Google DeepMind has made advancements in scaling test-time compute for diffusion models, a development that could enhance AI image generation capabilities. This new approach addresses biases in verifiers and explores the mixing of different verifiers, marking a significant step in the evolution of AI models. The paper detailing this work has garnered attention for its innovative methods, which could lead to improvements in models like DALL-E and Stable Diffusion. Additionally, Grok 3 is anticipated to become a leading AI model soon, with expectations of 20 times the computing power for training on a 100,000 H100 cluster. The competition between Grok 3 and OpenAI's O3-mini is expected to intensify next month. Meanwhile, anticipation builds for the release of Claude 4, with reports suggesting it may be testing at a scale 1,000 times larger than expected, prompting the need for new datacenters for training.