dfx didn't have a product ready to compete. Their driver/integration/product test strategy made that speed possible.
With that background you can understand why CUDA wasn't lucky, they repeated the same approach: combine their hardware with the software.
Don't forget the "Artificial Intelligence and Japan's Fifth Generation [Project]" [1] launched in 1982. Bad timing ;-). Wikipedia includes a specific page [2]. Finally, we cannot forget Transputers [3].
I clearly remember AI becoming a big tech subject in the late 2000s/early 2010s following the release of CUDA on consumer hardware, around the same time as Bitcoin and much before GPU-mining was a thing.
No, Nvidia was not lucky. They are a strong engineering culture who also has deep marketing expertise in 3D in all its facets for decades .
Nvidia wisely recognized that only so much horsepower could be used by a conventional 3d graphics pipeline with a given screen resolution, and they needed to invest in growing future compute-heavy adjacent markets.
They invested in generalizing their GPU into a more flexible vector coprocessor for HPC and then adjacent markets. They convinced fundamental engineers and researchers in this area to come work for them.
There was deep fundamental work done by Ian Buck in 2004 on leveraging GPUs as general vector processors ( https://graphics.stanford.edu/papers/brookgpu/ ) and that leadership and deep thinking went to Nvidia, not to Intel. Intel did not have the passion from the top to care about this. They couldn't even care enough to field competitive 3D chips (and associated software), much less extend their thinking to generalize beyond it skillfully. Nvidia did.
Anyone who spent every day thinking about how to grow the vector coprocessor market would have pursued crypto and AI when they came along but Nvidia's strong engineering and profits from a leading 3D position gave them competitive advantages which they are, for now, reaping.
Still seems like they were in the right place at the right time. When they first developed Cuda it was a hammer in search of a nail. Then they had the huge windfall from crypto-mining. That probably led to a lot of discussions on looking for GPGPU opportunities. Then AI came along and Cuda was just sitting there.
Then they put two and two together and started investing heavily as they saw momentum build.
>Then they put two and two together and started investing heavily as they saw momentum build.
There's been a decade or more of deep learning models breaking records in almost every single research field, powered (indirectly) through CUDA, cuDNN and other NVIDIA software.
AI didn't "come along" when OpenAI released ChatGPT. DNNs that have been 99% NVIDIA-focused have been beating the state-of-the-art for years and years.
Also for the record the ADA architecture (very dominant AI accelerator) was released when the stock price was like $100 (compared to the $500 now).
You could say that, for commercial purposes, AI actually did land with ChatGPT. It existed long before that, but that was unquestionably the event that started diverting billions of investment dollars into AI applications.
I don’t think what you’re saying disagrees with my point. NVidia saw the momentum in AI research building long before ChatGPT arrived. AlexNet came out in 2012 and drew a ton of attention back then.
Sorry, my points are rather disorganized since I just woke up this morning, but I think Nvidia CEO's claim of "betting the farm on AI" is questionable.
The chronology is this:
2007: CUDA released
2012: AlexNet (which runs on CUDA) turns heads and everyone (in the research world, not the public) starts getting really excited about AI
2012-2021: NVidia invests in CUDA while getting carried by gaming and crypto
2022-2023: AI explodes into the public consciousness and NVidia valuation balloons to absurd levels
Now, I don't think anyone can argue that NVidia was not smart to build CUDA. What no one would have predicted was how important it would turn out to be back when they started. It was more like "hey, these gaming devices are pretty good at matrix/vector math, let's build an API for people who want to do that" and then it turning out that AI is all matrix/vector math.
The point is that all of NVidia's investment in CUDA and AI was subsidized by the gaming and crypto cash cows. They didn't have to "bet the farm", they just had to keep it going as a side project and increase their investment as they saw the momentum build.
As the article implies, they were lucky and good. I was surprised how quickly they were able to implement Tensor cores and head off alternate architectures.
Lot of things were happening before you started paying attention to it. GPGPU definitely wasn't just there being useless before crypto and AI didn't just "Come along" after crypto.
CUDA has been heavily utilized for AI for many many years now, whole reason Nvidia is so entrenched in it is because they were they only ones taking GPGPU seriously like OpenCL (1) rose and was abandoned before we even get to your interpretation of the timeline.
(1): Easy to forget now that AMD and Apple had an common standard competitor to CUDA and completely fumbled it.
When they first developed CUDA, they did not yet have that huge of a windfall from crypto-mining. It was first released in June 2007. I would say it was more of the result of seeing initiatives of ham-fisting general-purpose computation onto graphics-specific API like OpenGL and such.
Honestly, who would have ever thought that a shitty, squashed, artifact laden, completely fake frames that don’t mean anything architecture would win?
Personally, I didn’t think it would, but the power of a small number in the top of your screen beats facts for most people. And here we are I guess.
But there’s also the problem that AMD drivers are STILL shit. This is 20 straight years of poor drivers. Something tells me that if AMD would just get their software act together, the DLSS train may not have taken off the way it did. You do see a lot of comments that the drivers haven’t been bad for a while, but anecdotally, they definitely are.
I'm almost certain this refers to DLSS which uses "AI" (DLSS means Deep Learning Super Sampling) to generate a higher resolution output frame from smaller resolution renders by combining data from multiple frames over time using various AI approaches (i'm not exactly sure how) and, as of DLSS 3, being able to interpolate frames asynchronously from the rendering so that it can double the framerate.
The process is not perfect and can introduce various visual artifacts, which are especially visible at lower monitor/output resolutions and the artifacts are more likely to occur when the render resolution is also much lower than the output resolution. These two also feed into each other as in general cheaper/weaker hardware (where the lower render resolutions would be used) tends to be paired with lower resolution monitors (where the artifacts would be more visible). I guess the "shitty, squashed, artifact laden" comes from there.
DLSS 3 doubles the framerate by interpolating frames in the GPU (so the game doesn't "know" about them and player input isn't handled), hence "fake frames".
It doesn’t “double” anything except a number in the corner of your screen.
The frames you’re getting are not based on gamestate, so they’re just fake placebos. This is why it’s curious to me that gamers by and large have completely accepted DLSS to the point that they’re actually completely okay with losing rasterization perf as long as a numbers in the corner of their screen is sufficiently faked.
DLSS doesn't mandate frame generation (added in DLSS 3) it can still be used to upscale without frame generation, and indeed this is how DLSS 2 works as it had no frame generation.
Even in games supporting DLSS 3, there is to best of my knowledge and experience almost always a separate configuration option to turn frame generation on or off, allowing you to use DLSS solely to render non-"placebo" frames and upscale the output.
This absolutely allows you to run at a lower internal resolution, get higher "real" FPS and enjoy a reasonable upscaled output image. Sure it won't be as dramatic a difference as with frame generation, but it doesn't have the drawbacks of non-gamestate frames either. I've found DLSS for upscaling (without frame gen) fantastic frankly for getting older Nvidia parts to run new games for budget conscious gamers who don't have hundreds or thousands of dollars to drop on a new 30xx/40xx part.
Supersampled images are nothing new. I am specifically discussing the fake frames, which is what Nvidia advertises with (imo this is bordering on straight up lies).
Nvidia did slap “Hurr durr AI driven” buzzwords in front of theirs, but supersampling exists super far back. As far as gaming goes, supersampling was probably popularized in super old emulators, particularly zsnes.
Sure, but the quality of DLSS (and AMD's FSR2) has generally been much better than previous super sampling solutions, and this is borne out in virtually all independent testing of the feature. Supersampling algorithms in old emulators are not great in comparison.
The drivers have been fine for years now, anyone using a current or previous gen knows it, the only reason people think they are still bad is because people are still parroting it.
Unfortunately this isn't true. They're certainly better than what they used to be, but they are no where near as reliable as Nvidia's. We tried a build out roughly 6 months ago and we couldn't switch back fast enough.
Are you talking about windows GPU drivers for gaming? I haven't had problems on Linux in a long time and I am honestly surprised with how many hours I have spent gaming on Linux with Proton.
As of 2 years ago, which saw similar “the drivers are fine now and have been for a couple generations”, they are anecdotally not okay.
Way more crashes. Way more weird bullshit (like audio disappearing????) that just doesn’t happen when you run an Nvidia card.
“AMD drivers are fine now” has lost all meaning. I will continue to give them a chance now and again, but it’s based on keeping competitive up, not on the drivers being good now.
Others explained it, has less to do with age, and more whether you are (were) a PC gamer.
Crysis came out to huge fanfare due to it's impressive graphics. However even the highest end spec'd PC's had trouble running the game at a stable frame rate at high settings--iirc because the game's engine (cryengine?) was not well optimized.
Crysis performance became a benchmark for PC's, and then the joke phrase "But can it run Crysis" started, used seriously when discussing PC hardward specs, and jokingly used for unrelated hardware "This printer has 24bit color?" "But can it run Crysis?"
I think kids these days definitely will understand this ancient and cliche joke. Its not like its some unkown twencen joke it gets said everytime nvidia comes out with the newest gaming behemoth cards
To say that the AI craze started after the crypto wave died down is disingenuous or misinformed. The future need for GPU's was apparent as soon as machine learning became relevant a decade ago. The effectiveness of transformers, rnn's, q-learning, etc, for language and other applications was not news when GPT-3 launched. NVidia invested heavily for 10 years, including funding research towards ML and AI, and steered the direction of the technology that we have today
The article mentions this choice being made in 2018. I don't know the ML industry, but as a gamedev I had been mystified about Nvidia's strategy since about 2018.
It felt like they weren't leaning into crypto, which surprised me. Instead it looked like they were trying to maintain gamer goodwill by not increasing consumer card costs during the boom. Of course scarcity raised secondary market princes, but Nvidia kept MSRP lower than the boom dictated.
It seemed like they were betting against crypto during the craze. And sticking to their strategy on the consumer side. So maybe that's how they stuck to a ML strategy too.
So they had all this CUDA stuff, which they must have invested in heavily because AMD showed what happens when you don't. That led to a software ecosystem for ML.
Maybe it was all luck, but a strategic choice explains some of this in hindsight.
> So they had all this CUDA stuff, which they must have invested in heavily because AMD showed what happens when you don't. That led to a software ecosystem for ML.
CUDA was already digital gold in 2018. ML had moved to GPUs several years prior, and CUDA was a primary enabler of that transition.
Nvidia had already been through one crypto bust at that point. The long view was that there will be another one and they wanted to keep their more stable markets viable for the future and not get demand slaughtered by mass dumping of used cards on the market when crypto dipped again.
Of course, the AI thing exploded afterwards this time so the demand dip didn't happen.
> Instead it looked like they were trying to maintain gamer goodwill by not increasing consumer card costs during the boom.
They've been selling mid-sized GPUs like the GTX 1080 at 800$ 8 years ago. A 300 mm2 GPU.
They have been rising and rising costs for a long time to milk as many dollars as they could.
People seem to forget even before the crypto craze the company had insane margins in their revenue. They weren't selling 800$ chips because those costed 600 or 500$ to produce...
Even the most expensive 4090 is hardly more than a 400$ chip, memories included to build.
Always a divide between people in these threads who assign pure genius as the sole reason for success and those who live in reality and accept that you also need allot of luck and cash on the way.
Yeah. I can absolutely believe that NVIDIA saw the potential for GPUs (and associated software) that went beyond hardcore gaming nerds building their own PCs. But HPC generally was not a very profitable market for most vendors and I don't really believe that crypto and LLMs as they have played out to date was especially foreseeable at a detailed level.
I think forum post quality probably is well in decline when posters start making popular meta posts about how people with their view are in reality and people without are delusional.
It was an observation of how every thread like this plays out not a “popular meta post”. I wouldn’t go as far as to say delusional I was more going for it’s naive to assign success purely to genius in the same way it’s naive to attribute a single cause or solution to climate change. In fact I think even that’s generous given that’s a future prediction that was not a guess or a gamble. Perhaps a better example would be for me to write a post about a massive successful stock trade or crypto where A) I had the cash to do it and B) things I gambled might happen went even better than I thought. There would be people assigning all the success to me when likely there were other similar plays I made that I lost big on as well as plenty of other people who saw it but simply didn’t have the means or timing to make it happen. So yes I think it’s naive to assign this and most to purely genius. You need a little luck and cash in reality on the way.
Actually, a GPU is not the best kind of hardware for AI (or rather, neural network simulation). It's very well-developed, and more useful than a CPU, but one could design and construct more NN-sim-oriented hardware. NVIDIA have been forced to do this somewhat, cannibalizing some of their more general-purpose compute capabilities in favor of matrix-multiply-add functionality (i.e. "tensor cores"). That's not exactly the "GPU way" of doing things. And one could go every further, perhaps all the way up to some analog computations instead of digital low-precision ones.
There's a natural compromise between "Efficiency" and "Flexibility" - training AIs is currently a fast enough moving field that by the time the really efficient targeted hardware could be released, the state of the art has moved to make them less suited to the latest generation.
Outside of training, using the trained network for inference seem to be changing less, so maybe a decent target for bespoke targeted hardware. And indeed it seems that custom hardware blocks are very much "catching favor" in that market - everyone seems to be adding accelerators to their SoCs.
GPUs seem to be at a happy medium, where they're often flexible enough to run techniques while still having better efficiency than a CPU.
I have to admit I regret not buying their stock. It should've been obvious this would be a boon for them, but I got distracted by the crypto hype and didn't even think about the impact AI would have on them.
True story, decades ago in HS we did the whole stock market competition. As a big gamer, I somehow convinced my team to dump everything into Nvidia.
We were 2nd in the state in Illinois, and I wanted to cement our place and possibly win by selling everything to lock in gains in the final week. The person executing the trade on our team accidentally shorted it and it went up a considerable amount in the last week knocking us down quite a bit.
At that point I seriously considered dumping my savings into Nvidia. I'd be retired right now if I had done so.
They'll also benefit from the boom on the graphics side as well.
Once gen AI gets good enough to generate high quality video games, virtual worlds, etc. in real time, that will redefine gaming and entertainment.
Why wait for the next Mission Impossible movie to come out when you can experience it...as Tom Cruise...with your own storyline with all of your friends. And get a new one every day.
I agree, but the art (e.g. what a good author does) comes from the structure, of which thousands of combinations could be created. Gen AI would then be able to endlessly fill in details for unique variations (different characters, locations, allegiances, time periods, decision trees, etc.).
Think about any good story. A million details could be different, and it would still work well.
And role-playing games have shown us the way to have a curated overarching story while still enabling player agency. Many of those principles will apply to Generative Cinema.
The current expectation that movie studios or the Hollywood machine will somehow be diminished by GenAI is misguided. If anything, it will normalize $100 movie rental "experiences" you can enjoy at home with no additional hardware besides your smartphone and a cast-enabled TV, with everything rendering real-time in the cloud.
You know what may be an interesting way for full immersion in 3D/AR - would be a Subnautica (SCUBA) style AR game. Because you would have 360 of movement, and critters could be projected through the water for you to fight, but youre actually wearing scuba gear... and being pulled around by an underwater "speederbike" with a laser.
I think AIs work loads match what GPU does too well, some luck in it for sure but credit them making Cuda nice and early and doing bigger bets on AI than anyone else.
Investing billionS over the course of CUDA and its predecessors. The whole concept about wanting to use GPU for not just Graphics but High performance or Highly parallel computing started before 2000s. CUDA announced in 2007, and most of the work predate back to Cg in early 2000s. Even Intel who were already very late to the party made the decision to go invest and start Larrabee in 2005. And there was PS3 Cell, which started development in 2001.
And yet all these work and success from Nvidia was because of, if you read 90% of HN comments for the past 2 years; Luck.
They could have given up at any point in time for the past 20 years and simply not do anything CUDA or GPGPU related. Because who would want to do that when vast majority of those investment were not even bringing in much revenue. Like Intel decided to cancel Larrabee. They persevere and hit the Jackpot some 10-15 years later. But all of this was because of; Luck.
Yes. Luck plays a big part. They could have continue another 10 years and they may never find the Killer App for it. But to ignore all the investment and work for such a long time and pin it down to Luck was about as rude and as disrespectful it can be. Especially on a forum which was started by VC with the spirit of entrepreneurship.
It does help to have billions to invest. AMD in the last 20 years was basically broke and they bet the farm on Zen. If they split their limited resources between Zen and CUDA they probably would have failed at both.
But their Zen bet has paid off and now they're playing catch up.
IMHO, Intel lost a couple of years because the CEO had a consensual affair with a subordinate so they fired him and put the CFO in charge for a while and puttered around unable to fix the serious process manufacturing problems getting to 10nm they encountered which caused them to fall behind in manufacturing to TSMC. Finally, after a few years of little progress, Gelsinger was hired, and we'll see what he can do.
If the process worked out Brian wouldn’t get fired, probably. The affair was very convenient for the board.
Intel had grown accustomed to internal mediocrity and got too big to root it out; the fact that accounting runs the company instead of someone with a vision doesn’t help. Accounting doesn’t like risky bets and Intel needed some to work out instead of cancelling everything left and right.
It seems pretty possible to me that the reason Nvidia pulled off this bet is that Jensen still basically unilaterally controls what NV is working on, and Jensen is still fundamentally a nerd (in the best way).
>It does help to have billions to invest. AMD in the last 20 years was basically broke
You're making it sound like AMD being broke at that time was some unfortunate accident due to external events, and not the result of their own blunders.
Nvidia had billions due to great products and great business decisions on their part, and AMD was broke entirely due to it's own actions, by having average products on the CPU side and making bad business decisions at the time by spending way too much money acquiring ATI, and then selling off their golden goose, the Imageon mobile GPU division to Qualcomm for pennies right at the beginning of the smartphone revolution.
It's a miracle they managed to turn things around and not end up like SGI and 3dfx, bankrupt and having their carcass devoured by Intel and Nvidia.
Maybe what happened to Intel is what happened to GE under Jack Welch.
Edit: just saw the CFO put in charge reference in other comment. There's your answer: financialization of the company.
This is likely a testament to the need for large tech companies to choose core differentiated competencies, and consistently invest in those competencies over long periods of time. It's so tempting for the finance minded to take a large high margin business like NVidia and cut R&D spending to boost profits. Or alternately allow the R&D spend become lazy and ineffective - This happened to Intel, Boeing, and arguably Google.
That NVidia has maintained this push for the last 2 decades makes one wonder what other tricks they'll have up their sleeve.
I don't see that there is enough value there to motivate the investment.
For games, to the extent that VR works for them... sure, I could see that use case. But for, say, business meetings? Uh, no. Or to hang out with friends? Sure, maybe, but how would they monetize it well enough to make the investment worthwhile? To make it compelling enough that I would visit?
I'm not saying that the use cases don't exist. But either making compelling VR experiences has to be cheap[1] (which I don't see on the near horizon), or they have to add enough value that people will pay for them in some way. That strikes me as uncertain.
[1] If they get cheap, then sure, although then it will have the same problem CGI now has... there is so much of it that it has lost a lot of its magic. It's hard to be common and compelling.
>I don't see that there is enough value there to motivate the investment.
People were saying the same about home computers in the '70s and it was relatively true for that period if you didn't look into the future and only considered what home computers looked like back then: janky machines built from radio shack parts by nerdy enthusiast tinkerers with electronics knowledge. Only when they were presented with prebuilt and polished products with usable apps that didn't require technical knowledge, did people see the light that home computers are the future and will become mainstream for all consumers not just enthusiasts.
Nobody can know yet how mainstream VR will look like exactly and who will get to dominate the field and dictate the product direction (Apple, Valve, Meta, etc), but for sure it will happen in the future, even if for now it's just a tinkering toy for gamers and enthusiasts with money.
There is a major difference: VR can't work the way sci-fi enthusiasts envision it for fundamental physical reasons.
You can't have a pair of glasses that is simultaneously opaque enough to give you the illusion you are in another place AND breezy enough so that your eyes won't sweat. Air is just much bigger than light, so you can't block light but allow air to pass through. So a VR headset will always be sweaty on the face. AR will never be able to create realistic opaque backgrounds.
You also can't have a holo-deck-like experience with glasses. The only reason the holo deck captures our imaginations is because it had space, smells, sounds, touch. All of those things are impossible to achieve with physical devices of any kind, or at least very close to it. The only thing that may create a holo-deck like experience would be based on brain-computer interfaces, if those are even truly possible.
Finally, to get many of the claimed benefits, even if the headsets were good enough to deliver them, you also need complex recording software that actually handles all of this. You can't have a nice realistic image of all of your colleagues in a VR meeting unless they each have a 3D camera setup, and everyone has enough bandwidth to actually receive and send all of the 3D videos, and do so with latency similar to audio traffic.
These are at least three fundamental problems that make the whole VR/AR craze just certain to fail. Again.
>The only reason the holo deck captures our imaginations is because it had space, smells, sounds, touch.
You don't need the exact fictional holo deck device to have a VR product that sells. 150 years ago Sci-Fi writers imagined we'd have robots in our homes doing our chores, and we do have them today, except not humanoid robots doing the washing and vacuuming by hand for us like we originally imagined, but we have fixed function dedicated robots for each task: dish washing machine, clothes washing machine, Roomba robo-vac, etc. They're a rudimentary and limited far cry from the fantasy and capable humanoid robots in sci-fi novels, yet they're ubiquitous today and sold by the millions. Same will be with VR, it will be more limited than the holo deck but it will sell at the right price/feature combo.
>You can't have a nice realistic image of all of your colleagues in a VR meeting unless they each have a 3D camera setup, and everyone has enough bandwidth to actually receive and send all of the 3D videos, and do so with latency similar to audio traffic
People also fantasized about video telephony like in star trek and yet those challenge got overcome with the introduction of 3G and camera phones and has improved ever since. Tech will also improve for VR. The iPhone already has had a 3D camera since a while now.
>These are at least three fundamental problems that make the whole VR/AR craze just certain to fail. Again.
It will fail today, but it will succeed in the future, even if you're too dead set to not see it.
>but we have fixed function dedicated robots for each task: dish washing machine, clothes washing machine, Roomba robo-vac, etc
But we don't have a clothes folding machine, precisely because the task is infinitely harder, from a first principles view, than anything a futurist imagined. VR/AR is the same. It's not just scaling up computer power because it's a matter of not having the physical ability to manipulate reality, energy, and matter the way we need.
Science isn't magic. How do you do haptic feedback to hands? That's an essential part of any AR system that isn't just a gimmick, and yet it's basically impossible without clunky gloves. How do you prevent damage to the human eye over extended use like a 9-5 job? The human eye did not evolve to "look at" different things that are in actuality on a screen an inch from our eyes, it really upsets the brain and the muscles that control vision, which is why VR/AR can be so tiring on your eyes. That cannot be innovated away.
>How do you do haptic feedback to hands? That's an essential part of any AR system that isn't just a gimmick, and yet it's basically impossible without clunky gloves.
Who said VR would need gloves and haptic feedback to succeed? We're talking about virtual reality here, not simulated reality. For the latter better wait for Elon's neural link or whatver we'll get that plugs our brains into the Matrix and simulates reality.
People still use mice and keyboards to interact with UIs despite having the ability to use touchscreens. Just because one thing exists, doesn't automatically mean the other dies.
>How do you prevent damage to the human eye over extended use like a 9-5 job?
Who said you need to use a VR device from 9-5 for it to succeed? You don't stare at your phone screen or tablet for 8h/day, do you? And yet you most likely have one.
> The human eye did not evolve to "look at" different things that are in actuality on a screen an inch from our eyes
Have you seen what lenses can do with light? Like move the focal point of a picture much further away? They're pretty big tech in cameras, telescopes, binoculars, and .... oh, these optical things humans wear on their faces, a couple of cm from their eyes to fix their vision issues, their called glasses I think.
How about we use those lens thingies to move the focal point of a screen that's 2cm from your eyes to 2m from your eyes? I'm telling you dude, whoever invents this tech is gonna be big.
Replying here, but with conflicting thoughts reading this whole comment chain..
I really liked immersive VR I experienced in research lab settings like CAVE systems, over 20 years ago. I'm probably among the people most tolerant to artifacts like frame rate jitter and lag, and most easily able to still get an immersive pop out of it. But I'm not an early adopter. I don't see the value or place for this single-purpose equipment in my life, nor my budget.
When mobile phones were just phones, I saw them getting smaller and lighter. I even fantasized about them shrinking until it was just the ear bud. I was willing to hand-wave some sci-fi UX without a display nor buttons. But, I didn't (and still don't, really) appreciate how people would care to get wireless ear buds that are still slaved to a larger device. I'd still be satisfied with wired ear phones if they were available.
I also didn't imagine today's smartphone ecosystem, even though I saw all the PDAs and other pocket computing platforms and their general purpose potential. I didn't predict the social/marketing angle that was going to make any of this seem worthwhile to average consumers. Now, I benefit from these economies of scale making the tech affordable, but I barely need it. I still prefer going to a laptop or desktop for any "real" tasks. Ironically, a smartphone ir tablet makes me feel frustrated and "mute" without a keyboard.
I understood the idea of convergence and the general purpose device. I understood the mobile/always on value and was on the early side of wire-cutting to have only a mobile phone. But, I was surprised at how rapidly the smartphone ate up digital camera and personal video camera markets. I am still surprised at how much smartphones are eating into spaces like regular laptops and PCs. And now the entire concept of a phone seems to be disappearing, with traditional voice calls being less relevant as time goes on.
So I am a fence-sitter on some kind of N-dimensional fence. I admit that a lot of tech development might occur and I probably can't guess which ones get popular. Maybe there is some VR/AR angle that will finally catch on.
But on the more general topic, I also think that all these developments above had many other passionate developers and ventures working on slightly different angles that failed in the market. As a third-party observer of decades of tech, I do also think it's a lot of luck. It is survivorship bias to fixate on how NVIDIA or Apple or anybody had some perfect strategy to ride these big waves.
> You can't have a pair of glasses that is simultaneously opaque enough to give you the illusion you are in another place AND breezy enough so that your eyes won't sweat. Air is just much bigger than light, so you can't block light but allow air to pass through. So a VR headset will always be sweaty on the face. AR will never be able to create realistic opaque backgrounds.
You can have a fan that pull the air in or out of the inside of the glasses without any light ever coming in.
> Air is just much bigger than light, so you can't block light but allow air to pass through.
That seems easy to fix - small tubes/vents that don’t go straight through but hit a corner or big enough curve. Air can go around obstacle but light won’t.
nVidia at least has a product to show for it. Meta has Horizon Worlds and what? I guess the Quest headsets are included? It’s hard to figure out what Meta spent all that money on.
Yes, they've shipped tens of millions of headsets across the world.
> It’s hard to figure out what Meta spent all that money on.
R&D on every problem for XR. Their software side is mediocre, but what Reality Labs is working on for hardware is unparalleled by any other company, even Apple.
There is definitely both luck and uncertainty with regard to R&D. If you don't look, you won't find it, but looking is not a guarantee.
In the case of AR/VR, I think there are two issues that make payoffs uncertain: 1) the hardware would have to get much cheaper; when will that be? 2) What is the killer app that would motivate the (large) expeditures required to produce compelling virtual environments? Games is an obvious case, but games are a very different beast than online meeting rooms -- the whole action/reward cycle of games isn't likely to work for business meetings. It isn't really clear that VR adds enough value to be compelling for non-gaming apps.
But it could easily be true that we just haven't imagined the right use case. You won't find it if you don't look.
I feel there’s always such a thing as paying too much, and Meta has a bit of a moat problem because I don’t think much stops somebody like Google from making a direct competitor to Quest.
Still I think people REALLY underestimate this space. First gaming has an outrageous TAM and VR games are GOOD. Second AR has an even bigger market, and I’ve realized that it’s not just about giving us all a HUD to walk around with, it’s also going to about having an AI assistant get information in the environment around us with a camera.
Sometimes boosting profits and dividends is the right play if the company isn’t set up to innovate. Innovation isn’t for every company and it’s good that some boards focus on redistributing profits.
Re: Intel, it's worth mentioning their Phi coprocessor board. They zig-ed when they should have zag-ed. The Phi essentially had thousands of i486 CPUs on it, but apparently that isn't as useful for ML because (apparently) it's all about the FLOPs, whereas the less-mathematical but more logical Phi cores could do (something?) better?
I just think it's an honorable mention because had things gone a little differently, perhaps Intel could have been king of the hill instead.
Intel didn't just miss by a little, they missed by a lot. Nvidia has more software engineers than hardware engineers. Building the software ecosystem is the thing that makes the whole thing work. Intel didn't just have the wrong product with Phi, they had a product with no ecosystem. It was impossible to develop for. None of Nvidia's competitors have a serious answer to the ecosystem problem. Its not clear that Intel has even ever understood this.
Intel has had more software engineers than hardware since forever. They know the ecosystem argument in and out - they made x86, they are the argument.
They lost the process lead and can’t figure it out for almost a decade now - we wouldn’t be having this discussion if their hardware worked out according to their plans.
> Nvidia has more software engineers than hardware engineers. Building the software ecosystem is the thing that makes the whole thing work.
One thing I never see people discuss in the context is that from the beginning NVidia drivers were closed source while Intel drivers were open source. If you don't see software as a competitive advantage that obviously limits the resources you can invest in it. Linus Torvalds said "Fuck you, NVidia" but who's fucked now?
> success from Nvidia was because of, if you read 90% of HN comments for the past 2 years; Luck.
Never once read a comment attributing Nvidia success to luck.
The only luck Nvidia has is the luck that AMD fell asleep at the wheel and couldn't get bothered to put more than 2 engineers on a CUDA competitor even when it was getting apparent that AI was worth billions (i.e. ~4-5 years ago).
which means they had reasons for doing what they did and found themselves well positioned for ML/AI but that those reasons were not specifically ML/AI.
You have to keep in mind that for a long time concurrency was thought of as the only way to keep getting increasing performance out of CPU's, what they invested in is massive concurrency and when ML/AI hit they were well-positioned for it due to their investments in massive concurrency.
I think it is obviously true that they have worked hard and built great devices. That was evident even when they only sold products for gaming. But this is what most companies do, or try to do: take their core products and invest in making them better. CUDA was impressive but not shocking.
When people say it's luck, I think they are reacting to the reality that Nvidia couldn't know, when they were doing this investing, that there was a big AI market waiting to take off. They were doing good work, but they were also very, very lucky that circumstances granted them this opportunity. There is no shame in that -- few companies achieve great success without some opportunity manifesting.
But it's a mistake to pat yourself on the back too hard, either. Without the opportunity, they'd still be making gpus with some other applications.
As you note, the "luck" debate often bogs down into a false dichotomy of extremes when the reality is usually in-between and complicated. In my experience, most people (and companies) have the opportunity to encounter approximately similar amounts of "good" and "bad" luck, when averaged over the long run. However...
* This is gated by the ability to recognize those opportunities when they appear, willingness to act decisively to maximize the probability of positive outcomes and the preparedness to exploit such advantages. This tends to require mental preparedness, emotional maturity and a willingness to invest scarce resources and/or time - in advance - toward maintaining situational awareness and some excess reserve resources. Doing this is hard but these traits are learnable.
* Similarly, a portion of available conscious effort and scarce resources must be continuously expended toward being resilient to bad luck when it inevitably strikes. The net impact of misfortune can vary substantially depending on mitigation steps taken in advance. This requires accurate awareness of ambient risk factors and careful balancing of where you choose to place your limited 'air bags' and 'ounces of prevention.'
Most of these things are at least somewhat within your ability to influence, with the exception of initial conditions. At the "opening deal" of life some people are dealt better cards and some people are dealt worse cards. This is not fair, but it is what it is. The silver-lining is that, after the initial cards are dealt, it can still be a long game with many rounds. How you choose to play the cards you have in each of those rounds can lead to substantially different outcomes. Because it's a game like poker with randomness, hidden variables, subtle cues and second-order probabilities - it's easy to conclude it's almost all luck. This is unfortunate because not understanding the 'meta' of the game, or even knowing there is a meta, does make it mostly luck for some.
I think NVidia's 'good fortune' is the cumulative result of playing the meta-game effectively for a long-time and thus leading to them having the capability to maximize their outcomes when eventually finding themselves in a high-opportunity environment (aka "lucky").
not luck, but the idea that they predicted the ML/AI renaissance 10-20 years out is laughable considering it was google that kicked it off because google had big data and showed it could be done.
They had their reasons for doing what they did and I'm sure they eventually realized they were well positioned for ML/AI, but there's no way they planned that out before ML/AI was a viable thing.
believe it or not they did predict it 10 years out, NVIDIA bet the farm on AI/ML after seeing AlexNet. This has been covered in other articles too.
And sure, AlexNet was good but remember this is the maxwell days, tensor cores aren't even a thing yet, it was at minimum a very bold bet on the basis of "some image classifier model thing". Nobody else saw it as more than an academic toy (obviously, or they'd have jumped in too).
> Within a couple of years, every entrant in the ImageNet competition was using a neural network. By the mid-twenty-tens, neural networks trained on G.P.U.s were identifying images with ninety-six-per-cent accuracy, surpassing humans. Huang’s ten-year crusade to democratize supercomputing had succeeded. “The fact that they can solve computer vision, which is completely unstructured, leads to the question ‘What else can you teach it?’ ” Huang said to me.
> The answer seemed to be: everything. Huang concluded that neural networks would revolutionize society, and that he could use CUDA to corner the market on the necessary hardware. He announced that he was once again betting the company. “He sent out an e-mail on Friday evening saying everything is going to deep learning, and that we were no longer a graphics company,” Greg Estes, a vice-president at Nvidia, told me. “By Monday morning, we were an A.I. company. Literally, it was that fast.”
It wasn't obvious. Otherwise it wouldn't be a bet! Everyone and their dog would want to be deep in the game, like what's going on with LLM at the moment. Nvidia revenue and R&D budget has traditionally been, and still are, smaller compared to Intel. Likely to AMD as well.
The hand wringing about luck can be annoying. Bringing it up is mostly useful to empathize with other people and be humble. Hard work without luck rarely works out. But luck without hard work rarely works out either (unless you're insanely lucky). Never doing anything because "luck" will guarantee you're never lucky.
Use luck to be humble, use luck to empathize, use luck to build people up, but don't use luck to tear people down.
Yes many are very eager to blame the winner, usually without seeing the work that took them there, and even more relevant, the competition keeps doing a mess.
Precisely. And this isn't just about Nvidia either. It is every single topic on successful companies. These sort of discussion are common or the norm on 99.999999999% of internet. But we are on HN, the bar needs to be higher, a lot higher. And I cant accept this without some rebuttal.
At least judging from the upvote it does seems I have the backing from silent majority. All is not lost.
But it has nothing to do with AI, it was an investment in optimized hard for floating point calculations for completely unrelated applications to AI. Not that they don't deserve it. It's great hardware. But it would be a shame for them to tie their business to AI and then there is a huge bust from creditors who realize that LLMs don't really do anything.
Yeah, I wouldn't call it just luck, but I refuse to accept that they saw AI coming and blowing up like that any more than anybody else. It worked out for them that they created cuda (btw how much of that was related to acquiring that company that made physX and the according accelerator card?) and decided to stick with it, improve on it, and supply developers with superb tools. But again, I don't think there ever specifically was AI in that planning. It seemed like a step-by-step thing, provide additional value eg to games with physics simulation that would give gamers a reason to buy Nvidia over ati (as if driver quality alone wasn't already a strong argument ;)).
The wise decision was to keep pushing cuda and not dropping the ball on it to cut costs in the short run, and realizing the potential of using it for scientific computation early on. Then one thing led to another. When AI came around, cuda was the only mature and serious framework for the job.
I wonder what will happen if someone figures out that fused FP mult add is no longer needed (e.g. just count spikes and add subtract permanence). This could be a big problem for the guys with all their eggs in one basket (like NVIDIA).
Once they changed the licensing on consumer gear in a DC it started to become clear they were executing on a strategy, I wouldn't be surprised if phasing out SLI was part of that strategy as well.
I could definitely see them having the foresight to predict that the future would pay good money for a bulk mathematical operations of a certain type. I have trouble imagining them predicting AI specifically, when crypto and gaming were paying the bills so well. If I went back to 2018, I wonder if he'd say they bet the company on bitcoin back in 2012.
the ceo has driven a unique culture as seen in his recent interviews. some of these run counter to prevailing business wisdom: long term projects, hard problems that could build platforms/markets vs easy problems that gain market share
etc..
The catch was they are betting multiple farms. One farm for crypto, another farm for AI, and I'm sure they'll have another farm for another hyped technology.
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[ 5.2 ms ] story [ 222 ms ] threadAs a counter, look at MS, they have been around for more than 10 years and there is plenty of luck, hubris, good decisions, bad decisions that did not matter, because they effectively held a dominant position.
Being dominant equals to luck.
Once you are dominant though, you can stay that way for a long time.
If you’re interested in the early gpgpu work, which interestingly enough worked both on Ati( now amd ) and nvidia hardware.
I agree to disagree :-)
So from their perspective, it wouldn’t have happened at all. But I understand my comment was ambiguous.
Here is Jensen talking about building the industry 9 months before the founding of OpenAI: https://www.youtube.com/watch?v=_iBLoNG0qHk
Gpgpu dates back to the early 2000s, and it happens that deep learning as a computational problem is very well suited to GPUs.People figured this out around 2012-2013, and just like with cuda a few years before, nvidia figured out there was a huge market for them, because the underlying compute problem was well suited to their hardware.
Ai could have used different models which are not computationally friendly to gpus ( or may not even require a lot of computational power ) and nvidia wouldn’t have been so successful at ai, much like intel’s cpus are not well suited to current deep learning models.
I remember discussing with friends in the hpc community what was going to happen to nvidia - we were wondering how they could grow their compute business. And bam, massive compute needs for ai, problem solved.
"Could have not happened" means without hindsight, you could see the possibility that it might not have played out.
nVidia didn't know for a fact that deep learning architectures would have been so successful in the past couple years. GP's point is that maybe deep learning would have worked 80 years later, and not have the great breakthroughs around 2016~now.
The video from 2015 proves nothing. nVidia was deeply invested into this bet by then, and the mere fact that the video exist is evidence that they already betted heavily on AI by 2015 -- before the big results we know of today came about.
They were already building GPUs mainly for gaming. Crypto then came along and swiped up a bunch of GPUs. When the self mining craze somewhat waned the AI craze started as the boundaries on its ethicality were broken down in an uncertain economic environment where corporations started racing to see who will get to the top.
The crypto craze waned just as LLMs were picking up. Any more delay with LLMs, and perhaps nvidia would have been overextended with no demand to take their inventory. There may in fact , be no nvidia in that future depending on the level of the bet.
Or take it 1 step further . if COVID hadnt happened, the crypto craze would never have occurred, and nvidia would have only been a bit-level player in the LLM craze we are now in.
I still remember nvidia ads in pc game magazines. That and 3dfx. Who knew?
Why? They were the only ones taking GPGPU seriously? AMD completely ignored it for years and Intel only became serious about GPUs very recently.
NFTs at 100K , etc.
Thats the "craze"
Before that it was still a speculative play, but hardly pervasive and available to so many.
Nvidia has been doing the hard work in preparing to succeed in this market. CUDA has been meticulously developed and maintained, creating an adhesion to their hardware that would not otherwise exist in the AI market.
It also has been willing and capable of creating lines of business hardware aimed at maximizing utility for their customers.
They also have hired and maintained a roster of the best engineers in their specialties, including the software part of the equation.
There is no part of their success that they weren't prepared to take advantage of when the opportunity presented itself. They didn't control the size of the opportunity itself, but no greatly successful company does.
Tell that to ATI/AMD, and all the now-defunct and also-ran (Matrox, 3dfx) graphics companies.
Matrox is still alive.
Iirc they found a niche in medical device imaging.
What if… you read my comment more closely, and saw it was a parenthetical example after "also-ran" and not "now-defunct".
this underplays the AMD board refusing a merger with NVIDIA (because jensen wanted to be CEO of the resulting company and hector ruiz didn't like that), and then overpaying for ATI and leaving themselves depleted of funds.
(staff writer, not blog "contributor") https://www.forbes.com/sites/briancaulfield/2012/02/22/amd-t...
Bulldozer/etc could have gone very differently if they hadn't been broke and forced to underinvest. They might not have ever been in the position of "consoles having to carry them" if they had simply done a merger-of-equals with NVIDIA, or if they had simply walked away from the graphics market afterwards instead of rushing to buy ATI.
A lot of people just can't bring themselves to admit that good decisions had a large role in putting NVIDIA where they are today, and that bad decisions had a large role in putting AMD where they were in the late 2000s/early 2010s. It wasn't just bad things happening to AMD - the bad things happened because of bad decisions, they were consequences of actions.
People overfixate on the Intel thing as being the root of all of AMD's woes, as opposed to the other 75% of the problem that they could control. Like hector ruiz was just an utter disaster all around, not just even this one thing. And even today, AMD does discounts/rebates for bulk purchases. And the best rebates come if you buy all of your hardware from them (and thus, none from your competitor) - same as Intel did, which is why the decision was eventually significantly reduced. The eventual finding was - like many things, it may or may not be anticompetitive, depending on how you use it - but volume rebates and even outright exclusivity agreements are not inherently illegal in the way AMD fans generally imply they are. Ask Pepsi.
Matrox and 3dfx were gone before they could even conceive of a general purpose GPU strategy.
[1]: The Matrox Parhelia itself being out of date tech on release to boot, lacking a Direct3D 9.0 class architecture that ATI launched two months later.
You could argue they successfully pivoted out of consumer and into b2b.
But they gave up on making their own cores.
https://en.m.wikipedia.org/wiki/Matrox
Hence "also-rans".
What are you trying to argue here?
Case in point: Nvidia has been hosting "GPU Conferences" annually to build awareness and drive adoption of CUDA. These events surely aren't free to host but necessary to build momentum and give an edge to your custom stack.
Luck is more applicable to the cryptomining boom and bust cycles that Nvidia also profited from. Their gaming GPUs (along with AMD's) just happened to be the best available at the proof of work.
The point isn't that they didn't invest in the direction that ended up being right, it's that they didn't do it specifically with ML/AI in mind years before it was even a twinkle in google's eyes.
Well yes and no. They were certainly lucky to be at right place in the right time. But they were also consistently investing into CUDA and the AI/ML ecosystem while their competitor(s) ignored it to such an extent that NVDIA became the only real option (and deservedly so).
This is why they can effectively behave like a monopoly these days and just almost inconceivably high margins.
IIRC were on CUDA 5 or something when imagenet came out and changed the world.
They might not have imagined LLMs when they decided to invest in making their GPUs programmable but I guarantee you they extrapolated the future compute potential of vector programmable machines and decided it was not a huge risk to enable it as it is simply betting that some important application would be around to tap into it.
It was hugely experimental but does demonstrate that the idea of a GPUs being used for compute isn’t a recent one.
What people find contentious is this claim that they specifically did it for ML/AI. That's not why they invested the way they did.
https://www.acquired.fm/episodes/nvidia-the-gpu-company-1993...
https://www.acquired.fm/episodes/nvidia-the-machine-learning...
https://www.acquired.fm/episodes/nvidia-the-dawn-of-the-ai-e...
>I'm a great believer in luck. The harder I work, the more of it I seem to have.
Nvidia has been working hard(er than their competition) on the software side for almost 2 decades to be in the position they find themselves today. 16 years ago, they released CUDA for general-purpose computing on GPUs, and then 9 years ago they followed that up with cuDNN. They have a consistent pattern of making a intentional, long-term bets to diversify their market exposure and unlock new product areas while building a software ecosystem moat.
Yes, they obviously got super lucky with the cryptocurrency frenzy, but there's a reason all the miners were mostly buying Nvidia cards instead of AMD cards.
>While it is true that Nvidia cards are generally preferred by miners due to better price-to-performance, AMD GPUs such as the Radeon RX 6600 XT could still be mined on profitably until recently. […] So yes, carefully consider the condition of all used graphics cards—Nvidia or AMD.
[0] https://www.pcworld.com/article/395149/should-you-buy-a-used...
Think you're just looking at this from the angle of a gamer and not someone who's been paying attention to GPGPU compute earlier than the past 6 months.
Then this luck should have equally found AMD, who even today are struggling to pick up the ball they've been dropping for a decade now. My last PC had a Radeon, and I waited the life time of that PC assuming AMD support was just around the corner, all the while renting Nvidia cards in the cloud for any serious projects.
I've been in the ML space long enough to remember when people were just speculating about doing ML/computation on GPUs. Nvidia made that much easier and has continued to improve support and features for the past decade+ There insane success is certainly part luck, but I wouldn't be so quick to dismiss all of it as merely happenstance.
https://www.youtube.com/watch?v=WLq9zv3k5n0
The race was on, but nobody else was running.
https://www.youtube.com/watch?v=Yhg3IEpl60M
Because they were broke and didn't have the resources to invest properly even if they wanted to.
That's not quite true -- they bet the farm on Zen, and that bet paid off. Which means that now they have the resources to also invest in AI. I'm fairly sure if they had bet the farm on AI instead of Zen or if they had tried splitting that bet they'd be bankrupt now.
Copy-pasting a comment from a discussion a little while[1] ago: CUDA was first released in 2007:
* https://en.wikipedia.org/wiki/CUDA
* https://developer.download.nvidia.com/compute/cuda/1.0/NVIDI...
Two years before the Bitcoin paper (2009):
* https://en.wikipedia.org/wiki/Bitcoin
They had a presentation called "The Era of the Personal Supercomputing" at SIGGRAPH 2007:
* https://dl.acm.org/doi/10.1145/1281500.1281647
* https://www.nvidia.com/content/events/siggraph_2007/supercom...
Ian Buck (co-?)creator of CUDA speaking in 2008:
> Ian Buck talks about his background developing Brook for GPUs at Stanford university and what paths were taken for developing a C platform for GPUs.
* https://www.youtube.com/watch?v=Cmh1EHXjJsk
> In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs. Ian Buck later joined NVIDIA and led the launch of CUDA in 2006, the world's first solution for general-computing on GPUs.
* https://developer.nvidia.com/cuda-zone
* http://graphics.stanford.edu/~ianbuck/
Nvidia purposefully went after parallel computing. Specific applications (cryptocurrency, ML/AI) appeared later.
[1] https://news.ycombinator.com/item?id=38446957#unv_38447944
It is true that they got lucky several times in a big way. But CUDA was an expensive R&D for many years without clear payouts.
It didn't wane, it was decimated when ETH switched to PoS, and off of GPU mining entirely.
All of the other mined coins dropped in value as miners moved to them and dumped all their rewards, making mining those coins unprofitable as well.
It was ETH that was propping up the entire GPU mining ecosystem.
In its early days, NVidia focused on its delivery speed by having a unified software driver/integration strategy. The TNT video card was meh, the TNT2 a little better but inferior to 3Dfx... by the time they launched GeForce, 3Dfx didn't have a product ready to compete. Their driver/integration/product test strategy made that speed possible.
With that background you can understand why CUDA wasn't lucky, they repeated the same approach: combine their hardware with the software.
[1] https://www.jstor.org/stable/26861060
[2] https://en.wikipedia.org/wiki/Fifth_Generation_Computer_Syst...
[3] https://en.wikipedia.org/wiki/Transputer
Nvidia wisely recognized that only so much horsepower could be used by a conventional 3d graphics pipeline with a given screen resolution, and they needed to invest in growing future compute-heavy adjacent markets.
They invested in generalizing their GPU into a more flexible vector coprocessor for HPC and then adjacent markets. They convinced fundamental engineers and researchers in this area to come work for them.
There was deep fundamental work done by Ian Buck in 2004 on leveraging GPUs as general vector processors ( https://graphics.stanford.edu/papers/brookgpu/ ) and that leadership and deep thinking went to Nvidia, not to Intel. Intel did not have the passion from the top to care about this. They couldn't even care enough to field competitive 3D chips (and associated software), much less extend their thinking to generalize beyond it skillfully. Nvidia did.
Anyone who spent every day thinking about how to grow the vector coprocessor market would have pursued crypto and AI when they came along but Nvidia's strong engineering and profits from a leading 3D position gave them competitive advantages which they are, for now, reaping.
Then they put two and two together and started investing heavily as they saw momentum build.
There's been a decade or more of deep learning models breaking records in almost every single research field, powered (indirectly) through CUDA, cuDNN and other NVIDIA software.
AI didn't "come along" when OpenAI released ChatGPT. DNNs that have been 99% NVIDIA-focused have been beating the state-of-the-art for years and years.
Also for the record the ADA architecture (very dominant AI accelerator) was released when the stock price was like $100 (compared to the $500 now).
The chronology is this:
2007: CUDA released
2012: AlexNet (which runs on CUDA) turns heads and everyone (in the research world, not the public) starts getting really excited about AI
2012-2021: NVidia invests in CUDA while getting carried by gaming and crypto
2022-2023: AI explodes into the public consciousness and NVidia valuation balloons to absurd levels
Now, I don't think anyone can argue that NVidia was not smart to build CUDA. What no one would have predicted was how important it would turn out to be back when they started. It was more like "hey, these gaming devices are pretty good at matrix/vector math, let's build an API for people who want to do that" and then it turning out that AI is all matrix/vector math.
The point is that all of NVidia's investment in CUDA and AI was subsidized by the gaming and crypto cash cows. They didn't have to "bet the farm", they just had to keep it going as a side project and increase their investment as they saw the momentum build.
Yes, and it takes lot of effort to be in the right place.
CUDA has been heavily utilized for AI for many many years now, whole reason Nvidia is so entrenched in it is because they were they only ones taking GPGPU seriously like OpenCL (1) rose and was abandoned before we even get to your interpretation of the timeline.
(1): Easy to forget now that AMD and Apple had an common standard competitor to CUDA and completely fumbled it.
Personally, I didn’t think it would, but the power of a small number in the top of your screen beats facts for most people. And here we are I guess.
But there’s also the problem that AMD drivers are STILL shit. This is 20 straight years of poor drivers. Something tells me that if AMD would just get their software act together, the DLSS train may not have taken off the way it did. You do see a lot of comments that the drivers haven’t been bad for a while, but anecdotally, they definitely are.
I'm sorry but what does this even mean?
The process is not perfect and can introduce various visual artifacts, which are especially visible at lower monitor/output resolutions and the artifacts are more likely to occur when the render resolution is also much lower than the output resolution. These two also feed into each other as in general cheaper/weaker hardware (where the lower render resolutions would be used) tends to be paired with lower resolution monitors (where the artifacts would be more visible). I guess the "shitty, squashed, artifact laden" comes from there.
DLSS 3 doubles the framerate by interpolating frames in the GPU (so the game doesn't "know" about them and player input isn't handled), hence "fake frames".
The frames you’re getting are not based on gamestate, so they’re just fake placebos. This is why it’s curious to me that gamers by and large have completely accepted DLSS to the point that they’re actually completely okay with losing rasterization perf as long as a numbers in the corner of their screen is sufficiently faked.
Even in games supporting DLSS 3, there is to best of my knowledge and experience almost always a separate configuration option to turn frame generation on or off, allowing you to use DLSS solely to render non-"placebo" frames and upscale the output.
This absolutely allows you to run at a lower internal resolution, get higher "real" FPS and enjoy a reasonable upscaled output image. Sure it won't be as dramatic a difference as with frame generation, but it doesn't have the drawbacks of non-gamestate frames either. I've found DLSS for upscaling (without frame gen) fantastic frankly for getting older Nvidia parts to run new games for budget conscious gamers who don't have hundreds or thousands of dollars to drop on a new 30xx/40xx part.
Nvidia did slap “Hurr durr AI driven” buzzwords in front of theirs, but supersampling exists super far back. As far as gaming goes, supersampling was probably popularized in super old emulators, particularly zsnes.
Way more crashes. Way more weird bullshit (like audio disappearing????) that just doesn’t happen when you run an Nvidia card.
“AMD drivers are fine now” has lost all meaning. I will continue to give them a chance now and again, but it’s based on keeping competitive up, not on the drivers being good now.
Woah, only one more year and this reference will be old enough to vote.
Pushing the limits of existing hardware, it looked truly spectacular when it came out - and many would say it still does.
Crysis came out to huge fanfare due to it's impressive graphics. However even the highest end spec'd PC's had trouble running the game at a stable frame rate at high settings--iirc because the game's engine (cryengine?) was not well optimized.
Crysis performance became a benchmark for PC's, and then the joke phrase "But can it run Crysis" started, used seriously when discussing PC hardward specs, and jokingly used for unrelated hardware "This printer has 24bit color?" "But can it run Crysis?"
It felt like they weren't leaning into crypto, which surprised me. Instead it looked like they were trying to maintain gamer goodwill by not increasing consumer card costs during the boom. Of course scarcity raised secondary market princes, but Nvidia kept MSRP lower than the boom dictated.
It seemed like they were betting against crypto during the craze. And sticking to their strategy on the consumer side. So maybe that's how they stuck to a ML strategy too.
So they had all this CUDA stuff, which they must have invested in heavily because AMD showed what happens when you don't. That led to a software ecosystem for ML.
Maybe it was all luck, but a strategic choice explains some of this in hindsight.
CUDA was already digital gold in 2018. ML had moved to GPUs several years prior, and CUDA was a primary enabler of that transition.
Of course, the AI thing exploded afterwards this time so the demand dip didn't happen.
They've been selling mid-sized GPUs like the GTX 1080 at 800$ 8 years ago. A 300 mm2 GPU.
They have been rising and rising costs for a long time to milk as many dollars as they could.
People seem to forget even before the crypto craze the company had insane margins in their revenue. They weren't selling 800$ chips because those costed 600 or 500$ to produce...
Even the most expensive 4090 is hardly more than a 400$ chip, memories included to build.
I'm not an ML developer, so I'm curious. Just economies of scale?
Outside of training, using the trained network for inference seem to be changing less, so maybe a decent target for bespoke targeted hardware. And indeed it seems that custom hardware blocks are very much "catching favor" in that market - everyone seems to be adding accelerators to their SoCs.
GPUs seem to be at a happy medium, where they're often flexible enough to run techniques while still having better efficiency than a CPU.
We were 2nd in the state in Illinois, and I wanted to cement our place and possibly win by selling everything to lock in gains in the final week. The person executing the trade on our team accidentally shorted it and it went up a considerable amount in the last week knocking us down quite a bit.
At that point I seriously considered dumping my savings into Nvidia. I'd be retired right now if I had done so.
Once gen AI gets good enough to generate high quality video games, virtual worlds, etc. in real time, that will redefine gaming and entertainment.
Why wait for the next Mission Impossible movie to come out when you can experience it...as Tom Cruise...with your own storyline with all of your friends. And get a new one every day.
The curation of an experience is undervalued by many.
Just like coding isn't about mechanics. It is about understanding requirements and coming up with solutions that meet needs
Think about any good story. A million details could be different, and it would still work well.
The current expectation that movie studios or the Hollywood machine will somehow be diminished by GenAI is misguided. If anything, it will normalize $100 movie rental "experiences" you can enjoy at home with no additional hardware besides your smartphone and a cast-enabled TV, with everything rendering real-time in the cloud.
And yet all these work and success from Nvidia was because of, if you read 90% of HN comments for the past 2 years; Luck.
They could have given up at any point in time for the past 20 years and simply not do anything CUDA or GPGPU related. Because who would want to do that when vast majority of those investment were not even bringing in much revenue. Like Intel decided to cancel Larrabee. They persevere and hit the Jackpot some 10-15 years later. But all of this was because of; Luck.
Yes. Luck plays a big part. They could have continue another 10 years and they may never find the Killer App for it. But to ignore all the investment and work for such a long time and pin it down to Luck was about as rude and as disrespectful it can be. Especially on a forum which was started by VC with the spirit of entrepreneurship.
But their Zen bet has paid off and now they're playing catch up.
Intel, OTOH, I'm not sure what their excuse is.
Intel had grown accustomed to internal mediocrity and got too big to root it out; the fact that accounting runs the company instead of someone with a vision doesn’t help. Accounting doesn’t like risky bets and Intel needed some to work out instead of cancelling everything left and right.
You're making it sound like AMD being broke at that time was some unfortunate accident due to external events, and not the result of their own blunders.
Nvidia had billions due to great products and great business decisions on their part, and AMD was broke entirely due to it's own actions, by having average products on the CPU side and making bad business decisions at the time by spending way too much money acquiring ATI, and then selling off their golden goose, the Imageon mobile GPU division to Qualcomm for pennies right at the beginning of the smartphone revolution.
It's a miracle they managed to turn things around and not end up like SGI and 3dfx, bankrupt and having their carcass devoured by Intel and Nvidia.
https://en.wikipedia.org/wiki/Advanced_Micro_Devices,_Inc._v....
That NVidia has maintained this push for the last 2 decades makes one wonder what other tricks they'll have up their sleeve.
Even something as simple as replacing TVs and monitors is a no-brainer. It's just a question of whether comfort and quality can be achieved.
For games, to the extent that VR works for them... sure, I could see that use case. But for, say, business meetings? Uh, no. Or to hang out with friends? Sure, maybe, but how would they monetize it well enough to make the investment worthwhile? To make it compelling enough that I would visit?
I'm not saying that the use cases don't exist. But either making compelling VR experiences has to be cheap[1] (which I don't see on the near horizon), or they have to add enough value that people will pay for them in some way. That strikes me as uncertain.
[1] If they get cheap, then sure, although then it will have the same problem CGI now has... there is so much of it that it has lost a lot of its magic. It's hard to be common and compelling.
People were saying the same about home computers in the '70s and it was relatively true for that period if you didn't look into the future and only considered what home computers looked like back then: janky machines built from radio shack parts by nerdy enthusiast tinkerers with electronics knowledge. Only when they were presented with prebuilt and polished products with usable apps that didn't require technical knowledge, did people see the light that home computers are the future and will become mainstream for all consumers not just enthusiasts.
Nobody can know yet how mainstream VR will look like exactly and who will get to dominate the field and dictate the product direction (Apple, Valve, Meta, etc), but for sure it will happen in the future, even if for now it's just a tinkering toy for gamers and enthusiasts with money.
You can't have a pair of glasses that is simultaneously opaque enough to give you the illusion you are in another place AND breezy enough so that your eyes won't sweat. Air is just much bigger than light, so you can't block light but allow air to pass through. So a VR headset will always be sweaty on the face. AR will never be able to create realistic opaque backgrounds.
You also can't have a holo-deck-like experience with glasses. The only reason the holo deck captures our imaginations is because it had space, smells, sounds, touch. All of those things are impossible to achieve with physical devices of any kind, or at least very close to it. The only thing that may create a holo-deck like experience would be based on brain-computer interfaces, if those are even truly possible.
Finally, to get many of the claimed benefits, even if the headsets were good enough to deliver them, you also need complex recording software that actually handles all of this. You can't have a nice realistic image of all of your colleagues in a VR meeting unless they each have a 3D camera setup, and everyone has enough bandwidth to actually receive and send all of the 3D videos, and do so with latency similar to audio traffic.
These are at least three fundamental problems that make the whole VR/AR craze just certain to fail. Again.
You don't need the exact fictional holo deck device to have a VR product that sells. 150 years ago Sci-Fi writers imagined we'd have robots in our homes doing our chores, and we do have them today, except not humanoid robots doing the washing and vacuuming by hand for us like we originally imagined, but we have fixed function dedicated robots for each task: dish washing machine, clothes washing machine, Roomba robo-vac, etc. They're a rudimentary and limited far cry from the fantasy and capable humanoid robots in sci-fi novels, yet they're ubiquitous today and sold by the millions. Same will be with VR, it will be more limited than the holo deck but it will sell at the right price/feature combo.
>You can't have a nice realistic image of all of your colleagues in a VR meeting unless they each have a 3D camera setup, and everyone has enough bandwidth to actually receive and send all of the 3D videos, and do so with latency similar to audio traffic
People also fantasized about video telephony like in star trek and yet those challenge got overcome with the introduction of 3G and camera phones and has improved ever since. Tech will also improve for VR. The iPhone already has had a 3D camera since a while now.
>These are at least three fundamental problems that make the whole VR/AR craze just certain to fail. Again.
It will fail today, but it will succeed in the future, even if you're too dead set to not see it.
But we don't have a clothes folding machine, precisely because the task is infinitely harder, from a first principles view, than anything a futurist imagined. VR/AR is the same. It's not just scaling up computer power because it's a matter of not having the physical ability to manipulate reality, energy, and matter the way we need.
Science isn't magic. How do you do haptic feedback to hands? That's an essential part of any AR system that isn't just a gimmick, and yet it's basically impossible without clunky gloves. How do you prevent damage to the human eye over extended use like a 9-5 job? The human eye did not evolve to "look at" different things that are in actuality on a screen an inch from our eyes, it really upsets the brain and the muscles that control vision, which is why VR/AR can be so tiring on your eyes. That cannot be innovated away.
Who said VR would need gloves and haptic feedback to succeed? We're talking about virtual reality here, not simulated reality. For the latter better wait for Elon's neural link or whatver we'll get that plugs our brains into the Matrix and simulates reality.
People still use mice and keyboards to interact with UIs despite having the ability to use touchscreens. Just because one thing exists, doesn't automatically mean the other dies.
>How do you prevent damage to the human eye over extended use like a 9-5 job?
Who said you need to use a VR device from 9-5 for it to succeed? You don't stare at your phone screen or tablet for 8h/day, do you? And yet you most likely have one.
> The human eye did not evolve to "look at" different things that are in actuality on a screen an inch from our eyes
Have you seen what lenses can do with light? Like move the focal point of a picture much further away? They're pretty big tech in cameras, telescopes, binoculars, and .... oh, these optical things humans wear on their faces, a couple of cm from their eyes to fix their vision issues, their called glasses I think.
How about we use those lens thingies to move the focal point of a screen that's 2cm from your eyes to 2m from your eyes? I'm telling you dude, whoever invents this tech is gonna be big.
I really liked immersive VR I experienced in research lab settings like CAVE systems, over 20 years ago. I'm probably among the people most tolerant to artifacts like frame rate jitter and lag, and most easily able to still get an immersive pop out of it. But I'm not an early adopter. I don't see the value or place for this single-purpose equipment in my life, nor my budget.
When mobile phones were just phones, I saw them getting smaller and lighter. I even fantasized about them shrinking until it was just the ear bud. I was willing to hand-wave some sci-fi UX without a display nor buttons. But, I didn't (and still don't, really) appreciate how people would care to get wireless ear buds that are still slaved to a larger device. I'd still be satisfied with wired ear phones if they were available.
I also didn't imagine today's smartphone ecosystem, even though I saw all the PDAs and other pocket computing platforms and their general purpose potential. I didn't predict the social/marketing angle that was going to make any of this seem worthwhile to average consumers. Now, I benefit from these economies of scale making the tech affordable, but I barely need it. I still prefer going to a laptop or desktop for any "real" tasks. Ironically, a smartphone ir tablet makes me feel frustrated and "mute" without a keyboard.
I understood the idea of convergence and the general purpose device. I understood the mobile/always on value and was on the early side of wire-cutting to have only a mobile phone. But, I was surprised at how rapidly the smartphone ate up digital camera and personal video camera markets. I am still surprised at how much smartphones are eating into spaces like regular laptops and PCs. And now the entire concept of a phone seems to be disappearing, with traditional voice calls being less relevant as time goes on.
So I am a fence-sitter on some kind of N-dimensional fence. I admit that a lot of tech development might occur and I probably can't guess which ones get popular. Maybe there is some VR/AR angle that will finally catch on.
But on the more general topic, I also think that all these developments above had many other passionate developers and ventures working on slightly different angles that failed in the market. As a third-party observer of decades of tech, I do also think it's a lot of luck. It is survivorship bias to fixate on how NVIDIA or Apple or anybody had some perfect strategy to ride these big waves.
You can have a fan that pull the air in or out of the inside of the glasses without any light ever coming in.
That seems easy to fix - small tubes/vents that don’t go straight through but hit a corner or big enough curve. Air can go around obstacle but light won’t.
That’s the theme of this article. Nvidia invested heavily in GPUs even though the complete business model wasn’t always clear.
Yes, they've shipped tens of millions of headsets across the world.
> It’s hard to figure out what Meta spent all that money on.
R&D on every problem for XR. Their software side is mediocre, but what Reality Labs is working on for hardware is unparalleled by any other company, even Apple.
In the case of AR/VR, I think there are two issues that make payoffs uncertain: 1) the hardware would have to get much cheaper; when will that be? 2) What is the killer app that would motivate the (large) expeditures required to produce compelling virtual environments? Games is an obvious case, but games are a very different beast than online meeting rooms -- the whole action/reward cycle of games isn't likely to work for business meetings. It isn't really clear that VR adds enough value to be compelling for non-gaming apps.
But it could easily be true that we just haven't imagined the right use case. You won't find it if you don't look.
Still I think people REALLY underestimate this space. First gaming has an outrageous TAM and VR games are GOOD. Second AR has an even bigger market, and I’ve realized that it’s not just about giving us all a HUD to walk around with, it’s also going to about having an AI assistant get information in the environment around us with a camera.
I just think it's an honorable mention because had things gone a little differently, perhaps Intel could have been king of the hill instead.
They lost the process lead and can’t figure it out for almost a decade now - we wouldn’t be having this discussion if their hardware worked out according to their plans.
One thing I never see people discuss in the context is that from the beginning NVidia drivers were closed source while Intel drivers were open source. If you don't see software as a competitive advantage that obviously limits the resources you can invest in it. Linus Torvalds said "Fuck you, NVidia" but who's fucked now?
Never once read a comment attributing Nvidia success to luck.
The only luck Nvidia has is the luck that AMD fell asleep at the wheel and couldn't get bothered to put more than 2 engineers on a CUDA competitor even when it was getting apparent that AI was worth billions (i.e. ~4-5 years ago).
“No, Nvidia just found themselves in a lucky situation.”
You have to keep in mind that for a long time concurrency was thought of as the only way to keep getting increasing performance out of CPU's, what they invested in is massive concurrency and when ML/AI hit they were well-positioned for it due to their investments in massive concurrency.
The vast majority of the comments on this article prior to the one you were replying to were attributing it solely/largely to luck.
When people say it's luck, I think they are reacting to the reality that Nvidia couldn't know, when they were doing this investing, that there was a big AI market waiting to take off. They were doing good work, but they were also very, very lucky that circumstances granted them this opportunity. There is no shame in that -- few companies achieve great success without some opportunity manifesting.
But it's a mistake to pat yourself on the back too hard, either. Without the opportunity, they'd still be making gpus with some other applications.
* This is gated by the ability to recognize those opportunities when they appear, willingness to act decisively to maximize the probability of positive outcomes and the preparedness to exploit such advantages. This tends to require mental preparedness, emotional maturity and a willingness to invest scarce resources and/or time - in advance - toward maintaining situational awareness and some excess reserve resources. Doing this is hard but these traits are learnable.
* Similarly, a portion of available conscious effort and scarce resources must be continuously expended toward being resilient to bad luck when it inevitably strikes. The net impact of misfortune can vary substantially depending on mitigation steps taken in advance. This requires accurate awareness of ambient risk factors and careful balancing of where you choose to place your limited 'air bags' and 'ounces of prevention.'
Most of these things are at least somewhat within your ability to influence, with the exception of initial conditions. At the "opening deal" of life some people are dealt better cards and some people are dealt worse cards. This is not fair, but it is what it is. The silver-lining is that, after the initial cards are dealt, it can still be a long game with many rounds. How you choose to play the cards you have in each of those rounds can lead to substantially different outcomes. Because it's a game like poker with randomness, hidden variables, subtle cues and second-order probabilities - it's easy to conclude it's almost all luck. This is unfortunate because not understanding the 'meta' of the game, or even knowing there is a meta, does make it mostly luck for some.
I think NVidia's 'good fortune' is the cumulative result of playing the meta-game effectively for a long-time and thus leading to them having the capability to maximize their outcomes when eventually finding themselves in a high-opportunity environment (aka "lucky").
They had their reasons for doing what they did and I'm sure they eventually realized they were well positioned for ML/AI, but there's no way they planned that out before ML/AI was a viable thing.
And sure, AlexNet was good but remember this is the maxwell days, tensor cores aren't even a thing yet, it was at minimum a very bold bet on the basis of "some image classifier model thing". Nobody else saw it as more than an academic toy (obviously, or they'd have jumped in too).
https://www.newyorker.com/magazine/2023/12/04/how-jensen-hua...
> Within a couple of years, every entrant in the ImageNet competition was using a neural network. By the mid-twenty-tens, neural networks trained on G.P.U.s were identifying images with ninety-six-per-cent accuracy, surpassing humans. Huang’s ten-year crusade to democratize supercomputing had succeeded. “The fact that they can solve computer vision, which is completely unstructured, leads to the question ‘What else can you teach it?’ ” Huang said to me.
> The answer seemed to be: everything. Huang concluded that neural networks would revolutionize society, and that he could use CUDA to corner the market on the necessary hardware. He announced that he was once again betting the company. “He sent out an e-mail on Friday evening saying everything is going to deep learning, and that we were no longer a graphics company,” Greg Estes, a vice-president at Nvidia, told me. “By Monday morning, we were an A.I. company. Literally, it was that fast.”
10 years out is 2014.
Use luck to be humble, use luck to empathize, use luck to build people up, but don't use luck to tear people down.
I remember talking to Jason Fried about this with 37 signals. A lot of people didn’t realize the grind that team had before things finally clicked.
It’s a common pattern to see people gloss over the insane lengths and foresite required to achieve overnight success. :)
At least judging from the upvote it does seems I have the backing from silent majority. All is not lost.
The wise decision was to keep pushing cuda and not dropping the ball on it to cut costs in the short run, and realizing the potential of using it for scientific computation early on. Then one thing led to another. When AI came around, cuda was the only mature and serious framework for the job.
NVIDIA will be okay though, they have the volume to get the newest nodes first. Only a few can compete with them.
Nvidia CEO: We bet the farm on AI and no one knew it https://news.ycombinator.com/item?id=37055375 (August 8, 2023 — 10 points, 4 comments)
Is this acknowledging the game market is dry?