Bitcoin's Turn Is Next — The Easy Money AI Trade Is Over? | Jordi Visser
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What is the main topic discussed in this episode?
again i'm more focused on the second half of the year and the fact that at some point here the agentic side becomes really important for for crypto that's not going to be today's business the ai trade's over the ability of getting seven eight times your money and that is over i think the things people need to watch and i've started to post more nex on this
How do Chinese open-source AI models threaten U.S. LLM monopolies and investor portfolios?
What's going on, guys? Today, we got a great conversation with Jordy Visser. In this conversation, we go deep into the rabbit hole of AI, what's going on with all the open source models. Does this actually present a risk to all of the American large language model labs? And then we also get into what's going to happen to the portfolios. What companies are going to be winners? What companies are going to be losers? Are companies like Google betting their entire company on winning the AI race? What's going on with the war in Iran, interest rates, the Fed, and of course, Bitcoin and crypto? All that and much more in this week's conversation with Jordy Visser. All right, Jordy, all hell has broken loose.
People are very worried about the Chinese open source models. There are people who are advocating that the White House bans them. We now have an open letter coming from NVIDIA and a bunch of other companies saying, no, we should not ban them. We should encourage competition. What is your take as to the impact on investors' portfolio as the AI industry tries to figure out what to do with these open source, open weight models?
It's just a... guess the best way to put it so this week in the video i'm going to do over the weekend i'm going to go through just the ups and downs that are going to come with ai we've talked about them a lot open source is just another one that causes conversation and it's really related to how fast this is moving so open source was always going to be a part of the puzzle always and i say that with certainty because intelligence, again, will all be different. You'll be using different models. There'll be a race to lower boundary. I mean, Satya Nadella on an interview with Dwarkesh Patel talked about the fact that AI would be commoditized. So you get to the point where you know this is going to happen to some degree where there's going to be open source.
So I just think this is another spot where everyone, because of how fast it's moving, we migrate from Anthropix ARR is going parabolic. What does that mean for every single company? Anthropix is going to be involved in every company and disrupting them. To, hey, we don't want Anthropix to have our data. We don't want OpenAI to have our data. We need to have open source. We need to have AI sovereignty. This has all been headed this direction. It's not like the Chinese open source models are a new thing. I just think we've reached a point where The Chinese open source models have caught up in a very, very big way. And the point of what I'm trying to go through is this needs to happen for adoption to lift off.
And the cheaper the models get and the more that open source drives the prices lower, the faster adoption happens and the faster we get into a world that we discussed last week, which is based on routers, where just like in a firm, you have different intelligence levels. Not every firm has all 150 IQ people because there's not that many 150 IQ people. So I think the frontier models will stay the way they are with very high cost. And what the Chinese models are going to run into, and this is the other part, that isn't getting discussed, but if you put everything together, the major story is even for Kimi K3, which started this whole thing, you saw they ran out of compute immediately, and they're going to have to go IPO.
So Eric Schmidt said at the end of last year, and he's repeated it this year, Energy is not going to stop AI. The biggest risk to stop AI is capital. And the capital is needed for the compute. And now we're seeing all of this stuff lead to, hey, maybe it's not the commoditization means adoption is going to go faster. Maybe we don't have the capital to fund all the compute that we need.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:00–0:19
2
How do Chinese open-source AI models threaten U.S. LLM monopolies and investor portfolios?
0:19–5:53
3
Why is capital (not energy) the biggest bottleneck for AI scaling and compute?
5:53–11:09
4
Is Google’s massive CapEx bet likely to pay off and what are the risks?
11:09–14:48
5
Could Anthropic’s growth slow and how will the shift to token efficiency affect margins?
14:48–20:08
6
Why is memory and compute a structural shortage for agentic AI and what does it mean for hardware stocks?
20:08–26:13
7
What is Travis Kalanick building with robotics and how could physical automation change daily life?
26:13–29:00
8
How should the Fed and investors factor robotics-driven deflation and labor changes into rate policy?
29:00–53:29
Speakers
2 identifiedMore from The Pomp Podcast
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