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Thank you for sharing. Financial education is crucial today to show incredible resilience and discipline in the volatile market, masterfully balancing strategy and insight for success. This dedication to continuous learning is inspiring...managed to grow a nest egg of around 100k to a decent 540k in the space of a few weeks... I'm especially grateful to Aaron Addison, whose deep expertise and traditional trading acumen have been invaluable in this challenging, ever-evolving financial landscape..
If we're talking about H100s and not gaming GPUs then it has more to do with the technological advancements than failure of high use. Up and Down cycles are known but this one will take longer
Yup. Don't laugh. But it is Intel. Long story short, I believe in the turnaround story. Mistakes: I bought AMD at $22 and sold at $64. I bought Nvidia in 2019 and sold after a 3.5x..
Very good points, Neil. If Nvidia neglects the low cost, vast volume, inference market, they may be overrun. Especially if someone is able to discover a way to do distributed training in parallel.
Also, if someone discovers a way of doing training on distributed inference nodes in parallel, and they're able to monetize it, they could become the largest company on the planet (I'm looking at you, META+TSLA)
@@nattydred2593If AI continue to become exponentially smarter then the intellectual property of Companies will become worthless since any AI will be able to recreate and even discover new upgraded version of the existing technology. If we end up with some kind of publicly available super AI that also control some robots then everything owned by companies will be pretty much worthless.
@sylvainh2o yeah, that's a risk. At the moment CUDA is a pretty effective moat, for training at least. It would take 100s of man years of concentrated effort to assemble software that could compete with it. Not practical. But AI would make it more feasible for a dedicated team to do that in only a few years. My bet is that Nvidia would not be standing still in the meantime.
Nvda has the CUDA software to run their GPU and IP protected not open source. AMD etc equivalence not as good because NVDA has been working on GPU for a long time. O have only recently resrted buying NVDA based on an average annual growth of 30% for the next 10 years, it could be more in earlier years but less later. I'll have 500 by Dec and add 1200 a year for the next 4 years, thinking of setting up a trust fund for grandkids education.
You'll probably want to optimize the workload and maybe other chips are better optimized/more efficient when they're designed specifically for inference
I don't care whatever the what i would't be touching the stock until few days after the election day, theres a lot of volatility and no sense movements
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🔥$100K Savvy Trader Portfolio: savvytrader.com/Couch_Investor
Thank you for sharing. Financial education is crucial today to show incredible resilience and discipline in the volatile market, masterfully balancing strategy and insight for success. This dedication to continuous learning is inspiring...managed to grow a nest egg of around 100k to a decent 540k in the space of a few weeks... I'm especially grateful to Aaron Addison, whose deep expertise and traditional trading acumen have been invaluable in this challenging, ever-evolving financial landscape..
AARONT44. 🌞🌞🌞🌞🌞
incredibly insightful, at least $50k---$300k profits. Can't stress enough how helpful experts in this field are!
Access to good information is what we investors needs to progress financially and generally in life. this is a good one and I appreciate
TELE
GRAM
Great overview over them magnificents 😊
What about nvda making AI infrastructure for all of India??
Other countries too?
Felix and friends did a video video or the lifecycle of the GPU need to be replaced every three years due to failure from high use
If we're talking about H100s and not gaming GPUs then it has more to do with the technological advancements than failure of high use.
Up and Down cycles are known but this one will take longer
do you own any semi stock ?
Yup. Don't laugh. But it is Intel. Long story short, I believe in the turnaround story.
Mistakes: I bought AMD at $22 and sold at $64. I bought Nvidia in 2019 and sold after a 3.5x..
Very good points, Neil. If Nvidia neglects the low cost, vast volume, inference market, they may be overrun. Especially if someone is able to discover a way to do distributed training in parallel.
Indeed
Also, if someone discovers a way of doing training on distributed inference nodes in parallel, and they're able to monetize it, they could become the largest company on the planet (I'm looking at you, META+TSLA)
@@nattydred2593If AI continue to become exponentially smarter then the intellectual property of Companies will become worthless since any AI will be able to recreate and even discover new upgraded version of the existing technology. If we end up with some kind of publicly available super AI that also control some robots then everything owned by companies will be pretty much worthless.
@sylvainh2o yeah, that's a risk. At the moment CUDA is a pretty effective moat, for training at least. It would take 100s of man years of concentrated effort to assemble software that could compete with it. Not practical.
But AI would make it more feasible for a dedicated team to do that in only a few years. My bet is that Nvidia would not be standing still in the meantime.
Couch, atlassian had the biggest stock jump after earning's report this week - > 20% we completely missed out 😮
Can't miss out if I didn't follow the company
Nvda has the CUDA software to run their GPU and IP protected not open source. AMD etc equivalence not as good because NVDA has been working on GPU for a long time. O have only recently resrted buying NVDA based on an average annual growth of 30% for the next 10 years, it could be more in earlier years but less later. I'll have 500 by Dec and add 1200 a year for the next 4 years, thinking of setting up a trust fund for grandkids education.
Yup, software is the key
But why can't they use the same infrastructure for inference?
Because supply constraint. With only NVIDIAs GPUS are massiv enough to train the models.
should be possible i don't know about the energy consumption.
@@pandoorapirat8644 makes sense :)
You'll probably want to optimize the workload and maybe other chips are better optimized/more efficient when they're designed specifically for inference
@@pandoorapirat8644 yes could be a reason since learning never ends!
Great video thank you! I know its not tesla video but seeing what elon does on xai i do feel like hes neglacting tesla xD
Tesla has their own monster ;)
I don't care whatever the what i would't be touching the stock until few days after the election day, theres a lot of volatility and no sense movements
Completely agree with you
Thumbnail does not match the content
I think it does
@@CouchInvestor now it does, before it said "bad news for nvda", but actually you reported good news for Nvidia