Section Insights
Value Distribution in AI
Where does the value go in AI?
The value in AI is generated primarily by the end user, who pays significantly for the models. The app layer has generated little value, while the model layer has transitioned from negative to positive gross margins.
- End users are the primary value generators in AI.
- The app layer has not yet realized significant value.
- The model layer's profitability has improved dramatically over the past year.
Model Layer Profitability
How has the model layer's value changed over time?
A year ago, the model layer was generating negative gross margins, but it has since shifted to generating substantial positive margins.
- The model layer's financial performance has improved significantly.
- Previous losses were due to high costs in the hardware supply chain.
Hardware Supply Chain Dynamics
What role did the hardware supply chain play in value creation?
The hardware supply chain was generating gross margins while the model layer was losing money, indicating a misalignment in value creation.
- The hardware supply chain was profitable even as the model layer struggled.
- Value creation was unevenly distributed across the AI ecosystem.
Value Capture in AI Components
How has value capture shifted among AI components?
Initially, memory manufacturers were not making profits despite delivering significant value, while other components like KSM C were capturing less value.
- Value capture in the AI market is dynamic and can shift rapidly.
- Memory manufacturers faced challenges in profitability despite high theoretical value.
Market Dynamics and Value Tracking
Why is tracking value shifts in AI components important?
The shifting value capture is crucial for market participants, such as Jane Street, to understand and navigate the evolving landscape.
- Market participants need to stay informed about value shifts.
- Understanding value dynamics can provide competitive advantages.
Transcript
0:00 This always a fun question, right? Which is where does the value go in AI? AI is generating all this value. You've got the end user, which we I think we all agree is generating more value than anyone else, hence they're paying a lot for these models. But then you have, you know, the app layer. Well, so far the app layer has generated very little value. then you've got the model layer, which up until a year ago was generating negative gross margins and is now generating massive positive gross margins. But if we go back again a year ago, the hardware supply chain was generating all this gross margin while literally everyone else was losing money on. So ultimately, you had this like negative value being created on the model layer almost, if you will, because they were selling the tokens for less than it cost them on the infra side. And all the value is being created used at the chip, the fab. Initially in 2023, the memory guys were making no money. Even though theoretically, their value they were delivering was humongous. Now you've got Well, actually KSM C makes way less value than the memory guys. So so the the value capture shifted around a lot, which is very fun for people tracking the market or participating in the market like like Jane Street as an example.
Summary
- End users are generating the most value in the AI ecosystem and are willing to pay significantly for AI models.
- The app layer has not yet captured substantial value compared to other layers.
- The model layer transitioned from negative gross margins to positive margins within the past year.
- Previously, the hardware supply chain was the main source of gross margins while other layers struggled.
- In early 2023, memory manufacturers were unprofitable despite their significant contributions to value.
- The value capture landscape is dynamic, with shifts in profitability among different sectors, including chip manufacturers and memory producers.
- Market participants, like Jane Street, find these shifts interesting for tracking and investment purposes.
Questions Answered
Where does the value go in AI?
The value in AI is generated primarily by the end user, who pays significantly for the models. The app layer has generated little value, while the model layer has transitioned from negative to positive gross margins.
How has the model layer's value changed over time?
A year ago, the model layer was generating negative gross margins, but it has since shifted to generating substantial positive margins.
What role did the hardware supply chain play in value creation?
The hardware supply chain was generating gross margins while the model layer was losing money, indicating a misalignment in value creation.
How has value capture shifted among AI components?
Initially, memory manufacturers were not making profits despite delivering significant value, while other components like KSM C were capturing less value.
Why is tracking value shifts in AI components important?
The shifting value capture is crucial for market participants, such as Jane Street, to understand and navigate the evolving landscape.