Tsinghua-Founded Naive AI Hits $1.4B Valuation Before LLM Launch

PrismML, an AI lab, is developing a compact large language model intended to shift how AI is deployed and used. The article positions PrismML as an emerging player worth attention in the AI space, though specific technical details, capabilities, or business model are not provided in the source material.

NVIDIA's Vera Rubin NVL72 system achieved leading performance in its MLPerf Inference v6.1 debut, delivering up to 3.7x higher throughput than the GB300 NVL72 on Qwen3-VL and up to 2.5x on DeepSeek-R1. The results demonstrate the effectiveness of full-stack hardware and software codesign, including enhanced Tensor Cores, NVFP4 precision, and disaggregated serving techniques. A 288-GPU submission across four GB300 NVL72 racks achieved 99% scaling efficiency, and software optimizations alone delivered up to 1.6x performance gains from v6.0 to v6.1.

Researchers at Nature Machine Intelligence have demonstrated a dual-model architecture for autonomous crystal materials research using two lightweight large language models working collaboratively. The approach combines reasoning and scientific tool execution while maintaining computational efficiency and local deployability. The method achieves competitive performance without requiring expensive infrastructure, making advanced materials research more accessible.

Perplexity is deploying OpenAI's GPT-6 Astra model to handle end-to-end system operations, including writing communications, modifying software, and monitoring production infrastructure. The company reports significantly reduced oversight requirements compared to earlier models. This represents a shift toward autonomous AI management of critical business systems.