Researchers introduce POET-X, a memory-efficient variant of the Reparameterized Orthogonal Equivalence Training framework that reduces computational overhead in LLM training. The method enables pretraining of billion-parameter models on a single Nvidia H100 GPU, where standard optimizers like AdamW exhaust memory.
Nvidia announced Monday it is investing $2 billion each into photonics companies Lumentum and Coherent to develop optical transceivers, circuit switches, and lasers for next-generation AI data centers. The technology aims to improve energy efficiency, data transfer speeds, and bandwidth in data center infrastructure.
Nvidia is reportedly planning a $30 billion investment in OpenAI, according to Reuters citing sources familiar with the matter. The deal would represent one of the largest funding commitments in the AI sector to date. Terms and timeline have not been officially confirmed by either company.
No models tracked yet.