1/ $AMD is an asymmetric opportunity everybody sleeps on. Data...

$META latest model now runs 100% on $AMD chips for live traffic.
They report significant cost efficiencies and minimal switching costs:
Its partnership with $META is just a beginning.
Lisa Su believes that inference will be a much bigger market than training:
In monolithic design, cores that require advanced manufacturing are put on the same die as I/O interfaces and memory controllers that require less advanced processes.
In chiplet, cores and memory controllers are put on different dies that are then connected with high-speed interconnects.
That allows us to use less advanced processes for I/O interfaces and memory controllers than cores.
Result? Cheaper chips with higher yields.
For instance, AMD MI300X chips come with 192GB H3 memory against 142GB of Nvidia H200 chips.
Higher memory capacity allows cheaper and more efficient inference workloads, positioning $AMD as the top choice for cost sensitive operators.
Nvidia's market share in data center GPUs declined from 98% in 2023 to 94% in 2024.
Hyperscalers are looking for alternatives.
Nvidia will likely remain as the leader by a margin in this market but also $AMD doesn't need to fully catch up.
Even if it can expand its market share to 10%, it'll generate more than $30 billion from this segment alone.
Based on the current market developments, analysts expect $4.6 and $6.1 EPS for this year and 2026 respectively.
This means that it's currently trading at 16 times 2026 earnings and the market is pricing zero growth beyond that.
This is a ridiculous valuation.
Even if we assume just 15% annual EPS growth between beyond 2026, we will get $10 EPS in 2030.
Attach a conservative 25 PE and we have $250 stock.
I share all my insights in my weekly newsletter.
Join 12,000+ readers to become a better investor.
You will also get a free e-book when you join 👇
capitalist-letters.com







