Models & Labs
OpenAI Releases ChatGPT Images 2.5 and Navier-Stokes Solution
Matt Wolfehigh confidence
Why it matters
- →Improves practical image generation quality for users
- →Represents a major theoretical breakthrough in fluid dynamics and mathematics
- →Raises questions about model interpretability and emergent behaviors
OpenAI has released ChatGPT Images 2.5, an upgrade to its image generation capabilities within the ChatGPT interface. In a separate scientific announcement, OpenAI revealed it has found a solution to the Navier-Stokes existence and smoothness problem, one of the Millennium Prize Problems in mathematics. The company also described its internal model as having an 'alien mind,' suggesting significant shifts in how the model processes information.
Read originalMore from Matt Wolfe
More in Models & Labs
Models & Labscoding
llama.cpp b10996 adds CUDA 13 and ROCm 10.0 builds
This release quietly closes the hardware gap for local inference by adding native support for CUDA 13 and ROCm 10.0 across Linux and Windows. NVIDIA users can now leverage newer driver stacks without waiting for upstream updates, while AMD GPU owners finally get first-class ROCm 10 binaries that match the maturity of their CUDA counterparts. Apple Silicon builds remain available but KleidiAI is explicitly disabled here, suggesting a focus on stability over new kernel optimizations for this specific iteration. The inclusion of openEuler support for Huawei's Ascend chips further broadens the ecosystem beyond standard x86 and ARM consumer hardware.
llama.cpp Releases
Models & Labsmodels
Llama.cpp b10981 release enhances OpenVINO support
The latest b10981 release of llama.cpp brings significant improvements to OpenVINO integration, particularly in optimizing stateful decode and GPU MoE inference. By addressing issues like stateful decode errors and enhancing the handling of sliding-window layers, this update ensures more reliable and efficient model performance. The release also introduces new features such as the GGML_OPENVINO_REQUANT_KQUANT for 4-bit requantization and improved handling of multi-head models. These changes make llama.cpp more robust and versatile, especially for developers working with complex AI models on diverse hardware setups.