How Nvidia Became America’s Third-Most Valuable Company
Vložit
- čas přidán 1. 06. 2024
- Use code tldrnews at the link below to get an exclusive 60% off an annual Incogni plan: incogni.com/tldrnews
Last week, Nvidia saw the biggest single-day gain in West Street history, fuelled by the ongoing AI boom. But, it's rise does look a bit unstable, so, we're going to take a look at what's going on with the American tech giant, and whether the boom can really last.
🎞 TikTok: / tldrnews
💡 Got a Topic Suggestion? - forms.gle/mahEFmsW1yGTNEYXA
Support TLDR on Patreon: / tldrnews
Donate by PayPal: tldrnews.co.uk/funding
Our mission is to explain news and politics in an impartial, efficient, and accessible way, balancing import and interest while fostering independent thought.
TLDR is a completely independent & privately owned media company that's not afraid to tackle the issues we think are most important. The channel is run by a small group of young people, with us hoping to pass on our enthusiasm for politics to other young people. We are primarily fan sourced with most of our funding coming from donations and ad revenue. No shady corporations, no one telling us what to say. We can't wait to grow further and help more people get informed. Help support us by subscribing, engaging and sharing. Thanks!
//////////////////////
1 - blogs.nvidia.com/blog/whats-t...
2 - www.economist.com/the-economi...
3 - www.ft.com/content/1492b328-5...
4 - www.economist.com/the-economi...
5 - www.economist.com/leaders/202...
6 - www.economist.com/leaders/202...
7 - www.economist.com/the-economi...
8 - www.economist.com/the-economi...
9 - www.economist.com/the-economi...
10 - www.ft.com/content/c43661bb-a...
11 - www.economist.com/business/20...
00:00 - Introduction
00:49 - Who is Nvidia?
02:41 - Nvidia’s Recent (and Ridiculous) Boom
05:42 - Can it Last?
08:15 - Sponsored Content
CUDA is not a fine tuning software. It is a framework used to write software that makes the best use of NVIDIA chips. And once a workload is written in CUDA it takes effort to port to other manufacturers hardware. Each manufacturer (AMD, Intel) has their own such framework and none of them are inter-compatible. Most existing software is written using CUDA because for some time it was the only choice.
Was just about to say how such a big mistake could make it on video
I hope ZLUDA gets a lot of effort invested in it.
rOCM already does make the effort a lot less than it would have been previously.
ZLUDA will make it zero, if it ever gets good enough.
To simplified Cuda is a language to talk to any Nvidia GPU. Nvidia sell shovels, carts, maps and dictionaries.
At least they are aware of CUDA and mention it. Most mainstream news don't even understand why people buy Nvidia over AMD in the first place.
Intel and Nvidia both use OpenCL. It can do everything cuda can and is an open standard.
Hardware wise, gpus are all huge clusters of floating point units. If cuda wasn't proprietary it could run on any newer gpu with modern shaders.
Funny story: My HPC professor has Nvidia shares (at least he told us as much when we started the class). And what does he teach in class? Besides OpenMP for CPU parallelism, he also teaches CUDA.
He's definitely nurturing his investment.
I just hope the open source AMD CUDA project gets very up and running, may shift the non extreme hardware market at least
Your explanation of the difference between CPUs and GPUs is incorrect.
GPUs do not simply process in parrellel - CPUs also do this.
GPUs are specifically designed for certain types of calculations that are used in generating images for a screen, specifically vector calculations. These calculations are also widely used in large language model, hence why Nvidia made the switch to focussing on AI.
So compared to existing large chip manufacturers (e.g. Intel, AMD), Nvidia has been tailoring their chips towards AI development for decades, which is why they're well placed to cash in on the AI boom compared to their competitors.
Agreed.
It's not exactly incorrect as much as it's "simplified".
I think yours explanation is still too much for a normal person and also I see why they've explained it the way they did - it kind of gets the point across, those who know, know and for those who don't it won't be useful anyway
@@Khantia No it's blatantly incorrect. That's like saying the difference between strawberry and mint ice cream, is that mint ice cream is cold, it's literally nonsensical. Simplification != Incorrect explanation.
True. Vector calculations are common in all neural networks, not just LLMs, that's why people have been running them on GPUs for decades. NVidia was smart to spot this emerging trend and release CUDA in 2007 to make it easier to run neural networks efficiently on Nvidia GPUs. Back in those days, there weren't that many people using neural networks, but 16 years later, their investment is definitely paying off.
I anyone question "Why Nvidia and not AMD?" The answer is CUDA. It's proprietary and became standard in the industry a decade ago. Just like you are going to get a job they ask knowledge of Microsoft Office or Adobe software and not another open source alternative.
ROCm is shrinking the gap by a lot.
This might be a problem in the future though, for example people are underscoring how fast indie and open source ai architecture development is going, its mostly unrelated right now since all eyes are in big companies
Notice how gpt4 has gotten worse the past few years? Thats due to censorship and open ai actively gimping development due to ideological reasons, open source is hard to stop like this
Microsoft, Alphabet, Amazon, and Meta DON’T like with monopolies? I’m sure that is unpleasant, I wouldn’t know
Some inaccuracies..
nVidia cards weren't participially great at crypto and etherium, it's just that the demand was far greater than supply, so any card was better than no card and because nVidia had the far greater market share at the time, they were producing more product to sell and they had a larger profit margin, so they benefitted far more than AMD.
The strength of CUDA is that they seeded it into universities decades ago, investing heavily to ensure software developers knew CUDA really well, which supported the efforts to get software written for CUDA. Work is just coming to fruition to enable CUDA code to run (imperfectly) on AMD cards, so that advantage may diminish rapidly now as well.
Covid also should have been mentioned, it bridged the gap between crypto and A.I, ensuring demand remained extremely high.
As someone in tech I appreciate the effort but i do agree with the other comments about CUDA and CPU vs. GPU, I would suggest in future that you get a technical expert to check over scripts to root out any issues.
Also 74.3% != ~4/5
NVIDIA is great a producing powerful chips, but not necessarily the most efficient. NVIDIA GPUs are literally used as space heaters by some gamers. That’s where Apple and Amazon may have an advantage because their scale is so large, they have to design their chips with system efficiency as a requirement. Apple’s Mac chips are already approaching NVIDIA’s GPUs performance in some cases at 1/3 the power. It’s insane how inefficient their chips are.
NVDA could squander their lead (Intel did, Tesla seems primed to) but even so it would take a while and, imo, the value would plateau rather than plummet.
it's the "bit spenny" for me 😂😂😂
Nvidia does have their own models, it is just mainly tied to their consumer GPUs as features for them compared to their competitors and not something meant to be widely used like an LLM.
I quite like most of the simplifications in this video, but I think explaining CUDA as just a way to optimise the compute units is a little misleading or at least oversimplified
I hope not
So a serious miss on the story was glossing over their domination of the software side of things. Like other companies can make chips have as good or better specs or maybe better than NVIDIA, but they are generally a decade behind on the software side of things. CUDA is the standard for AI, and it doesnt work on non-NVIDIA chips. Other companies can make boards who are similar in specs, but start from ground 0 in programing for those boards. NVIDIA expands this by the fact that its software library is open, so its way bigger than any company can reasonably make in a internal company environment. Their advantage is like a snowball rolling down hill. Because its open source, more devs will choose to use it, and thus expand the library, and thus attract more devs. That large snowball only works on NVIDIA boards.
Of all the companies in direct competition, realistically only Google probably matters, as they have been more into the board manufacturing for AI specifically longer than others by a few years, and of course been internally involved with AI for a long time. Other companies can make specialized chips for very narrow applications, which is what companies like Tesla plans, but that wont threaten the general AI-focused GPU market.
This also ties into the biggest threat to NVIDIA: A change in the best way to approach Machine learning. Just as NVIDIA benefited when GPUs were identified as the optimal method to approach machine learning when CPUs were still handling the task, if this changes then NVIDIA no longer has the monopoly from all that software utilizing the CUDA core architecture.
This will be a short lived story 😅 they are profiteering right now and charging 40k for what cost 3k to produce ! This never lasts. Expect the share to go back to 1T valuation.
Why would you round up 74.25%, almost exactly 3/4s, to 80%.
Rounding to 75% would make more sense. Otherwise it’s closer to 70% than it is to 80%
Nvidia is becoming another Apple.
Nvidia is Actually good Unlike apple
@@THE.CONFIDENTIAL rtx fanboy, prepare for RDN4
@@santiagopenanavas That was 2 weeks ago.
I don't think anything other than the hallucination problem can stop AI, It can be decreased but not stopped.
2:40 actually as far as i have seen the 2021 crash WAS NOT crypto related sure it might have worsened it but the real problem there was the massive chip shortage skyrocketing the prices, you see the same crash for Intel and AMD right there and they are not very dependent on crypto
6:25 you make me empathise with chatgpt
Please do a simple Google search of the difference between GPU vs CPU. CPU has limited concurrency, GPU has very high concurrency.
That's basically what he said? You just rephrased it so you can pretend to be smart.
@@Ziggletoothplease listen from 1:35 , maybe 🤔 I just want to just portray my idiotic intelligence. But, you have to get hearing aids.
I for one, welcome Nvidia- Skynet/BigBrother/Arasaka/Thalmor/TheEmpire
during the AI boom,
sell GPUs
Modern day gold rush
@@dermeisterdesspiegels3518 true Nvidia CEO is doing his best to sell and boost the stock as much he can during the ai boom
@@darklord4936 and as the saying goes, what goes up, most come down 😁
Last I checked (6 months or so ago when I got a little interested in them due to their GPU's) their PE ratio was well over 60, I think it went over 100 for a time. When I am buying shares I dont touch anything over 30 (which is, or was, about average). I would assume the boom cannot last but I have been wrong plenty of times before.
Groq will kill Nvidia, LLMs and other GenAI models aren't trained often but its used for inferencing much more frequently. Thats where GPUs seem to be struggling and Groq's LPUs are much better. Majority of companies wont train LLMs but rent out LLMs from other companies like OpenAI, Antropic or Meta.
I was expecting an answer to the question. Not another story that everybody knows. Are the AI chips designed by AWS en GCP better? Why can Tesla and Apple pull it off to design own chips. That could answer the question…. This isn’t deep research
We'll already see other tech giants and even start-up trying to design chips better or at least on par with Nvidia's chips. Whenever they manage to do so is another question, Nvidia just has a massive head start in this field. A few good competitors wouldn't be bad tho.
Unless they fucked up really bad like engineers and other human resources leaving to do their own thing/taken by other companies offering better compensation (for examples Fairchild semiconductor) or their intellectual property stolen by data breach/corporate espionage (looking at you China 👀) they'll be okay for a long time.
This will make a great movie!
AI vs. Crypto
Abundance vs. scarcity
$0.01 any pictures vs. $250k monkey pic
Nothing ever last forever
Nvidia right now sounds a lot like a monopoly.
Nvidia will beat out Microsoft and Apple to become the largest company in the world soon. AI market is only going to continue to grow and Nvidia essentially has a monopoly on the best AI chips
Nvidia is one of those companies that sorta seems boring.
But when you look at it in detail, kinda like this video you realize that yes they really only make one product.
But that one product has usecases with just about every hyped industry over the last 30 years.
I'm not an AI specialist, but I've worked among them, and I've seen stuff the general public doesn't know about. It's not just gimmicky chatbots. I know from experience just how important Nvidia is.
I've seen drones that detect pests, or extinguish fires, and small agricultural cars that remove weeds. All powered by computer vision AI. All powered by Nvidia. So yeah, I have quite a bit of trust in them.
That being said, like the video mentioned, the competition isn't sitting idle. I just ordered a Google Coral AI chip. AMD would also like a share of that pie. Once Nvidia no longer holds a virtual monopoly, I can't say that their stocks won't go down again.
this isnt hidden knowledge, its very well documented what ai is both good and bad at and really easy to show where people insert ai because its the latest buzzword and not because it provides benefit
Yea its almost 4/5ths but also literally 3/4ths😂
Nvidia needs to be broken up, it's a monopoly in AI, crypto, video editing, heavy code, and Gaming
7:36 so exactly like khazakstan and russia
No
I keep saying: Why the f doesn't AMD support CUDA as well? Thanks for pointing CUDA out. You have done great research on the topic.
There is too much money to be made in selling and shorting stock, for stock to maintain growth continuously
U are taking short term no one cares about short term it'd about long term growth
The market is not made for shorting, bull is almost always favoured, if you think shorting is the way try successfully shorting tesla and see what investors have learnt the last 5 years
@@beepboopbeepp who said the market is made for shorting? 🤣
Do you think institutional investors are hodl'ing like the Tesla cult? They sell high and buy it back lower, and in the mean time you have traders shorting and calling through other market instrument, quite literally the basics of the stock market 🤦♂️
It's funny you have so much trust in hodl'ing when Elon secures loans against his shares and tries to dilute everyone elses to recoup the losses and to start a rival to the company your saying is so amazing, that even the owner wants out 🥴🤣
Elon had Tesla public for 7+ years, in which time the stock increased about $10-$15 per share. It shot up during the pandemic because it is sold as a "tech" company and that year Tesla tripled their carbon credit selling, then Elon took it from over $400 a share down to less than half of that at $190, while Alphabet, Google, Apple, Amazon have all recovered back or above to the pandemic highs or close to.
I can't wait for the fall
Tldr: no
Hello TLDR business, I like your content but have some remarks for you.
Saying NVidia has strong fundamentals isn't representative if you don't give some metrics.
It has strong fundamentals if you consider growth of revenue, net income, net debt etc... but if you look at price earning ratio, DCF valuation or things like that, it gives real argument for speculation/over valuation.
Some simple metrics without entering details would also make your channel more "business like".
That could even be a separate video, explaning the basic ratios of finance for later content
Cool
pay to remove information about me that they are not really supposed to sell😅
no thanks 🤣
A few inaccuracies in this one guys.
The CPU/GPU breakdown is incorrect. CPUs can work on tasks in parallel too, they're designed to do lots of different jobs to do with the Operating System, Files, Multimedia etc (it's called a General Purpose Processor). As such they need lots of types of commands and internally they need to be structured to do all these jobs. GPUs only have one job- to do lots of maths calculations very very quickly (for 3D graphics and vectors), this means they don't need as many commands and can be physically designed to be way more efficient. All this also makes them excellent for the repetitive simple calculations needed for AI.
Also CUDA is not tuning software, it's a platform/model for writing software on the nVidia GPUs.
A few technical inaccuracies in this video. The GPU vs. CPU comparison chart made no sense and NVidia most certainly have their own models.
many
What is the definition of a 'boom'?
Which 'boom' has actually 'lasted'? For how long should it last to have been considered as 'lasted'?
If a 'boom' 'lasts' enough, then, almost by concept, it is not a boom, but a plateau...😂😂😂
So..........all this is BS!
Funny story Nancy pelosi made so much money of this (insider trading)
sorry so much about this video is wrong and it was clearly written by someone not familiar with the industry.
you should probably take this video down and re write it
SELL OR BUY?
Im in the sell camp at the moment
Really like the channel and team, but I feel you dropped the ball with this video on many aspects, which also puts in doubt your expertise on other topics
strongly agree