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How to choose the right AI platform

IBM watsonx

Watsonx is an enterprise-ready AI and data platform designed to multiply the impact of AI across your business.

发布日期: 2024年4月13日

To help you make the most from your data, an enterprise AI platform should combine the most important aspects of AI — predictive, classification and ML— for a holistic approach. The ideal solution is backed with four key elements.

We'll dive into each of these below ??

When it comes to selecting an AI model, it’s best to have a variety of sizes and architectures so you can pick what’s best suited to your needs. Your data and AI platform should provide the ability to build, train, validate tune and deploy AI using both curated open-source models and private foundation models that can bring in business domain context.

Before deploying a model, you need to ensure that it delivers reliable results and helps keep the data — and your intellectual property (IP) — secure. AI should be explainable, fair, robust and transparent. All models should offer transparency into the data’s origin, bias and governance. The solution should track data, curating methods and models, enabling AI that can be updated to meet evolving business and regulatory requirements.

Learn more about trustworthy AI below ??

Consumer AI isn’t the same as enterprise AI. Models should be highly curated to business domains and use cases that drive quick gains in productivity and time to value—such as augmenting and automating HR, customer service and code generation.

Learn how AI targeted for your use case can jumpstart business value ??

Your generative AI and ML platform should empower you to be an AI value creator, not just a user. You shouldn’t be limited to just prompting someone else’s AI model with no control over the model or the data. Regardless of if you’re a data scientist or a business user, the platform should allow you to build, train, tune and deploy, and govern the data and AI models you’re using.

Here's how generative AI is transforming various enterprise functions ??

Access our full ebook here ?? https://ibm.biz/BdmFwe .

Don P.

7 个月

Choose the one that had governance purpose buit into the foundation. Only WatsonX has had robust governance since it was released. The rest are just pretending. Seriously, ask the others to show their AI’s adherence to basic governance. They can’t. They tried to bake it in after the fact. Trying to corral the AI after the fact, you will never know the gaps and missteps that will bring litigation - for violating privacy, IP theft, data manipulation, etc. How trustworthy are other AI? Only as good as the accuracy and trust provided by real time reports on their training sources, bias, hallucinations, reporting on IP concerns, etc. If you cannot prove that your AI adheres to safety, privacy, ethical and security best practice frameworks. Then your AI is NOT trustworthy of my input or data. That should be THE first and primary concern for all companies wanting to use an AI.