model-training

Mistral AI has launched Forge, a platform that allows enterprises to train custom AI models on their proprietary data including codebases, compliance policies, and operational documentation. The system supports both dense and mixture-of-experts architectures with pre-training, post-training, and reinforcement learning capabilities.

AWS has published a technical guide on hyperparameter optimization for Amazon Nova Forge, its platform for building custom frontier models from Amazon Nova checkpoints. The guide addresses three core challenges: catastrophic forgetting during domain specialization, learning rate calibration when mixing proprietary and curated training data, and baseline performance constraints for reinforcement fine-tuning.

Cursor acknowledged that its newly launched Composer 2 coding model was built on Moonshot AI's open-source Kimi 2.5 model, not developed independently. The admission came after user scrutiny revealed code references to Kimi. Cursor claims only 25% of compute came from the base model, with 75% from its own training and reinforcement learning.

Meta has signed a multi-billion dollar deal to rent Google's TPU (Tensor Processing Unit) chips for training its AI models, marking a significant shift away from Nvidia's dominance in AI infrastructure. The arrangement provides Meta with alternative compute capacity while signaling growing competition in the specialized AI chip market.