Browsing: Multimodal

Mistral AI has released Mistral Small 4, a new model in the Mistral Small family designed to consolidate several previously separate capabilities into a single deployment…

Why Document OCR Still Remains a Hard Engineering Problem? What does it take to make OCR useful for real documents instead of clean demo images? And…

Google expanded its Gemini model family with the release of Gemini Embedding 2. This second-generation model succeeds the text-only gemini-embedding-001 and is designed specifically to address…

Microsoft has released Phi-4-reasoning-vision-15B, a 15 billion parameter open-weight multimodal reasoning model designed for image and text tasks that require both perception and selective reasoning. It…

How can a trillion-parameter Large Language Model achieve state-of-the-art enterprise performance while simultaneously cutting its total parameter count by 33.3% and boosting pre-training efficiency by 49%?…

NVIDIA has just released Dynamo v0.9.0. This is the most significant infrastructure upgrade for the distributed inference framework to date. This update simplifies how large-scale models…

Google Research is proposing a new way to build accessible software with Natively Adaptive Interfaces (NAI), an agentic framework where a multimodal AI agent becomes the…

section(“6) pack unpack”) B, Cemb = 2, 128 class_token = torch.randn(B, 1, Cemb, device=device) image_tokens = torch.randn(B, 196, Cemb, device=device) text_tokens = torch.randn(B, 32, Cemb, device=device)…

Optimizing Multimodal Agents Multimodal AI agents, those that can process text and images (or other media), are rapidly entering real-world domains like autonomous driving, healthcare, and…

A team of Stanford Medicine researchers have introduced SleepFM Clinical, a multimodal sleep foundation model that learns from clinical polysomnography and predicts long term disease risk…