Maximizing Business Value with Diverse AI Models
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In this riveting episode by IBM Technology, the team delves into the thrilling world of AI models, urging businesses to embrace innovation and flexibility. They introduce traditional AI, powered by machine learning and deep learning, alongside the formidable large language models (LLMs) that are revolutionizing the game. By advocating for the strategic use of multiple AI models, they unlock a treasure trove of data potential that can propel businesses to new heights.
Traditional AI, with its structured data analysis and rule-based predictions, emerges as the trusty steed of the AI realm, boasting attributes like compact size, low latency, and energy efficiency. On the flip side, the large language models, particularly encoder models, step into the spotlight with their prowess in handling structured data and delivering enhanced accuracy, albeit with a trade-off in power consumption and latency. Decoder models, the mavericks of the AI world, shine bright as they craft new data from unstructured sources, showcasing the boundless creativity AI can offer.
By dissecting the unique strengths of each AI model, businesses are encouraged to tailor their approach dynamically, harnessing the power of different models based on specific needs. The channel illustrates this strategy through captivating examples in fraud analysis and insurance claim assessment, demonstrating how a hybrid model approach can strike the perfect balance between precision and efficiency. As the episode draws to a close, the team underscores the transformative potential of multi-model AI environments in driving accurate predictions and unlocking unparalleled value for businesses daring enough to embrace the AI revolution.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
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