LLaVA Vision
Multimodal AI: a glimpse into the future
LLaVA:
Large Language and Vision Assistant
A Glimpse into the Future of Multimodal AI Models
In the rapidly accelerating realm of artificial intelligence, the next frontier is undoubtedly the development of multimodal models. These models, unlike traditional large language models, are capable of processing more than just text inputs. They can handle images, videos, audio, and most any other types of data. One such model that has recently stirred up the AI community is LLaVA, which stands for Large Language and Vision Assistant.
What is a Multimodal AI Model?
Multimodal models are designed to understand and reason across multiple forms of information. Try taking a photo of your refrigerator's contents and ask the model to suggest recipes based on the ingredients visible in the image. These models create joint embeddings, which are shared representations that capture information from text, images, videos, and audios. This shared representation allows the model to solve problems and reason across different types of data.
LLaVA in Action:
LLaVA, integrated with Llama2, is a multimodal model that can handle tasks across both text and images. A few demonstrations of its capabilities include:
Identifying objects and scenarios in photos. For example, when presented with an image of a golden retriever lying on grass under sunlight, LLaVA could deduce that the weather was sunny.
Recognizing famous personalities in images. In one instance, it correctly identified Elon Musk from a photo.
Generating stories based on complex images. When given a four-panel dramatic scene, LLaVA was able to craft a story that captured the essence of the image, understanding the facial expressions and the sequence of events.
Real-World Applications
Product Development: LLaVA can turn sketches into functional HTML websites. This capability can be a game-changer for designers and product managers during the early stages of ideation.
Content Curation: LLaVA can be used to curate and classify content. It can rate images based on their violence score, making it a likely tool for content moderation on social media platforms.
Medical Diagnostics: By analyzing images, LLaVA can provide basic diagnoses. For instance, when presented with an image of a foot, it suggested the possibility of a fungal infection.
CAPTCHA Verification: With the rise of advanced AI models, traditional CAPTCHA systems might become obsolete. LLaVA's ability to extract text from images suggests that new verification methods might be needed in the future. How do we verify you are Human?
Robotics: Google's research paper on Palm showcased the integration of a multimodal model with a robot. The robot, when given a prompt, could generate a plan based on visual and text inputs and execute complex tasks.
Recursive Analysis:
LLaVA gives us hints of the exciting possibilities that multimodal models bring to the increasingly digitalized human experience. From understanding images to crafting stories and assisting in product development, the applications are vast and expansive. As AI continues to evolve, models like LLaVA will undoubtedly play ever greater roles in shaping our future technology and human amplification systems.
Call to Action:
If you're interested in exploring LLaVA further, you can try it out through the demo website or install it on your local machine via its GitHub link. The world is not ready for multimodal AI, and this is just the beginning! LLaVA is a promising glimpse into what capabilities are coming down the pipeline.