philip lelyveld The world of entertainment technology

MULTI-MODAL AI IS THE NEW FRONTIER IN PROCESSING BIG DATA

Multi-modal AI is a new AI paradigm, in which various data types like image, text, speech and numerical data are combined with multiple intelligence processing algorithms to achieve higher performances. Multi-modal AI often outperforms single-modal AI in many real-world problems. ...

Multi-modal systems, with access to both sensory and linguistic modes of intelligence, process information the way humans do. ...

Multi-modal learning pieces together disjointed data into a single model. Since multiple sensors are used to observe the same data, multi-modal learning offers more dynamic predictions compared to a unimodal system processing more datasets translates to more intelligent insights. The ability to process multi-modal dataconcurrently is vital for advancements in AI. ...

DALL.E: It is an AI program developed by OpenAI that creates digital images from textual descriptions.

FLAVA: It is a multimodal model trained by Meta over images and 35 different languages.

NUWA: This model is trained on images, videos, and text, and given a text prompt or sketch, it can predict the next video frame and fill in incomplete images.

MURAL: It is a digital workspace for visual collaboration and helps everyone on the team imagine together to unlock new ideas, and solve hard problems.

ALIGN: It is an AI model trained by Google over a noisy dataset of a large number of image-text pairs.

CLIP: It is a multimodal AI system developed by OpenAI to successfully perform a wide set of visual recognition tasks.

Florence: It is released by Microsoft research and is capable of modeling space, time, and modality.

See the full story here: https://www.analyticsinsight.net/multi-modal-ai-is-the-new-frontier-in-processing-big-data/