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Nvidia Rides AI Wave to Pass Apple as Largest Company
- gnabgib 2y agoDiscussion (79 points, 12 days ago, 48 comments) https://news.ycombinator.com/item?id=41952389 https://news.ycombinator.com/item?id=41952389
- nvidiafanbot 2y agoApple has an entire diversified product roadmap and ecosystem. Nvidia has a gpu. I don’t see longevity for Nvidia.
- Dr_Birdbrain 2y ago(deleted because I was wrong)
- andsoitis 2y ago> Do they even do any R&D anymore? Yes. “Apple annual research and development expenses for 2024 were $31.37B, a 4.86% increase from 2023. Apple annual research and development expenses for 2023 were $29.915B, a 13.96% increase from 2022. Apple annual research and development expenses for 2022 were $26.251B, a 19.79% increase from 2021” — https://www.macrotrends.net/stocks/charts/AAPL/apple/research-development-expenses https://www.macrotrends.net/stocks/charts/AAPL/apple/researc...
- deleted 2y ago[deleted]
- monocasa 2y agoR&D spending is basically a lie at most tech companies because of how the tax grants for R&D spending work.
- andsoitis 2y ago> R&D spending is basically a lie Chips, for one, don’t research themselves: https://www.apple.com/uk/newsroom/2023/03/apple-accelerates-investment-in-germany-to-expand-silicon-design-center/ https://www.apple.com/uk/newsroom/2023/03/apple-accelerates-...
- monocasa 2y agoYes, but any numbers they list are a lie, and are essentially whatever maxes out the R&D tax credit.
- seanmcdirmid 2y agoSoftware developers are consider the D in R&D, much of it is just engineering salary cost since they are a tech company.
- mgh2 2y agoRegarding R&D: They have quite a few reports integrating their products with health. Ex: https://news.ycombinator.com/item?id=41491121 https://news.ycombinator.com/item?id=41491121 https://news.ycombinator.com/item?id=41948739 https://news.ycombinator.com/item?id=41948739 Tested by community: https://news.ycombinator.com/item?id=41799324 https://news.ycombinator.com/item?id=41799324 https://news.ycombinator.com/item?id=42019694 https://news.ycombinator.com/item?id=42019694 VR was a 10 year or so project but agreed no product-market fit yet.
- godelski 2y ago> They seem to have lost faith in their own ability to innovate. As they should. I mean they can, but they have to change course. All of Silicon Valley has tried to disenfranchise the power users. With excuses that most people don't want those things or how users are too dumb. But the power users are what drives the innovation. Sure, they're a small percentage, but they are the ones who come into your company and hit the ground running. They are the ones that will get to know the systems in and out. They do these things because they specifically want to accomplish things that the devices/software doesn't already do. In other words: innovation. But everyone (Google and Microsoft included) are building walled gardens. Pushing out access. So what do you do? You get the business team to innovate. So what do they come up with? "idk, make it smaller?" "these people are going wild over that gpt thing, let's integrate that!" But here's the truth: there is no average user. Or rather, the average user is not representative of the distribution of users. If you build for average, you build for no one. It is hard to invent things, so use the power of scale. It is literally at your fingertips if you want it. Take advantage of the fact that you have a cash cow. That means you can take risks, that you can slow down and make sure you are doing things right. You're not going to die tomorrow if you don't ship, you can take on hard problems and *really* innovate. But you have to take off the chains. Yes, powerful tools are scary, but that doesn't mean you shouldn't use them.
- andsoitis 2y ago> the average user is not representative of the distribution of users. What does this mean? Just thinking about iPhones: As of September 2024, there are an estimated 1.382 billion active iPhone users worldwide, which is a 3.6% increase from the previous year. In the United States, there are over 150 million active iPhone users.
- godelski 2y agoAre you math inclined? This is easier to explain with math (words) but I can put it in more English if you want. If you're remotely familiar with high dimensional statistics, one of the most well known facts is that the density of a normal ball lies on the shell while the uniform ball is evenly distributed. Meaning if you average samples of a normal ball, the result is not representative of the samples. The average is inside the ball, but remember, all the sampling comes from the shell! It is like drawing a straight line between two points on a basketball, the middle of that line is going to be air, not rubber. But if you do for a uniform ball, it is. That's the definition of uniform... Understanding this, we know that users preference is not determined by a single thing, and honestly, this fact becomes meaningful when we're talking like 5 dimensions...[0]. This fact isn't just true for normal balls, it is true for any distribution that is not uniform. To try to put this is more English: there are 1.382 billion active iPhone users world wide. They come from nearly 200 countries. The average person in Silicon Valley doesn't want the same thing as the average person in Fresno California. Do you think the average person in Japan wants the same thing as the average Californian? The average American? The average Peruvian? Taste and preference vary dramatically. You aren't going to make a meal that everyone likes, but if you make a meal with no flavor, at least everyone will eat it. What I'm saying is that if you try to make something for everyone, you make something with no flavor, something without any soul. The best things in life are personal. The things you find most enjoyable are not always going to be what your partner, your best friends, your family, or even your neighbor finds most enjoyable. We may have many similarities, but our differences are the spice of life, they are what make us unique. It is what makes us individuals. We all wear different size pants, why would you think we'd all want to put the same magic square in our pockets (if we even have pockets). We can go deeper with the clothing or food analogy, but I think you get that a chef knows how to make more than one dish and a clothing designer knows you need to make more than one thing in different sizes and colors. [0] https://stats.stackexchange.com/a/20084 https://stats.stackexchange.com/a/20084
- lukan 2y agoCould you please not delete your comment in the future, even if you are wrong, but maybe just an edit stating that? It would make reading the thread easier ..
- aurareturn 2y agoApple has the iPhone. It’s very concentrated in the iPhone. You can say services but services are powered by the iPhone as well.
- bjornsing 2y agoBut there are people who owns those iPhones, and many of them care that it’s an Apple iPhone. When you use ChatGPT, do you care if the matrix multiplications were done on genuine Nvidia hardware, or custom OpenAI ASICs?
- aurareturn 2y agoIn gaming, people do care if it's Nvidia or AMD. They want Nvidia. For AI, I assume enterprise do care if it's Nvidia. Right now, Nvidia is in the "no one ever got fired for buying Nvidia" camp. You can buy AMD to save a few dollars, run into issues, and get fired.
- bjornsing 2y agoI’m not questioning Nvidia’s moat in gaming. But that’s pretty much irrelevant to its valuation. And sure, for small scale and research activities Nvidia makes sense, even for the long term. But that’s not where the money is at, either. The only way Nvidia can sustain its valuation is if it can win in the large scale production AI market long term, and that market turns out to be huge. I don’t really see how that can happen. As soon as NN architectures are stable over the economic lifetime of a chip custom ASICs will make so much more sense: 10x more performance and no Nvidia tax. It’s already happening [1]. 1. https://www.etched.com/ https://www.etched.com/
- aurareturn 2y agoLet's say the Transformer market is 10x bigger in 2035 than in 2025. Nvidia maintains 40% of the entire market, down from the 90% today. They'd still be vastly bigger in 2035 than in 2025. >10x more performance and no Nvidia tax. It’s already happening Nvidia can do the same though. The moat isn't in inference. It's in training.
- ikrenji 2y agoa gpu is all you need if you’re one of two companies worldwide that makes them
- ClassyJacket 2y agoEspecially if you're the only one that makes GPUs for AI use
- andsoitis 2y ago> Nvidia has a gpu. In addition to the GPUs (which they invented) that Nvidia designs and manufactures for gaming, cryptocurrency mining, and other professional applications, the company also creates chip systems for use in vehicles, robotics, and other tools.
- Legend2440 2y agoOkay, but $22.6B of their $26B revenue this quarter was from datacenter GPUs. The only reason they are this big right now is because they are selling H100s, mostly to other big tech companies.
- archerx 2y agoReally? Nvidia’s marketing and PR teams are trying to trick people into thinking that they invented GPUs? Does Nvidia have no shame and or scruples? The term "GPU" was coined by Sony in reference to the 32-bit Sony GPU (designed by Toshiba) in the PlayStation video game console, released in 1994. https://en.wikipedia.org/wiki/Graphics_processing_unit https://en.wikipedia.org/wiki/Graphics_processing_unit
- pests 2y agoIt really depends on what you want to call a "GPU" The device in the PS1 has also been referred to as a "Geometry Transfer Engine" You can see it's features and specs here: https://en.m.wikipedia.org/wiki/PlayStation_technical_specifications#Graphics_processing_unit_.28GPU.29 https://en.m.wikipedia.org/wiki/PlayStation_technical_specif... Some may say that it is not a "real GPU" or certain features (like 3d) are missing to make it one. The Nvidia claim is for the GeForce 256 released in 99. This makes me wonder if our grandkids will be debating on what the first "real AI chip" was - would it be what we call a GPU like the H100 or will a TPU get that title?
- archerx 2y agoThat is just pedantic and a bit disingenuous. 2D/3D accelerators existed before 1999. I actually had one of these cards; https://en.wikipedia.org/wiki/S3_ViRGE https://en.wikipedia.org/wiki/S3_ViRGE It sucked but it was technically one of the first "GPU"s. Also let us not forget 3dfx and the Voodoo series cards. Don't let Nvidia rewrite history please.
- paxys 2y agoTake away iPhone and Apple is worth at best 1/10 of its current market cap. The company isn't as diversified as you think.
- JimDabell 2y agoAirPods alone generate five times as much revenue as Spotify, and about two-thirds as much as Netflix. Apple is also the world’s biggest watchmaker. When some of Apple’s side-quests are industry giants in their own right, I think it’s fair to say that Apple are diversified.
- littlestymaar 2y agoThat's true but at the same time these are mostly I phones accessories. Should the iPhone fall out of fashion (which I don't expect but it's a thought experiment) then the sales of these products will decline as well, so is that really diversification?
- JimDabell 2y agoShould the iPhone fall out of fashion, Apple will make the Apple Watch compatible with whatever displaces it. AirPods are already usable as normal Bluetooth wireless earphones.
- aurareturn 2y agoAirpods are only popular because of the iPhone.
- HDThoreaun 2y agoIve compared airpods to competitors and the airpods were clearly better imo. Sure they became popular because of the iPhone but theyre also just a competitive product.
- yread 2y agoEver tried using apple watch without an iPhone?
- farseer 2y agoNvidia also has CUDA, which has surpassed all rival attempts at GPU programming frameworks in the last 2 decades. I remember learning OpenCL and rooting for it to become the standard but couldn't find a single job for that role.
- cyberax 2y agoCUDA is nice, but it's not a moat. Rocm exists, and even creating a totally new AI computer API is not that far-fetched.
- _zoltan_ 2y agoCUDA is totally a moat. ROCM exists but AMD is like 100k engineering years behind NVDA just in terms of how much time NVDA had to invest into CUDA and all the ecosystem around it. need dataframes and pandas? cuDF. need compression/decompression? nvcomp. need vector search? cuVS. and the list goes on and on and on.
- bjornsing 2y ago> need dataframes and pandas? cuDF. need compression/decompression? nvcomp. need vector search? cuVS. and the list goes on and on and on. Sure, but that doesn’t mean I’m going to pay a billion extra for my next cluster – a cluster that just does matrix multiplication and exponentiation over and over again really fast. So I’d say CUDA is clearly a moat for the (relatively tiny) GPGPU space, but not for large scale production AI.
- erinaceousjones 2y ago> Relatively tiny GPGPU space There's a lot of other things which are very GPU parallelizable which just aren't being talked about because they're not part of the AI language model boom, but to pick a few I've seen in passing just from my (quite removed from AI) job: - Ocean weather forecasting / modelling - Satellite imagery and remote sensing processing / pre-processing - Processing of spatial data from non-optical sensors (Lidar, sonar) - Hydrodynamic and aerodynamic turbulent flow simulation - Mechanical stress simulation Loads of "embarrassingly parallel" stuff in the realms of industrial R&D are benefitting from the slow migration from traditional CPU-heavy compute clusters to ones with GPUs available, because even before the recent push to "decarbonise" HPC, people were seeing the increase in "work done per watt" type cost efficiency is beneficial. Probably "relatively tiny" right now compared to the AI boom, but that stuff has been there for years and will continue to grow at a slow and steady pace, imo. Adoption of GPGPU for lots of things is probably being bolstered by the LLM bros now, to be honest. CUDA benefits from being early to market in those areas. Mature tools, mature docs, lots of extra bolt-ons, organizational inertia "we already started this using CUDA", etc.
- mgoetzke 2y agoApple once had just an iMac.
- ksec 2y agoWith the profits they are getting now I would have loved Nvidia to diversify into other market with their GPU. Server CPU would be a great opportunity.
- seydor 2y agoLike Tesla but bonkers
- PittleyDunkin 2y ago"largest" in terms of market valuation; so, not a very substantial measure.
- aurareturn 2y agoFor public companies, market cap is the most important metric. So it’s the most substantial measure to me.
- RayVR 2y agoWhy is market cap the most important metric? It does not exist in a void. Market cap + P/E or forward P/E, P/B, P/S, etc. are all metrics of high import. Market cap is one piece of a complicated picture. On its own, you don't know too much.
- wbl 2y agoAnd how much money do you make from trading large cap US equities?
- aurareturn 2y agoWhy is market cap the most important metric? It does not exist in a void. Market cap + P/E or forward P/E, P/B, P/S, etc. are all metrics of high import. I thought it was obvious that I implied market cap increase by percentage. When you're evaluating your ROI on tech stocks, the #1 factor is market cap delta between when you bought the shares and now.
- Legend2440 2y agoMarket cap is kind of made up. The stock is worth what people believe it to be worth. Profit is the number that really matters.
- aurareturn 2y ago>Market cap is kind of made up. For a public company, it's all about return on investment, right? Market cap is the most important factor in return on investment right? Therefore, market cap is the most important measure.
- ChrisArchitect 2y ago[dupe] https://news.ycombinator.com/item?id=42055199 https://news.ycombinator.com/item?id=42055199
- mythz 2y agoWeirdly enough for my next "AI hardware" purchase, I'm waiting for the release of the M4 Ultra to max out on VRAM since Nvidia's chips are highly overpriced and using GPU RAM to price gouge the market. Since M4 Max allows 128GB RAM I'm expecting M4 Ultra to max out at 256GB RAM. Curious what x86's best value get consumer hardware with 256GB GPU RAM. I've noticed tinygrad offers a 192 GPU RAM setup for $40K USD [1], anything cheaper? [1] https://tinygrad.org/#tinygrad https://tinygrad.org/#tinygrad
- unsnap_biceps 2y agoI really wonder how the future tariffs are going to shape the AI industry. Are we going to see huge AI clusters being hosted overseas? Will it eat into Nvidia's bottom line or will consumers just eat the price increase?
- seydor 2y agoAI pirates are probably going to be a big thing, but it will not because of tarrifs, they will be running illegal models.
- patates 2y agoIllegal models! I'm sure there will be more regulation to come but the law has already struggled a lot with the internet and the transactions through it. I wonder how much trial and error this wave will cause.
- gigatexal 2y agoTrump is stupid and insane and a coward. But I don’t think he’s so stupid enough to put such egregious tariffs up. Maybe someone can explain how the economy works to him like a 5-year old and maybe he’ll get it.
- aurareturn 2y agoI think he mentioned the tariffs to try the election. I don't think he's dumb enough to raise tariffs on every goods which lead to inflation which lead to low approval ratings.
- surgical_fire 2y agoNot to mention that other countries will also raise tariffs agains US products and services exports. To presume other countries will accept increased tariffs against their industries without retaliation is naive, to say the least.
- doctorpangloss 2y ago
- zamalek 2y agoThe trough of disillusionment is going to be frightening, and I believe we're starting to see the first signs of it (with Apple's paper, ironically enough).
- ninjin 2y agoNot sure which paper you are referring to. Would you be happy to share it for those of us that seemingly have missed it?
- omgwtfbyobbq 2y agoIt's a part of the hype cycle. https://en.m.wikipedia.org/wiki/Gartner_hype_cycle https://en.m.wikipedia.org/wiki/Gartner_hype_cycle I'm not sure how accurate it is overall, but there are companies that fit it.
- mgh2 2y agoThis one? https://news.ycombinator.com/item?id=42024539 https://news.ycombinator.com/item?id=42024539
- ninjin 2y agoThanks, that is probably the one. Here is a link to the paper itself on arXiv: https://arxiv.org/abs/2410.05229 https://arxiv.org/abs/2410.05229
- yardstick 2y agoPaper as in stocks. Traditionally stock certificates were printed on paper. Apples share price has taken a bit of a fall this week.
- deleted 2y ago[deleted]
- kahon65 2y agoNot ready
- 2y ago
- dr_dshiv 2y agoIs it scary that Huawei is competing with both, very quickly?
- _zoltan_ 2y agoin what sense? there isn't any competitor to the MacBook Pro and the M4. there isn't any competitor to NVL based Blackwell racks. not even for the H100/H200. so how do you think Huawei competes?
- dr_dshiv 2y agoThey are the biggest high-end competitor to the iPhone in China. They have been shut out of nvidia chips so they are rapidly figuring out how to make their own. I’m sure both Apple and nvidia view Huawei as a serious competitor. Like, the kind of company that could, in 5 years, take a third of their market share.
- olliej 2y agoI get that they’re selling huge amounts of hardware atm, but I feel like this is entirely due to the hype train that is BS generators. I have not encountered any of the aggressively promoted use cases to be better than anything they replaced, and all the things people seem to choose to use seem of questionable long term value. I can’t help but feel that this nonsense bubble is going to burst and a lot of this value is going to disappear.
- devjab 2y agoIn document recognition they’re going to replace everything that came before. A couple of years ago you needed a couple of ML experts to setup, train and refine models that could parse through things like contracts, budgets, invoices and what not to extract key info that needed to be easily available for the business. Now you need someone semi-proficient in Python who knows enough about deployment to get a local model running. Or alternatively skills to connect to some form of secure cloud LLM like what Microsoft peddles. For us it meant that we could cut the work from 6-12 months to a couple of weeks for the initial deployment. And from months to days for adding new document types. It also meant we need one inexpensive employee for maybe 10% or their total time, where we needed a couple of expensive full time experts before. We actually didn’t have the problem with paying the experts, the real challenge was finding them. It was almost impossible to attract and keep ML talent because they had little interest in staying with you after the initial setups, since refining, retuning and adding new document types is “boring”. As far as selling hardware goes I agree with you. Even if they have the opportunity to sell a lot right now it must be a very risk filled future. Local models can do quite a lot on very little computation power, and it’s not like a lot of use cases like our document one need to process fast. As long as it can get all our incoming documents done by the next day, maybe even by next week, it’ll be fine.
- olliej 2y agoI mean I’ve not had any problems with whatever the macOS built in one is, but document recognition is a a tiny part of the industry and isn’t involved in the hype bubble at all. The stuff with Python->traing->??->$$$ is what I don’t buy: First: the “AI” stuff is “generate content with no obvious financial value to anyone”, chat bots (which no one I know actually seems to want), or “maybe better predictions”. Second: the “person can do X with AI with less training” etc is not a value of AI, it’s just a product of improved libraries and UI for putting things together. It doesn’t mean the thing they’re doing with AI has any value outside of bandwagonning. Third: the reason for AI start ups is just that training costs a tonne of capital - and VCs love throwing cash at bandwagons so there’s a pile of “AI” startups, all of which offering essentially the same thing below cost in the hopes that they’ll magically find a profit model. Finally: there’s already near enough on device processing power on phones for most actual practical uses of “AI” so the need for massive gpu rigs will start to tank especially once the hype train dies off and people start asking what is actually useful in the giant AI startup buzz. Each of these things is going to result in the valuation bubble for nvidia collapsing. Mercifully I don’t think there’s any real harm in the nvidia valuation bubble (congrats to the folk who made well on their RSUs!), but I still don’t think the valuation has significant longevity.
- deleted 2y ago[deleted]
- NoZZz 2y agoA pretty rediculous proposition. The chinese have just improved their chip fabricaiton processes, and a GPU is just a retarded parallelised cpu. Given that most of these innovations are being open sourced, it will be captured by a player that can push down the price.