Models & Labs
Anthropic launches Claude Cowork on mobile and web
The Verge AIhigh confidence
Why it matters
- →Expanding to mobile and web increases accessibility for users.
- →Cloud-based sessions enhance task continuity across devices.
- →The move signifies a shift towards more flexible AI task management.
Anthropic has launched its Claude Cowork AI platform on mobile and web, expanding beyond its previous desktop-only availability. The platform now supports cloud-based sessions, allowing tasks to continue even when devices are offline. Users can access Cowork on iOS and Android, though the full experience remains on the desktop app. This expansion aims to provide more flexibility and accessibility for users managing AI tasks across different devices.
Read originalMore from The Verge AI
More in Models & Labs
Models & Labsmodels
llama.cpp b10955 release addresses heap corruption
The latest release of llama.cpp, b10955, tackles a critical issue of heap corruption by disabling the ggml-cpu precompiled header and fixing CACHE_LINE_SIZE ambiguity. This update ensures consistent CACHE_LINE_SIZE values across C++ kernels and C work-buffer sizing code, preventing heap-buffer-overflow and subsequent crashes. By restoring the natural include order and removing the std::hardware_destructive_interference_size branch, the update makes the value deterministic and include-order independent. This release is a technical fix that stabilizes the runtime environment for developers using llama.cpp.
llama.cpp Releases
Models & Labsmodels
llama.cpp b10956 release enhances SYCL backend
The latest llama.cpp release, b10956, introduces significant improvements to the SYCL backend, particularly for handling large k values in TOP_K operations. By implementing a radix select method, the update allows for efficient GPU-resident processing, avoiding previous limitations that forced operations to fall back to the CPU. This change enhances performance, especially in scenarios requiring large k values, such as qwen4exp's sparse-attention indexer. The update ensures that operations are more efficient and scalable, providing a notable boost in processing speed without regressing any measured shapes.
