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Today, we're introducing AC2, the Applied Compute Agent Cloud, to enable every team to train, serve, and improve their own frontier models.
206,702 просмотров • 1 месяц назад •via X (Twitter)
Комментарии: 33
AC2 turns post-training into a repeatable, engineered process. Use your own harness to train up to multi-trillion-parameter models with all the latest research techniques.
Ari, our research agent, monitors training, reads traces to find failure modes, analyzes results, and turns insights into better data, graders, and experiments.
When you have the right checkpoint, deploy it to production with AC2 inference: dedicated, low latency, and 99.9% uptime all while preserving the configuration used during training.
The most useful data comes from real user interactions, feedback, and traces. With self-distillation, your model can learn from production traces even when the original environment can’t be replayed.
Over the last six months, AC2 has powered our Applied AI team’s work for Microsoft, NVIDIA, Cognition, Harvey, DoorDash, and others. Now, we’re excited to empower every AI team with their own model factory. AC2 is available in private beta. Reach out to learn more.
Congrats @rhythmrg @ypatil125 @lindensli @michaelzchen5 and team! Looking forward to working as we post train our @rox_ai models.
congrats!
congrats @ypatil125 @lindensli @michaelzchen5 and team!!
Let's go!! @ypatil125 @lindensli Agastya and team!
congrats guys!
👑
Congrats team!
congrats on the launch!
🔥
congrats on the launch AC team!
congrats on the launch!
the team is cooooking 🧑🍳
Congrats @ypatil125 @lindensli and team, cooking 🔥
great work! can I get access?
Improvement loops need reversible deployment.
Congrats on the launch !!
Incredible launch, congrats @rhythmrg and team!
So exciting!! Let’s go!!
Wow
Congrats on the launch!
Awesome !! This gives companies more control over their models. Something awesome is happening ! We just need to combine it all...!!
What happens when the us government regulates frontier models and we are only allowed to use claude
insane
most teams lack enough clean data for frontier training, how does ac2 prevent garbage feedback loops
It’s like Tinker
"Enable every team to train frontier models" is the pitch every MLOps startup makes right before the pricing page shows you still need a stack of H100s and an RL infra team to use it. What's actually managed here — the training loop, or just the serving layer around someone else's weights?
congrats @ypatil125 and team!
The trace-to-checkpoint loop is the real product: research agents find failure modes, graders turn them into evidence, and deployment preserves the tested configuration. Account and session state belong in that trace too:
