Apple’s Core AI framework is positioned as a developer stack for deploying AI models directly inside apps on Apple silicon. The documentation describes Swift APIs, `.aimodel` assets, model specialization, caching, Xcode profiling, and debugging tools. It appears aimed at developers building low-latency, privacy-conscious on-device inference workflows, though the documentation is marked as preliminary beta information.
Microsoft and open-source AI community leader Hugging Face have announced a further expansion of their strategic partnership. At the heart of this…
In this case study, Prezi — the well-known company behind the non-linear presentation software of the same name — shares how it is embracing the "multimodal…
During Microsoft Build 2024, Hugging Face announced a further strategic collaboration with Microsoft, aimed at providing developers with a more seamless…
This case study takes an in-depth look at how Writer, an enterprise-grade generative AI platform, leverages the Hugging Face open-source ecosystem and…
Hugging Face and AWS have jointly announced the new "Hugging Face LLM Inference Container" — a brand-new deep learning container (DLC) purpose-built for Amazon…
Hugging Face has announced an important partnership with Microsoft, officially launching the "Hugging Face Model Catalog" on the Azure Machine Learning (Azure…
In May 2021, Gradio officially released version 2.0 and announced a deep integration with the Hugging Face platform. This collaboration fundamentally changed…
When deploying Transformer models in production environments, latency and throughput are often the deciding factors for a project's success. Hugging Face…