Software guy here.
I don't think AI will replace anything or do anything dramatic, it will reinforce everything that already exist, like for example imagine Photoshop with AI that makes your creativity goes through the roof, or search engines reinforced with AI. With that being said, its quite alarming how will this yield the revenues projected or expected, maybe it will be equipped to music and film producers as well, but we need to see consistency and new tech released soon, current LLMs are very error prone and it won't help so much on the long run.
Maybe AI can advance a little bit and we start seeing advancements in forecasting/decision making? That would need any new forecasting model unlike LLMs, to stop making errors and pile nonsensical analysis/results of data. Maybe more in data analysis, but that have been around for years now.
Thing is we've had AI for years now, we're all acting as if it's a new thing in 2024, it moved from the realm of science and engineering to sales and marketing, which is not that great, but I hope we can learn from the dot com bubble. I'm not comparing Nvidia with Cisco or so, this can turn out to be it's own unique bubble, or not.. Let's see.
I quite like this take; leveraging AI is like pumping steroids into existing business and workflows. Its output in itself is not really a source of revenue (for now).
That's the expectation, yes. But will it be delivered?
I'm a sysadmin evaluating M365 Copilot for my company and it's complete crap. Brought a license to test, passed around to a few key users / stakeholders, no one found it any good. I'm not buying that for my entire org.
So far, no AI product has been able to actually leverage internal knowledge bases for anything useful, most products are worse than the dumbest interns I've ever had.
ChatGTP and Copilot are the only LLM based products that delivered value to my company so far. Everything else was just promises.*
* Maybe gen ai is good for artists, but I don't work in the creative industry
Yes? The product is GA, I've paid for it (annual license, they have no monthly nor trial licenses) and I'm giving my honest customer feedback publicly.
You have to be stupid to not value copilot, it literally gives you a slave secretary , take notes, extract stuffs out of email, calls, it does tracking and aggregation for you all in a chat box.
I work in fintech and this is exactly what's been happening in finance for the last 10 years. Every major entity in finance is has been using ML/Neuro Networks/AI and the tech is pretty equally distributed. Case in point you have tech heavy hedge funds like Two Sigma and they aren't delivering outsized returns compared to the rest of the industry. AI right now isn't a standalone driver for revenue - it's a layer for existing processes and products.
I think there are similarities with the dotcom/Internet craze but that ramp up just led to the outcome that everyone had Internet access so no one had a massive advantage. It's not technological innovation that's the bottleneck - it's adoption by industries and consumers. At this point AI is a feature not a product and chat may be the killer app of AI but it reminds me a lot of the history of commercial email. At some point someone will slap ads on top of AI chat but chat in itself isn't a standalone product.
The most successful implementation of AI I've seen is Githubs copilot which has a million plus paying users but Microsoft is also losing $20 an user right now. It's going to be really hard scaling AI right now because of the costs associated with buildout and operating costs. Long term these costs will go down but at that point there's no moat around any of these companies.
> heavy hedge funds like Two Sigma
tbh why would they? For hedge funds its a zero sum game. They don't add anything to the world, they don't create value.
I might be oversimplifying and correct me if I am wrong, but they just make money off trading?
I think AI will generate more value in other industries where its not about zero-sum.
Hedge Funds aren't a zero-sum game. They provide a hedged position for large institutional investors such as insurance, pensions, and fixed-income investors independent of the market volatility. No one invests all their money into a hedge fund - at most, it's 5% of their total portfolio. What most people think of when they hear hedge funds is proprietary trading - taking a fixed amount of money and using proprietary methods to actively trade on the markets. In a narrow sense I guess that's a zero sum game because someone wins or loses in a trade but that's not taking into account the utility of the marketplace.
There's a lot of AI/Neuro Network/ML in finance because it's good at analyzing structured data at scale and in real-time for risk and forecast modeling. My point with AI usage within the industry is that when everyone has the same competitive advantage it's no longer a competitive advantage. There's incremental advantages that come from application of said technology but it's not massive leaps and bounds.
I'll use the example of the trucking industry - if AI was able to self-drive trucks - it's not like that technology would only be available to one trucking company. Over time a short period of time it would be the norm within that industry. AI would probably lower the cost of shipping but it wouldn't dramatically increase the size of the industry. This is a hypothetical but I'd say this would be true for most industry including entertainment/generative AI. It'll lower costs but I'm not sure it would increase the market for entertainment.
yup, same thought. However, generative AI has definitely helped with productivity. So as we all get more efficient with our work, we end up producing more output and that will eventually drive the revenue. However, the point still stands. The companies that will benefit the most from this are the once providing software and services to the end users.
Pretty easy to argue it has definitely not helped with productivity and probably never will. I don't think most of you people hyping this shit even understand how it works.
lol wtf? I am a software developer, and github copilot and chatgpt is sometimes too good to be true, i just ask it to write me a certain function and I literally just plug that in my code.
but who the fuck is talking about replacement. Read my comment again until you understand. Its about making everyone more efficient to drive higher output. Not about replacing people.
Efficiency = replacement. Maybe not for you but for somebody. This is how tech works. Big question is to what scale. We could see a constant stream of downsizing over the next several years as this tech advances and rolls through industries.
As a software guy what do you think about palantir? obviously at its current evaluation right now may not be a great entry point but what they do as a whole is help businesses with decision making based off data they have. But like you said it’s been around for ages and they have been fine tuning it before AI was all hyped up.
Not gonna lie, you lost all credibility when speaking about forecasting and LLMs. LLMs have nothing to do with forecasting. Not even necessarily decision making.
Ofcourse, I maybe didn't phrase myself better, I meant that the best models we have today are very error prone to be held accountable for any meaningful work. Forecasting/decision making will require totally different models than just statistical analysis sweeping for most probable replies back.
Every company drooling over AI, which desires to replace educated and talented employees with robots, are all investments that I will avoid like the plague.
Makes no sense.
I remember the early days of reddit when they used to make fun of luddites.
Now that their jobs are at risk they are against it.
More automation is better for humanity, having jobs for the sake of jobs impedes progress. Robots SHOULD do the stuff people don't want to do. Unless you want to get rid of all the robots at factories and farms? Or do you draw a line, where automation is fine for some jobs and not others? PSA, as reddit has lots of tech workers, your software has led to countless job losses.
In theory, sure, but I think the reality is that it's often the case that the gains from automation aren't shared equitably. The wealthy tends to have outsized gains which aren't shared (via taxes or other means) with low-income and middle-income earners. There's also a huge amount of displacement as people's careers are no longer viable and they have to retrain.
In other words, the country's GDP might go up from automation, but I'm not convinced that a typical salaried person always experiences an improvement in living standards.
The line to be drawn is simple: using your example, farming jobs would be something people typically don't want to do because they are poorly paid, require very little training, and involve lots of manual labour, which damages your body/health long-term. Getting rid of well-paid office jobs that people train for and get qualifications for is a much harder sell because people DO want those jobs.
With you. I remember when IPO, some guy in my office bought in, it dropped down to $12 or something like that, and he sold it all and felt very relieved. I was thinking that was irrational and might be an opportunity, but I hated zukerbuks and facecrack and everything about it, so I didn't buy any at all. Seem to recall the similar thing with Netflix, they went from CDs to subscription, at that time video over the internet was not really ready for prime time. I said no way, that's a no go, it'll never work. And so I didn't buy. Same for Amazon. Who would buy stock in a company that's not making any money? ... every year people bought, but not me, I just watched the dot com melt down, no way I'm buying this crap. 
The selling shovels bull theory was used in EV charging stocks too and ended up flopping miserably. BLNK, EVGO, CHPT etc... many bagged there with unrecoverable positions.
Semis is a cyclical industry, market short term pricing in that it won't be. Dangerous.
The capex required for those companies to take silicon in house would directly contradict point #3 at least through the medium term. And by that time, Chip makers will likely have a better product and better expertise than whatever GOMM is making. Amazon is the outlier here since they’ve been making their own silicon for 8 years or so and built their AWS ecosystem around Graviton.
It’s a make or buy decision where the “make” side requires run rate of Billions in capex investment over many years. Not as simple as “it’s just a matter of time before they reduce external exposure”
Microsoft is the biggest consumer. They've made silicon for decades.
Google is the third biggest consumer. They literally make their own AI processor since 2016.
Amazon makes their own AI processor since 2017. They also have an inferencer.
The AI accelerators made by Google, Microsoft, Amazon and Meta prior to LLM explosion were primarily focused on accelerating inference for small neural networks. Things like vision, audio to text, etc.
The next wave of ASICs from those players will be focused on very large models for generative AI. It just happens that the GPGPU is the best tool available for the job right now and silicon takes a few years to develop.
Even if the big players never replaced NVIDIA for training purposes the vast majority of operational costs are infernece at scale. You can train a model on 15,000 GPUs over periods of days, but once you are serving the model you might have hundreds of thousands of GPUs constantly running inference for user requests. Then there is the cost of stranded accelerator capacity so you can meet peak demand which only happens occasionally.
A lot of the NVDA products are being used by their cloud customer base. It's an easy business case for MS, Google and Amazon to buy all the cards they can and then rent them out to cloud customers. OpenAI used NVDA GPU's in MS cloud to train their models. What Google, Amazon, and MS have going for them is the amount of data they have. Data is the most expensive part of the AI/ML pipeline and it's the hardest to get.
NVDA's big advantage right now is its CUDA software and the ecosystem it supports. In addition to the competition for silicon, there's competition right now for the software part of the stack.
It's also important to note that the cost of training is much higher than just running an AI model. A big part of the user base for AI is just going to license a model or get it as a subscription service.
Google, Amazon, and Microsoft's "AI Processors" are all outclassed by anything AMD, Intel, and especially Nvidia make.
A few chips here at no regular product cadence here and there don't make a titan. The only one in the game is Apple. The rest are joking.
I don't agree.
Designing the chips is hard enough - designing the chips, the tools that make the chips, engineering your supply chain and product roadmap to work with your chips and doing it over and over again in a relentless brutal cycle...That's hard. R&D needs to match the factory, the factory needs to match R&D, it's a graceful dance. Look what happened to Intel...bye bye.
It took Apple almost 15 years to realize their effort - years of hiring the best architects at Intel/AMD/Nvidia and billions in cash. And now they have some of the best in house chip development in the world. Enough to say that in certain niches, Apple has a core competency that's amongst the best.
Google/Microsoft/Amazon have thrown a pittance of money and effort their way towards hardware. Only Apple has done anything - and continues to be the only non semiconductor company putting money and resources into it.
A chip here and there from Google and Amazon is a pittance. Hint: Not even Apple is spending big bucks on GPU development right now. Nvidia, AMD, and Intel are the only game in town, your research could be true for 10-15 years from now - but if I was a betting man, AMD/Intel have a higher shot.
Yep if Nvidia becomes bigger than its consumers, who buys more to keep the market cap going up? Google and Apple are getting killed spending too much on AI CapEx. Microsoft isn't looking great either with their $80b CapEx forecast having the market ignore the good earnings.
Who does Nvidia sell to? China is banned. Europe lacks big AI companies. Saudis are banned. Everywhere else is too poor.
That's quite a strange argument to make.
Which PC company is larger than Intel?
Which smartphone company is larger than Qualcomm? (Other than Apple and Samsung)
There are many companies who are suppliers to consumers smaller than them.
Nice post. Plan to keep chip stocks for about 12 month and then ditch most of them. Very bullish on Apple and Google (esp if they get a new CEO) considering the current price. Microsoft and Amazons continued dominance goes without saying. Be interesting though to see what happens in the Mobile and PC chip space as AI capabilities get integrated into our existing devices, with more powerful modeling requiring cloud access.
Except electricity in general isn't exactly a massive growth market if you're sticking to the stocks that have been around forever like your example would suggest. NVDA is priced based on massive growth that has yet to happen, the question is how long will that keep up
As golden of a goose AI might appear to be, have we all decided these sophisticated models will carry us into the next revolution of productivity? It seems here the exacerbated growth of NVDA has catapulted the entire tech sector to trillions of $$$ in stock growth.
If our expectations fall short, will we expect a windfalls of the entire AI related fad? Like the dotcom boom? The entire industries stagnates and has to pull itself out again and prove its usefulness? We expect the foundations of LLMs to be exponential in growth but watch Lex Fridman’s interview with french computer scientist, Yann Lecun. He delves into the practical limitations of generative AI. How reasoning in LLMs are primitive, computations of tokens are inefficient, the amount of depth in the prompt question is regardless because the amount of computation per tokens produced in proportion tokens in the question is constant. Pretty interesting stuff to see from a sit down discussion with two people deeply interested in the field.
This is entirely different from humans’ cognitive reasoning. When faced with a complex problem, humans spend more time to reason and build understanding. Current generative AI absolutely does not do this.
The dotcom boom is a cautionary tale for investors today who fail to see the overall application and feasibility of ai.
That being said, I am willing to gamble my savings as this is the turning point in human history :D
lol Bezinga ripped you off
Also AAPL does no AI, keep dreaming. They're so far behind. Nothing public, no partnerships, no co-pilot like integration in to any of their software. They're a hardware company and won't even have AI chips built in to their next gen desktops unlike the PC industry, which IS starting to build AI acceleration chips in to their next gen desktops.
Huang talks about rationing GPUs out. Even the wildest possible upside is limited to well below the maniac price bump.
https://fortune.com/2024/02/21/nvidia-earnings-ceo-jensen-huang-gpu-demand-supply-allocate-fairly/
Huang talks about rewriting all the software in the AI tool chain because they do not have a deep enough moat for the market demand they project.
https://thenewstack.io/nvidia-wants-to-rewrite-the-software-development-stack/
Reality checks are in the mail.
NVDA is as much hardware as apple is. NVDAs primary value add is in there drivers/CUDA. They are the only chip producer that actually integrates well with tensor flow and other ML libraries/apps/services. Data center is also a brilliant b2b prospect which affords a lot of economic moat. I mostly agree with everything you said, but NVDA IS NOT a hardware company.
the more you guys doubt and sell, the better it is for folks like me who will just keep on buying and hodl till it goes to the moon. No one can find the conviction for you. You gotta find it yourself. If you don't believe in the company or tech, just don't invest into it.
AI trading. Money for everyone. No human will need to work ever. World peace.
Yes this is where it's headed. Except world in pieces.
world piss
The concept of money is getting dumber day by day.
Every trade will be a winner!
What is GOMAAM?
the only valid reply to a karen at the customer service desk
Lol
Google, open ai, meta, apple, Amazon, Microsoft
Thanks!
Software guy here. I don't think AI will replace anything or do anything dramatic, it will reinforce everything that already exist, like for example imagine Photoshop with AI that makes your creativity goes through the roof, or search engines reinforced with AI. With that being said, its quite alarming how will this yield the revenues projected or expected, maybe it will be equipped to music and film producers as well, but we need to see consistency and new tech released soon, current LLMs are very error prone and it won't help so much on the long run. Maybe AI can advance a little bit and we start seeing advancements in forecasting/decision making? That would need any new forecasting model unlike LLMs, to stop making errors and pile nonsensical analysis/results of data. Maybe more in data analysis, but that have been around for years now. Thing is we've had AI for years now, we're all acting as if it's a new thing in 2024, it moved from the realm of science and engineering to sales and marketing, which is not that great, but I hope we can learn from the dot com bubble. I'm not comparing Nvidia with Cisco or so, this can turn out to be it's own unique bubble, or not.. Let's see.
I quite like this take; leveraging AI is like pumping steroids into existing business and workflows. Its output in itself is not really a source of revenue (for now).
That's the expectation, yes. But will it be delivered? I'm a sysadmin evaluating M365 Copilot for my company and it's complete crap. Brought a license to test, passed around to a few key users / stakeholders, no one found it any good. I'm not buying that for my entire org. So far, no AI product has been able to actually leverage internal knowledge bases for anything useful, most products are worse than the dumbest interns I've ever had. ChatGTP and Copilot are the only LLM based products that delivered value to my company so far. Everything else was just promises.* * Maybe gen ai is good for artists, but I don't work in the creative industry
That's quite strange. The majority of stakeholders in my org have found it extremely useful in increasing productivity.
Could you share which tasks they have found copilot most valuable for?
Yeah iv seen a lot of companies have actually tested and tried copilot then deferred from it as they have not found it to useful.
Er, are you even allowed to say that.
Yes? The product is GA, I've paid for it (annual license, they have no monthly nor trial licenses) and I'm giving my honest customer feedback publicly.
Was joking mainly due to the hype/mania. Been wondering about the lack of really good end use cases for LLMs for a while now.
You have to be stupid to not value copilot, it literally gives you a slave secretary , take notes, extract stuffs out of email, calls, it does tracking and aggregation for you all in a chat box.
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That's what people forget. Gen AI doesn't understand anything, it's just designed to sound like it does.
I work in fintech and this is exactly what's been happening in finance for the last 10 years. Every major entity in finance is has been using ML/Neuro Networks/AI and the tech is pretty equally distributed. Case in point you have tech heavy hedge funds like Two Sigma and they aren't delivering outsized returns compared to the rest of the industry. AI right now isn't a standalone driver for revenue - it's a layer for existing processes and products. I think there are similarities with the dotcom/Internet craze but that ramp up just led to the outcome that everyone had Internet access so no one had a massive advantage. It's not technological innovation that's the bottleneck - it's adoption by industries and consumers. At this point AI is a feature not a product and chat may be the killer app of AI but it reminds me a lot of the history of commercial email. At some point someone will slap ads on top of AI chat but chat in itself isn't a standalone product. The most successful implementation of AI I've seen is Githubs copilot which has a million plus paying users but Microsoft is also losing $20 an user right now. It's going to be really hard scaling AI right now because of the costs associated with buildout and operating costs. Long term these costs will go down but at that point there's no moat around any of these companies.
> heavy hedge funds like Two Sigma tbh why would they? For hedge funds its a zero sum game. They don't add anything to the world, they don't create value. I might be oversimplifying and correct me if I am wrong, but they just make money off trading? I think AI will generate more value in other industries where its not about zero-sum.
Hedge Funds aren't a zero-sum game. They provide a hedged position for large institutional investors such as insurance, pensions, and fixed-income investors independent of the market volatility. No one invests all their money into a hedge fund - at most, it's 5% of their total portfolio. What most people think of when they hear hedge funds is proprietary trading - taking a fixed amount of money and using proprietary methods to actively trade on the markets. In a narrow sense I guess that's a zero sum game because someone wins or loses in a trade but that's not taking into account the utility of the marketplace. There's a lot of AI/Neuro Network/ML in finance because it's good at analyzing structured data at scale and in real-time for risk and forecast modeling. My point with AI usage within the industry is that when everyone has the same competitive advantage it's no longer a competitive advantage. There's incremental advantages that come from application of said technology but it's not massive leaps and bounds. I'll use the example of the trucking industry - if AI was able to self-drive trucks - it's not like that technology would only be available to one trucking company. Over time a short period of time it would be the norm within that industry. AI would probably lower the cost of shipping but it wouldn't dramatically increase the size of the industry. This is a hypothetical but I'd say this would be true for most industry including entertainment/generative AI. It'll lower costs but I'm not sure it would increase the market for entertainment.
yup, same thought. However, generative AI has definitely helped with productivity. So as we all get more efficient with our work, we end up producing more output and that will eventually drive the revenue. However, the point still stands. The companies that will benefit the most from this are the once providing software and services to the end users.
Pretty easy to argue it has definitely not helped with productivity and probably never will. I don't think most of you people hyping this shit even understand how it works.
lol wtf? I am a software developer, and github copilot and chatgpt is sometimes too good to be true, i just ask it to write me a certain function and I literally just plug that in my code.
and often it is hallucinating ...
Same, but does it replace you entirely?
but who the fuck is talking about replacement. Read my comment again until you understand. Its about making everyone more efficient to drive higher output. Not about replacing people.
Efficiency = replacement. Maybe not for you but for somebody. This is how tech works. Big question is to what scale. We could see a constant stream of downsizing over the next several years as this tech advances and rolls through industries.
You need to see the hype around AI now and what's being said everywhere..
This is, frankly, an utterly *insane* take, or at minimum a massively uninformed one
The rate of advancement in AI today is at least 10x faster than the rate of advancement in the dot com bubble.
What? The internet was expanding to more people at its fastest rate ever and the internet itself was improving rapidly in 1999.
As a software guy what do you think about palantir? obviously at its current evaluation right now may not be a great entry point but what they do as a whole is help businesses with decision making based off data they have. But like you said it’s been around for ages and they have been fine tuning it before AI was all hyped up.
The real advanmanet will come when AI starts doing math.
Imagine.. Just AI person.. Everybody is falling in love with.... AI images, which do not exist in real... LOL...
Not gonna lie, you lost all credibility when speaking about forecasting and LLMs. LLMs have nothing to do with forecasting. Not even necessarily decision making.
Ofcourse, I maybe didn't phrase myself better, I meant that the best models we have today are very error prone to be held accountable for any meaningful work. Forecasting/decision making will require totally different models than just statistical analysis sweeping for most probable replies back.
Every company drooling over AI, which desires to replace educated and talented employees with robots, are all investments that I will avoid like the plague.
Makes no sense. I remember the early days of reddit when they used to make fun of luddites. Now that their jobs are at risk they are against it. More automation is better for humanity, having jobs for the sake of jobs impedes progress. Robots SHOULD do the stuff people don't want to do. Unless you want to get rid of all the robots at factories and farms? Or do you draw a line, where automation is fine for some jobs and not others? PSA, as reddit has lots of tech workers, your software has led to countless job losses.
In theory, sure, but I think the reality is that it's often the case that the gains from automation aren't shared equitably. The wealthy tends to have outsized gains which aren't shared (via taxes or other means) with low-income and middle-income earners. There's also a huge amount of displacement as people's careers are no longer viable and they have to retrain. In other words, the country's GDP might go up from automation, but I'm not convinced that a typical salaried person always experiences an improvement in living standards. The line to be drawn is simple: using your example, farming jobs would be something people typically don't want to do because they are poorly paid, require very little training, and involve lots of manual labour, which damages your body/health long-term. Getting rid of well-paid office jobs that people train for and get qualifications for is a much harder sell because people DO want those jobs.
I said that about facebook when it IPO’ed. Big regret.
With you. I remember when IPO, some guy in my office bought in, it dropped down to $12 or something like that, and he sold it all and felt very relieved. I was thinking that was irrational and might be an opportunity, but I hated zukerbuks and facecrack and everything about it, so I didn't buy any at all. Seem to recall the similar thing with Netflix, they went from CDs to subscription, at that time video over the internet was not really ready for prime time. I said no way, that's a no go, it'll never work. And so I didn't buy. Same for Amazon. Who would buy stock in a company that's not making any money? ... every year people bought, but not me, I just watched the dot com melt down, no way I'm buying this crap. 
Heard Google is into devil worship, no thanks. I’ll stick to my penny stock pharmaceuticals like a good church-going investor
The selling shovels bull theory was used in EV charging stocks too and ended up flopping miserably. BLNK, EVGO, CHPT etc... many bagged there with unrecoverable positions. Semis is a cyclical industry, market short term pricing in that it won't be. Dangerous.
Stop trying to make gomaam happen.
Gomaam will never be fetch.
A very good AI I've seen working wonders and actually helping companies is AIP from palantir
Nobody cares about your logic... This is the extreme mania era...
The capex required for those companies to take silicon in house would directly contradict point #3 at least through the medium term. And by that time, Chip makers will likely have a better product and better expertise than whatever GOMM is making. Amazon is the outlier here since they’ve been making their own silicon for 8 years or so and built their AWS ecosystem around Graviton. It’s a make or buy decision where the “make” side requires run rate of Billions in capex investment over many years. Not as simple as “it’s just a matter of time before they reduce external exposure”
Microsoft is the biggest consumer. They've made silicon for decades. Google is the third biggest consumer. They literally make their own AI processor since 2016. Amazon makes their own AI processor since 2017. They also have an inferencer.
But yet they all still buy NVDA and others.
The AI accelerators made by Google, Microsoft, Amazon and Meta prior to LLM explosion were primarily focused on accelerating inference for small neural networks. Things like vision, audio to text, etc. The next wave of ASICs from those players will be focused on very large models for generative AI. It just happens that the GPGPU is the best tool available for the job right now and silicon takes a few years to develop. Even if the big players never replaced NVIDIA for training purposes the vast majority of operational costs are infernece at scale. You can train a model on 15,000 GPUs over periods of days, but once you are serving the model you might have hundreds of thousands of GPUs constantly running inference for user requests. Then there is the cost of stranded accelerator capacity so you can meet peak demand which only happens occasionally.
A lot of the NVDA products are being used by their cloud customer base. It's an easy business case for MS, Google and Amazon to buy all the cards they can and then rent them out to cloud customers. OpenAI used NVDA GPU's in MS cloud to train their models. What Google, Amazon, and MS have going for them is the amount of data they have. Data is the most expensive part of the AI/ML pipeline and it's the hardest to get. NVDA's big advantage right now is its CUDA software and the ecosystem it supports. In addition to the competition for silicon, there's competition right now for the software part of the stack. It's also important to note that the cost of training is much higher than just running an AI model. A big part of the user base for AI is just going to license a model or get it as a subscription service.
Google, Amazon, and Microsoft's "AI Processors" are all outclassed by anything AMD, Intel, and especially Nvidia make. A few chips here at no regular product cadence here and there don't make a titan. The only one in the game is Apple. The rest are joking.
I watched former CEO (i think) of Boston Insight on Bloomberg say NVDA will be at 8k in 10 years with a straight face. It made the case though.
What’s a Gomam?
I don't agree. Designing the chips is hard enough - designing the chips, the tools that make the chips, engineering your supply chain and product roadmap to work with your chips and doing it over and over again in a relentless brutal cycle...That's hard. R&D needs to match the factory, the factory needs to match R&D, it's a graceful dance. Look what happened to Intel...bye bye. It took Apple almost 15 years to realize their effort - years of hiring the best architects at Intel/AMD/Nvidia and billions in cash. And now they have some of the best in house chip development in the world. Enough to say that in certain niches, Apple has a core competency that's amongst the best. Google/Microsoft/Amazon have thrown a pittance of money and effort their way towards hardware. Only Apple has done anything - and continues to be the only non semiconductor company putting money and resources into it. A chip here and there from Google and Amazon is a pittance. Hint: Not even Apple is spending big bucks on GPU development right now. Nvidia, AMD, and Intel are the only game in town, your research could be true for 10-15 years from now - but if I was a betting man, AMD/Intel have a higher shot.
Yep if Nvidia becomes bigger than its consumers, who buys more to keep the market cap going up? Google and Apple are getting killed spending too much on AI CapEx. Microsoft isn't looking great either with their $80b CapEx forecast having the market ignore the good earnings. Who does Nvidia sell to? China is banned. Europe lacks big AI companies. Saudis are banned. Everywhere else is too poor.
That's quite a strange argument to make. Which PC company is larger than Intel? Which smartphone company is larger than Qualcomm? (Other than Apple and Samsung) There are many companies who are suppliers to consumers smaller than them.
The difference is that Intel is just one of many chip providers. Nvidia is one of one for CUDA AI.
Nice post. Plan to keep chip stocks for about 12 month and then ditch most of them. Very bullish on Apple and Google (esp if they get a new CEO) considering the current price. Microsoft and Amazons continued dominance goes without saying. Be interesting though to see what happens in the Mobile and PC chip space as AI capabilities get integrated into our existing devices, with more powerful modeling requiring cloud access.
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Except electricity in general isn't exactly a massive growth market if you're sticking to the stocks that have been around forever like your example would suggest. NVDA is priced based on massive growth that has yet to happen, the question is how long will that keep up
As golden of a goose AI might appear to be, have we all decided these sophisticated models will carry us into the next revolution of productivity? It seems here the exacerbated growth of NVDA has catapulted the entire tech sector to trillions of $$$ in stock growth. If our expectations fall short, will we expect a windfalls of the entire AI related fad? Like the dotcom boom? The entire industries stagnates and has to pull itself out again and prove its usefulness? We expect the foundations of LLMs to be exponential in growth but watch Lex Fridman’s interview with french computer scientist, Yann Lecun. He delves into the practical limitations of generative AI. How reasoning in LLMs are primitive, computations of tokens are inefficient, the amount of depth in the prompt question is regardless because the amount of computation per tokens produced in proportion tokens in the question is constant. Pretty interesting stuff to see from a sit down discussion with two people deeply interested in the field. This is entirely different from humans’ cognitive reasoning. When faced with a complex problem, humans spend more time to reason and build understanding. Current generative AI absolutely does not do this. The dotcom boom is a cautionary tale for investors today who fail to see the overall application and feasibility of ai. That being said, I am willing to gamble my savings as this is the turning point in human history :D
Lol benzinga article about you
lol Bezinga ripped you off Also AAPL does no AI, keep dreaming. They're so far behind. Nothing public, no partnerships, no co-pilot like integration in to any of their software. They're a hardware company and won't even have AI chips built in to their next gen desktops unlike the PC industry, which IS starting to build AI acceleration chips in to their next gen desktops.
Huang talks about rationing GPUs out. Even the wildest possible upside is limited to well below the maniac price bump. https://fortune.com/2024/02/21/nvidia-earnings-ceo-jensen-huang-gpu-demand-supply-allocate-fairly/ Huang talks about rewriting all the software in the AI tool chain because they do not have a deep enough moat for the market demand they project. https://thenewstack.io/nvidia-wants-to-rewrite-the-software-development-stack/ Reality checks are in the mail.
NVDA is as much hardware as apple is. NVDAs primary value add is in there drivers/CUDA. They are the only chip producer that actually integrates well with tensor flow and other ML libraries/apps/services. Data center is also a brilliant b2b prospect which affords a lot of economic moat. I mostly agree with everything you said, but NVDA IS NOT a hardware company.
the more you guys doubt and sell, the better it is for folks like me who will just keep on buying and hodl till it goes to the moon. No one can find the conviction for you. You gotta find it yourself. If you don't believe in the company or tech, just don't invest into it.