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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.

Applied Compute

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206,702 görüntüleme • 1 ay önce •via X (Twitter)

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Applied Compute profil fotoğrafı

Applied Compute1 ay önce

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.

Applied Compute profil fotoğrafı

Applied Compute1 ay önce

Ari, our research agent, monitors training, reads traces to find failure modes, analyzes results, and turns insights into better data, graders, and experiments.

Applied Compute profil fotoğrafı

Applied Compute1 ay önce

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.

Applied Compute profil fotoğrafı

Applied Compute1 ay önce

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.

Applied Compute profil fotoğrafı

Applied Compute1 ay önce

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.

Ishan Mukherjee profil fotoğrafı

Ishan Mukherjee1 ay önce

Congrats @rhythmrg @ypatil125 @lindensli @michaelzchen5 and team! Looking forward to working as we post train our @rox_ai models.

John Schulman profil fotoğrafı

John Schulman1 ay önce

congrats!

vincent sunn chen profil fotoğrafı

vincent sunn chen1 ay önce

congrats @ypatil125 @lindensli @michaelzchen5 and team!!

Apoorv Agrawal profil fotoğrafı

Apoorv Agrawal1 ay önce

Let's go!! @ypatil125 @lindensli Agastya and team!

Dan Biderman profil fotoğrafı

Dan Biderman1 ay önce

congrats guys!

Jonathan Jacobi profil fotoğrafı

Jonathan Jacobi1 ay önce

👑

Francesca LaBianca profil fotoğrafı

Francesca LaBianca1 ay önce

Congrats team!

andrew profil fotoğrafı

andrew1 ay önce

congrats on the launch!

Jared Rosner profil fotoğrafı

Jared Rosner1 ay önce

🔥

kevin profil fotoğrafı

kevin1 ay önce

congrats on the launch AC team!

Maanav Khaitan profil fotoğrafı

Maanav Khaitan1 ay önce

congrats on the launch!

Lina T profil fotoğrafı

Lina T1 ay önce

the team is cooooking 🧑‍🍳

Zongheng Yang profil fotoğrafı

Zongheng Yang1 ay önce

Congrats @ypatil125 @lindensli and team, cooking 🔥

Ramin profil fotoğrafı

Ramin1 ay önce

great work! can I get access?

Neeraj Kumar profil fotoğrafı

Neeraj Kumar1 ay önce

Improvement loops need reversible deployment.

Shriram Sridharan profil fotoğrafı

Shriram Sridharan1 ay önce

Congrats on the launch !!

Praneet profil fotoğrafı

Praneet1 ay önce

Incredible launch, congrats @rhythmrg and team!

angela zhang profil fotoğrafı

angela zhang1 ay önce

So exciting!! Let’s go!!

Omeed Tavakoli profil fotoğrafı

Omeed Tavakoli1 ay önce

Wow

Ishan Gupta profil fotoğrafı

Ishan Gupta1 ay önce

Congrats on the launch!

Alex profil fotoğrafı

Alex1 ay önce

Awesome !! This gives companies more control over their models. Something awesome is happening ! We just need to combine it all...!!

angel hernandez profil fotoğrafı

angel hernandez1 ay önce

What happens when the us government regulates frontier models and we are only allowed to use claude

Sebastian Tan profil fotoğrafı

Sebastian Tan1 ay önce

insane

Sebastian Buzdugan profil fotoğrafı

Sebastian Buzdugan1 ay önce

most teams lack enough clean data for frontier training, how does ac2 prevent garbage feedback loops

jian profil fotoğrafı

jian1 ay önce

It’s like Tinker

Rompel profil fotoğrafı

Rompel1 ay önce

"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?

Robby Manihani profil fotoğrafı

Robby Manihani1 ay önce

congrats @ypatil125 and team!

刘朝 Zhao Liu profil fotoğrafı

刘朝 Zhao Liu1 ay önce

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:

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