Multimodal systems can also amplify biases inherent in each data type. Visual datasets, such as those used in computer vision, may not equally represent all demographic groups.

Ultimately, multimodal AI is more than just a technological breakthrough—it’s a powerful tool that can make healthcare more personal, effective and humane.

Multimodal analysis and synthesis encompasses the integration, processing and generation of information from diverse data channels – such as text, images, audio and video – within a unified ...

Cesare Rollo, from the University of Torino in Italy, and colleagues introduced a multimodal computational framework for patients' stratification and prognosis prediction (VAE-Surv). VAE-Surv ...

Businesses and developers can pick from a whole catalog of multimodal models — or get help mixing and matching from the 1,800 options in the Azure AI Foundry — to create more intelligent and ...

Multimodal search is nothing new, as OpenAI and Google offer the same on their respective chatbots. OpenAI launched its latest generation of embeddings models in January.

SAN FRANCISCO, June 24 (Reuters) - Artificial intelligence data infrastructure company LanceDB raised a $30 million series A round, the company said Tuesday. The round was led by Theory Ventures ...

Phi-4-multimodal is a 5.6 billion parameter model that uses the mixture-of-LoRAs technique to process speech, vision, and language simultaneously. LoRAs or Low-Rank Adaptations, is a way of ...