{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"Building Multimodal Generative AI Systems: Architecture, Refinement, and Enhancement","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/c715aafb\"></iframe>","width":"100%","height":180,"duration":254,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/building-multimodal-generative-ai-systems-architecture-refinement-and-enhancement.\nGenerative AI systems are built in blocks, each performing a distinct function and interacting with other blocks to achieve a larger goal.\nCheck more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n            You can also check exclusive content about #generative-ai, #ai, #ai-agent, #multimodal-models, #ai-architecture, #ai-enhancement, #data-augmentation, #ai-integrations,  and more.\nThis story was written by: @tona. Learn more about this writer by checking @tona's about page,\n            and for more stories, please visit hackernoon.com.\nGenerative AI systems are built in blocks, each performing a distinct function and interacting with other blocks to achieve a larger goal. The rise of Generative Multimodal Models brings up a new perspective of thinking of AI as a system rather than Large Language Models (LLMs) alone.\n        \n        ","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}