91 summarised stories about Multimodal AI, each linking back to the original source. Browse all topics →
SiliconANGLE 2 months ago 27
Echovane Inc. closed a $1 million pre-seed round to speed up development of its AI-native, end-to-end market research platform. The funding round totals $1,000,000, co-led by Titan Capital and Neon Fund, to build out its AI agent infrastructure. Echovane will expand multimodal capabilities and its global participant network so studies can be executed faster while preserving research quality.
MarkTechPost 2 months ago 48
ByteDance’s Seed team released SeedRealtime, a native audio-visual full-duplex LLM that processes audio, video, and text in one end-to-end model and supports real-time continuous interaction. It is partially deployable because it is live inside the Doubao app, while ByteDance has provided no technical report, parameter count, or open weights. As a result, external teams can’t integrate the model yet, but Seed is offering a reference architecture shift away from cascaded ASR/VLM/TTS pipelines and external turn-taking components.
Hugging Face 2 months ago 36 ● 4 sources
Meta released Muse Glimmer, a multimodal 30B open-source model aimed at local agentic use cases like coding and document analysis. It was distilled from Muse to a 30B parameter model and released today under the Apache 2.0 license. Meta also shipped day-0 support in Transformers and llama.cpp (plus vLLM and Inference Endpoints), so developers can load and run it locally with standard tooling.
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TLDRocket
17 October 2026
The big thread today is the messy middle between agent ambitions and the boring parts that make them safe and auditable. ServiceNow is positioning its AI Control Tower as the enterprise hub to discover, govern, and—crucially—control AI agents across models and clouds, while a field study of 15 large-enterprise customers (conducted September 15–21, 2026) presses on a key question: how strong is “technical runtime enforcement” and lifecycle evidence compared with other tools? ServiceNow’s answer is mostly commercial muscle—aiming for $1.5B in full-year AI ACV—but its guidance effectively says buyers should treat Control Tower as strongest for governance workflows and operational action, then verify where model validation evidence and real-time blocking are actually handled.
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