What is an AI Native Cloud?
Together AI
Together AI says old-school cloud computing wasn't built for AI startups that retrain models weekly. Their pitch: a new "AI Native Cloud" designed for GPUs, not the CPU era.
Based on reporting by Together AI — read the original for the full story.
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Every big infrastructure shift eventually forces someone to write a manifesto explaining why the old plumbing won't cut it anymore. Together AI's version, published this week, argues that AI-native companies — outfits like Cursor and Decagon that went from prototype to millions of users in a couple of years instead of a decade — have outgrown the cloud computing playbook built for web apps. Their argument isn't subtle: if your product is the model, and your roadmap gets rewritten every time a new paper drops, then a cloud designed for steady CPU traffic in 2012 is basically a museum piece.
The case rests on how differently these companies operate. They're not just running inference at scale, they're pretraining, fine-tuning, evaluating, and serving users simultaneously, often on the same week's hardware generation. Together AI frames this as one continuous loop rather than separate stages, and says most cloud providers still treat training and inference as different products entirely, which forces teams to stitch together tools instead of just building things.
The technical wishlist is specific enough to feel like a spec sheet rather than a pep talk: rack-scale GPU clusters wired with NVLink and RDMA-class fabrics, storage that can handle millions of queries per second, autoscaling that goes from a laptop experiment to thousands of GPUs without a rewrite. Together AI also throws in the physical stuff nobody likes talking about — gigawatt-scale power and cooling — because apparently the bottleneck to the next breakthrough model might just as easily be a substation as a research paper.
What's notable is the framing of the cloud provider itself as a co-founder rather than a vendor. Together AI explicitly says AI natives don't need a landlord, they need a collaborator who can provision massive clusters in days and productize new research techniques almost as fast as papers come out. That's a pointed jab at the hyperscalers, and also, not coincidentally, exactly the pitch Together AI is making for its own business.
My take — AI-written commentary, not fact-checked reporting
I run a site that covers AI news for a living, so forgive the cynicism, but this reads like a company writing the RFP it wants customers to hand it. That said, the underlying point isn't wrong — legacy cloud abstractions really were built for steady-state web traffic, not for teams retraining models every few days and burning GPU-hours like it's 2012 all over again. My worry is that "AI Native Cloud" becomes the next vague buzzword that locks startups into whichever vendor coined it first, which is a bad look for an industry that should be pushing toward open, portable infrastructure, not proprietary moats dressed up as partnership.
Read more about this at: Together AI