Until recently, I was personally using ChatGPT / Claude to most summrise and proofread docs, memos, sops. Since last one week, I've been using to redesign the website and app of draftly.so. I left coding a few years ago and I was impressed with the results. Something that would take me weeks was done in a couple of hours. What I learned is that you should treat AI like a child. Give smaller tasks and when it makes mistakes and you already know the solution, fix it yourself. Would love to know how your use AI in your daily life.

Imagine AI agents transforming business intelligence by providing real-time insights, automating data analysis, and uncovering hidden trends. I'd love to hear your thoughts on how these AI agents can help businesses stay ahead of the curve, driving unparalleled efficiency, innovation, and growth.

Looking to understand the differences between AWS's machine learning offerings? I've written a comprehensive comparison between AWS SageMaker and Amazon ML. This article explores: SageMaker's end-to-end ML capabilities vs. Amazon ML's historical approach Detailed analysis of SageMaker's features including Studio, Autopilot, and Ground Truth Implementation best practices and cost optimization strategies Practical recommendations for teams starting with machine learning on AWS Whether you're a data scientist, developer, or decision-maker, this comparison will help you understand AWS's machine learning evolution and make informed decisions about using SageMaker for your ML projects. Here is the article link - https://medium.com/@smith.emily2... Join the discussion and share your experiences with these platforms!

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AI is reshaping industries and roles. What changes do you foresee in the workforce as AI adoption grows?