Locator: 50294TRAINIUM.
Chips are followed here.
Trainium -- AWS.
Again, things are moving very quickly. Wow!
Yes, "everyone" might say this is all about competition among the various semiconductors.
It may be. To some extent.
In fact, LDCs are going to be scrambling for chips from wherever they find them. But as chips become more available, buyers will select based on personal need or based on their particular business model.
Has it come down to this? Nvidia, AMD, and AWS? I don't know. Let's ask a chatbot. From chatbot:
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The Answer From ChatGPT
The answer: no!
It's even more interesting that that.
The AI chip market is splitting into two tiers:
- global-scale platforms; and,
- serious challengers with asymmetric advantages.
So, is it now AWS vs Nvidia vs AMD?
Nvidia
- still the center of gravity
- CUDA ecosystem = massive moat
- dominates training (still)
- deep ties across all clouds
- even with Trainium, Nvidia is the devault global standard.
AWS
- the most dangerous new entrant
- vertical integration (chips + cloud + customers)
- now anchored by
- OpenAI workloads
- Anthropic alignment
- AWS isn't just competing in chips, it's redefining the stack.
AMD
- the "second source" at scale
- it has a big OpenAI commitment (multi-GW)
- strong hyperscaler relationships
- open ecosystem vs CUDA lock-in
- the only credible horizontal challenger to Nvidia
But here's what I was missing (and it's crucial):
- there are two more players at this level that cannot be left out.
Google (TPUs)
- quietly one of the most powerful players
- TPUs already at one million-chip scale deployments
- deep integration with Anthropic
- fully vertically integrated stack
- chip --> software --> model --> cloud
- Google may be the most complete AI stack in existence.
MSFT (custom silicon + Azure)
- less visible but critical
- custom AI chips (Maia, Cobalt)
- still deeply tied to Nvidia
- massive Azure footprint
- MSFT's strength: control of enterprise + distribution layer
SO, the real "Big 5":
- Nvidia
- AWS
- AMD
- MSFT
Then, there's the second tier -- don't ignore these
- emerging challengers
- Cerebras Systems (wafer-scale chips)
- Groq (ultra-fast inference)
- Tenstorrent
- these are: "if the paradigm shifts, they win" players.
The real shift -- this is the key insight --
the industry is moving from --
- OLD WORLD --
- chips = independent market
- Nvidia sells to everyone
- NEW WORLD --
- chips are strategic weapons inside platforms
What make Trainium different?
- it's not just a chip -- it's a business model shift
- bundled with AWS
- priced to undercut Nvidia
- locked to Amazon ecosystem
Think: Tranium = "private-label AI compute."
AI chips are no longer a semiconductor market -- they're the foundation of competing digital nations:
- Nvidia: think Switzerland (neutral supplier)
- AWS / Google / MSFT: empires
- AMD - balancing force (would this be South Korea, China)?
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What About Apple?
AI prompt:
Except for mentioning Apple at the very, very beginning, Apple was not mentioned again. In the long reply above, one could also divide the chip market into two tiers (personal -- EDGE -- use) vs cloud. Apple has its own EDGE and Cloud and has its own Silicon design -- where is Apple using Trainium? In its iCloud?
I asked the question, got the reply. If readers are interested they can ask the same question on the chatbot they prefer.
