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Inference Engine

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  1. DigitalOcean Previews AI Agent Learning and Data Services

    DigitalOcean introduced previews of Learning Services and Agent Data Services for building, evaluating, and improving AI agents on its cloud platform, according to a single news report. Learning Services, built on Inference Engine and Managed Agents, includes Insights for recording agent activity, Signals for identifying failures and performance weaknesses, and Simulations for testing potential improvements before deployment. The report says Insights, Signals, and Evaluations, including Simulations, are available in public preview, while Inference Router optimization and Agent Data Services are in private preview. Although the report opens by describing both new services as public previews, its later availability statement identifies Agent Data Services as private preview. Agent Data Services is described as a managed foundation that indexes and governs access to documents, video, audio, logs, and agent conversations.

    InfoQ 中文 AI&大模型 · 🔥 0

Experience and discussion from the community

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uzu: A high-performance inference engine for AI models.

What problem it solves Developers need to run AI models inside applications while handling model downloads, inference configuration, and chat sessions. The project presents local inference with data privacy and no inference costs as its deployment model. Key features High-level application API — The engine exposes a simple API for creating an engine, loading a model, opening a chat session, and re…

github.comhttps://github.com/trymirai/uzu

LocalAI: An open-source AI engine for running models locally across modalities and hardware.

What problem it solves Running AI models locally can require integrating multiple inference engines, model formats, hardware accelerators, and API surfaces. LocalAI addresses this with a small core, on-demand backends, and compatible APIs that work across supported hardware without requiring a GPU. Key features Composable inference backends — Backends are packaged separately and pulled only when a…

github.comhttps://github.com/mudler/LocalAI

kimi-k3-in-c: Kimi K3 inference in portable C99, with no BLAS, framework, or GPU required.

What problem it solves Running the Kimi K3 model normally presents a storage and memory barrier because its checkpoint is very large. This project provides a portable C99 inference engine that streams model data so the complete model can run on a CPU without requiring GPU infrastructure or a deep-learning framework. Key features Portable C99 inference — The engine is implemented in portable C99 an…

github.comhttps://github.com/FareedKhan-dev/kimi-k3-in-c