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The next wave of AI value won’t come from technology alone. It comes from identifying the right use cases, bringing the right expertise to the table, and building strong partnerships to turn ideas into impact. 🎥 Hear Daniela’s perspective on where organizations should focus their AI efforts, and why...

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Strategy

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Larry Ellison basically explained why OpenAI is positioned to win the AI race. Today’s models all trained on the same thing: public data. The internet. Books. Papers. General knowledge. Impressive, but capped. Ellison’s point: peak value only comes when AI is trained on private data. That’s where OpenAI is moving: • partnerships with universities to work with unpublished research • experts teaching models real job tasks, not just theory • deep access to how science, medicine, law, and finance actually work Public data makes AI smart. Private data makes it decisive. The next AI leap won’t come from reading more of the internet. It’ll come from being invited behind the curtain. That’s the real moat.

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"The unsolved problem of how do you turn data into something that is valuable within your business is now playing out." Aaron Levie spoke at Axios' AI+ Summit about the relationship between agents, data and business value.

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AI runs on electricity, and Sweden has a head start. This morning at Ruinen we put the question on the table: is the next wave of AI data centres a Swedish opportunity, and what does the grid need to make it happen?

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To get real value from #generativeAI, organizations are customizing model to match their business DNA. 💻🧬 In this #AWS blog, learn five tips for tuning generative AI models, from starting with clear business goals to choosing the right customization approach and optimizing coast + performance. 👉

Amazon Web Services

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