Offshore
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The Long Investor
Market experienced a massive influx of new capital in November and December ‘23 as retail investors returned to the market to chase.
Usually a strong sign that the market is in Wave 5, which indicates a top
Wave 5 went parabolic and jumped 26% over 5 months.
Market is now being hit by multiple negative catalysts right around the same time.
The market also initially considered that the first rate cut would happen in March
This is now delayed but the market is keeping to its original plan
Pulling back when Q1 ended
I believe the market will continue to pull back for the next few months and then rally for Wave A leading up to the US election in November, before pulling back again afterwards to complete Wave C
I have added $SPY and $QQQ charts here for free over the last 2 day to show this interpretation.
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Market experienced a massive influx of new capital in November and December ‘23 as retail investors returned to the market to chase.
Usually a strong sign that the market is in Wave 5, which indicates a top
Wave 5 went parabolic and jumped 26% over 5 months.
Market is now being hit by multiple negative catalysts right around the same time.
The market also initially considered that the first rate cut would happen in March
This is now delayed but the market is keeping to its original plan
Pulling back when Q1 ended
I believe the market will continue to pull back for the next few months and then rally for Wave A leading up to the US election in November, before pulling back again afterwards to complete Wave C
I have added $SPY and $QQQ charts here for free over the last 2 day to show this interpretation.
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The Long Investor
Is this the strangest conflict yet?
- giving days notice of each attack
- giving notice on targets
I did not write the Art of War but I’m pretty sure this is not how its usually done
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Is this the strangest conflict yet?
- giving days notice of each attack
- giving notice on targets
I did not write the Art of War but I’m pretty sure this is not how its usually done
IRAN IRGC STATES THAT IRAN WILL TARGET ISRAELI NUCLEAR SITES WITH COUNTERATTACK tweet
X (formerly Twitter)
zerohedge (@zerohedge) on X
IRAN IRGC STATES THAT IRAN WILL TARGET ISRAELI NUCLEAR SITES WITH COUNTERATTACK
Offshore
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The Long Investor
National Do Not Open Your Portfolio Account tomorrow.
Unless you’ve hedged with Silver, Oil and defensive stocks.
Which is what we have done. https://t.co/1ixFIaSZDD
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National Do Not Open Your Portfolio Account tomorrow.
Unless you’ve hedged with Silver, Oil and defensive stocks.
Which is what we have done. https://t.co/1ixFIaSZDD
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Offshore
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The Long Investor
$TSLA hit $144 in Robinhood overnight trading and then it got halted.
Interesting
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$TSLA hit $144 in Robinhood overnight trading and then it got halted.
Interesting
$HOOD Robinhood halts 24 hr trading. https://t.co/oVkbJf1T67 tweet
Offshore
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The Long Investor
In the space of 2 weeks, the number of companies in the S&P500 with an RSI below 30 went from 6 to 64.
10 X jump.
Market is looking weak.
$SPY https://t.co/DMfeR0n7d5
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In the space of 2 weeks, the number of companies in the S&P500 with an RSI below 30 went from 6 to 64.
10 X jump.
Market is looking weak.
$SPY https://t.co/DMfeR0n7d5
There are only 6 companies in the S&P 500 with RSI's below 30, 3 of them should be of considerable interest to you:
$UNH
$NKE
$LULU tweet
Offshore
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Hidden Value Gems
Most analysts are trained to forecast next-year earnings and a relevant multiple, but few focus on how long a company will stay in business. During the second session of my first Investment Masterclass, we discussed the longevity effect in investing, among other points that are often missed in financial analysis.
There is still space left for the second cohort in June.
You can join the waitlist on the Hidden Value Gems website.
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Most analysts are trained to forecast next-year earnings and a relevant multiple, but few focus on how long a company will stay in business. During the second session of my first Investment Masterclass, we discussed the longevity effect in investing, among other points that are often missed in financial analysis.
There is still space left for the second cohort in June.
You can join the waitlist on the Hidden Value Gems website.
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AkhenOsiris
$META $NVDA
Zuckerberg on buying H100s back in 2022, initially for Reels:
"The corpus of content candidates that we could potentially show you expanded from on the order of thousands to on the order of hundreds of millions. It needed a completely different infrastructure. We started working on doing that and we were constrained on the infrastructure in catching up to what TikTok was doing as quickly as we wanted to. I basically looked at that and I was like “hey, we have to make sure that we're never in this situation again. So let's order enough GPUs to do what we need to do on Reels and ranking content and feed. But let's also double that.” Again, our normal principle is that there's going to be something on the horizon that we can't see yet.
We thought it was going to be something that had to do with training large models. At the time I thought it was probably going to be something that had to do with content. It’s just the pattern matching of running the company, there's always another thing. At that time I was so deep into trying to get the recommendations working for Reels and other content. That’s just such a big unlock for Instagram and Facebook now, being able to show people content that's interesting to them from people that they're not even following.
But that ended up being a very good decision in retrospect. And it came from being behind. It wasn't like “oh, I was so far ahead.” Actually, most of the times where we make some decision that ends up seeming good is because we messed something up before and just didn't want to repeat the mistake."
Source: youtu.be/bc6uFV9CJGg
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$META $NVDA
Zuckerberg on buying H100s back in 2022, initially for Reels:
"The corpus of content candidates that we could potentially show you expanded from on the order of thousands to on the order of hundreds of millions. It needed a completely different infrastructure. We started working on doing that and we were constrained on the infrastructure in catching up to what TikTok was doing as quickly as we wanted to. I basically looked at that and I was like “hey, we have to make sure that we're never in this situation again. So let's order enough GPUs to do what we need to do on Reels and ranking content and feed. But let's also double that.” Again, our normal principle is that there's going to be something on the horizon that we can't see yet.
We thought it was going to be something that had to do with training large models. At the time I thought it was probably going to be something that had to do with content. It’s just the pattern matching of running the company, there's always another thing. At that time I was so deep into trying to get the recommendations working for Reels and other content. That’s just such a big unlock for Instagram and Facebook now, being able to show people content that's interesting to them from people that they're not even following.
But that ended up being a very good decision in retrospect. And it came from being behind. It wasn't like “oh, I was so far ahead.” Actually, most of the times where we make some decision that ends up seeming good is because we messed something up before and just didn't want to repeat the mistake."
Source: youtu.be/bc6uFV9CJGg
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AkhenOsiris
$META
Zuckerberg on AI:
"Our bet is that it's going to basically change all of the products. I think that there's going to be a kind of Meta AI general assistant product. I think that that will shift from something that feels more like a chatbot, where you ask a question and it formulates an answer, to things where you're giving it more complicated tasks and then it goes away and does them. That's going to take a lot of inference and it's going to take a lot of compute in other ways too."
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$META
Zuckerberg on AI:
"Our bet is that it's going to basically change all of the products. I think that there's going to be a kind of Meta AI general assistant product. I think that that will shift from something that feels more like a chatbot, where you ask a question and it formulates an answer, to things where you're giving it more complicated tasks and then it goes away and does them. That's going to take a lot of inference and it's going to take a lot of compute in other ways too."
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AkhenOsiris
$META
Zuckerberg on 350,000 GPUs, Inference:
"That's the whole fleet. We built two, I think 22,000 or 24,000 clusters that are the single clusters that we have for training the big models, obviously across a lot of the stuff that we do. A lot of our stuff goes towards training Reels models and Facebook News Feed and Instagram Feed. Inference is a huge thing for us because we serve a ton of people. Our ratio of inference compute required to training is probably much higher than most other companies that are doing this stuff just because of the sheer volume of the community that we're serving."
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$META
Zuckerberg on 350,000 GPUs, Inference:
"That's the whole fleet. We built two, I think 22,000 or 24,000 clusters that are the single clusters that we have for training the big models, obviously across a lot of the stuff that we do. A lot of our stuff goes towards training Reels models and Facebook News Feed and Instagram Feed. Inference is a huge thing for us because we serve a ton of people. Our ratio of inference compute required to training is probably much higher than most other companies that are doing this stuff just because of the sheer volume of the community that we're serving."
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AkhenOsiris
$META $NVDA
Zuckerberg on AI, GPUs, scarcity, runway:
I think it's likely enough that we'll keep going. I think it’s worth investing the $10Bs or $100B+ in building the infrastructure and assuming that if it keeps going you're going to get some really amazing things that are going to make amazing products. I don't think anyone in the industry can really tell you that it will continue scaling at that rate for sure. In general in history, you hit bottlenecks at certain points. Now there's so much energy on this that maybe those bottlenecks get knocked over pretty quickly. I think that’s an interesting question.
Well, there are going to be different bottlenecks. Over the last few years, I think there was this issue of GPU production. Even companies that had the money to pay for the GPUs couldn't necessarily get as many as they wanted because there were all these supply constraints. Now I think that's sort of getting less. So you're seeing a bunch of companies thinking now about investing a lot of money in building out these things. I think that that will go on for some period of time. There is a capital question. At what point does it stop being worth it to put the capital in?
I actually think before we hit that, you're going to run into energy constraints. I don't think anyone's built a gigawatt single training cluster yet. You run into these things that just end up being slower in the world. Getting energy permitted is a very heavily regulated government function. You're going from software, which is somewhat regulated and I'd argue it’s more regulated than a lot of people in the tech community feel. Obviously it’s different if you're starting a small company, maybe you feel that less. We interact with different governments and regulators and we have lots of rules that we need to follow and make sure we do a good job with around the world. But I think that there's no doubt about energy.
If you're talking about building large new power plants or large build-outs and then building transmission lines that cross other private or public land, that’s just a heavily regulated thing. You're talking about many years of lead time. If we wanted to stand up some massive facility, powering that is a very long-term project. I think people do it but I don't think this is something that can be quite as magical as just getting to a level of AI, getting a bunch of capital and putting it in, and then all of a sudden the models are just going to… You do hit different bottlenecks along the way.
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$META $NVDA
Zuckerberg on AI, GPUs, scarcity, runway:
I think it's likely enough that we'll keep going. I think it’s worth investing the $10Bs or $100B+ in building the infrastructure and assuming that if it keeps going you're going to get some really amazing things that are going to make amazing products. I don't think anyone in the industry can really tell you that it will continue scaling at that rate for sure. In general in history, you hit bottlenecks at certain points. Now there's so much energy on this that maybe those bottlenecks get knocked over pretty quickly. I think that’s an interesting question.
Well, there are going to be different bottlenecks. Over the last few years, I think there was this issue of GPU production. Even companies that had the money to pay for the GPUs couldn't necessarily get as many as they wanted because there were all these supply constraints. Now I think that's sort of getting less. So you're seeing a bunch of companies thinking now about investing a lot of money in building out these things. I think that that will go on for some period of time. There is a capital question. At what point does it stop being worth it to put the capital in?
I actually think before we hit that, you're going to run into energy constraints. I don't think anyone's built a gigawatt single training cluster yet. You run into these things that just end up being slower in the world. Getting energy permitted is a very heavily regulated government function. You're going from software, which is somewhat regulated and I'd argue it’s more regulated than a lot of people in the tech community feel. Obviously it’s different if you're starting a small company, maybe you feel that less. We interact with different governments and regulators and we have lots of rules that we need to follow and make sure we do a good job with around the world. But I think that there's no doubt about energy.
If you're talking about building large new power plants or large build-outs and then building transmission lines that cross other private or public land, that’s just a heavily regulated thing. You're talking about many years of lead time. If we wanted to stand up some massive facility, powering that is a very long-term project. I think people do it but I don't think this is something that can be quite as magical as just getting to a level of AI, getting a bunch of capital and putting it in, and then all of a sudden the models are just going to… You do hit different bottlenecks along the way.
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AkhenOsiris
$META $NVDA
By when will the Llama models be trained on your own custom silicon?
Zuckerberg:
"Soon, not Llama-4. The approach that we took is we first built custom silicon that could handle inference for our ranking and recommendation type stuff, so Reels, News Feed ads, etc. That was consuming a lot of GPUs. When we were able to move that to our own silicon, we're now able to use the more expensive NVIDIA GPUs only for training. At some point we will hopefully have silicon ourselves that we can be using for at first training some of the simpler things, then eventually training these really large models. In the meantime, I'd say the program is going quite well and we're just rolling it out methodically and we have a long-term roadmap for it."
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$META $NVDA
By when will the Llama models be trained on your own custom silicon?
Zuckerberg:
"Soon, not Llama-4. The approach that we took is we first built custom silicon that could handle inference for our ranking and recommendation type stuff, so Reels, News Feed ads, etc. That was consuming a lot of GPUs. When we were able to move that to our own silicon, we're now able to use the more expensive NVIDIA GPUs only for training. At some point we will hopefully have silicon ourselves that we can be using for at first training some of the simpler things, then eventually training these really large models. In the meantime, I'd say the program is going quite well and we're just rolling it out methodically and we have a long-term roadmap for it."
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