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#webnn

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Last April, @dontcallmeDOM stressed the need for the web community to address #AI's growing impact on the Web. Previous @w3c report highlighted challenges like synthetic content, bias, #security, #sustainability, and data consent.
▶️ w3.org/reports/ai-web-impact/

Progress has been made with ML-based #APIs such as #WebNN and Prompt API. New concerns include AI agents, which pose risks to trust, #privacy, #safety, and the web economy.

🎬 Watch "AI Impact on the Web: updates": youtu.be/dniPpsCRQgI

During the WebEvolve 2024 conference in #Shanghai 🇨🇳, Ningxin Hu (Intel) explained how #WebNN provides a unified abstraction of #neural networks for the web, and enables access to #AI hardware acceleration via native OS #ML APIs. This approach delivers near-native performance and supports next-generation use cases.

Check slides and event report:
▶️ w3.org/2024/01/webevolve-serie
▶️ w3.org/2024/01/webevolve-serie #W3CChina

... and watch the 🎬 ! youtu.be/juTRGIIEx_8

Continued thread

W3C has active ongoing work on making #browsers better platforms to run #MachineLearning models through its #WebNN #API, incl. recent work in adding support for Transformers, a key component to #GenerativeAI models.

But the intersection between Web and #AI spans a much broader set of questions: ethical impact of relying on #AI and #MachineLearning models ; impact on content creation, on user interactions, on content re-use, and the risk of creating new centralization bottlenecks