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Why foundation models are a paradigm shift for AI

There’s traditional AI and then there’s generative AI. One word separates them, but the difference couldn’t be more massive. While traditional AI can analyze data and tell you what it sees, generative AI can use that same data to create something new.

In this episode of AI Academy, learn about a new class of flexible, reusable AI models that can unlock new revenue, reduce costs, and increase productivity, then use our guidebook to dive deeper.

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Watch (8:29)
What you’ll learn
  • Importance of foundation models to generative AI
  • Benefits of flexible AI models
  • How to select the right AI and data platform for your business
You should look for a platform that has proven expertise in foundation models, the governance tools in place to help you address potential ethical concerns, and can help you transition from experimentation to deployment. Kate Soule Senior Manager Business Strategy IBM Research and MIT-IBM AI Lab
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Track 2 Choose the right AI model for your use case Bigger isn’t always better when it comes to AI models. Learn how to find the right fit for your business needs. Then get the guidebook to help you take action. Go to episode page
Track 2 Is data management the secret to generative AI? Every conversation starts with generative AI, but ends with data. Why? Because there is no AI without data. Generative AI is changing the way we think about data.  Go to episode page
Track 2 Trust, transparency and governance in AI Explore issues like AI hallucination, bias and risk, and learn how applying AI ethics and governance builds trust. Then put theory into practice with our guidebook. Go to episode page
Track 1: Strategic essentials
Track 3: Putting AI to work
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