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To understand the risks posed by AI, follow the money

O'Reilly on Data

Others retort that large language models (LLMs) have already reached the peak of their powers. These are risks stemming from misalignment between a company’s economic incentives to profit from its proprietary AI model in a particular way and society’s interests in how the AI model should be monetised and deployed.

Risk 317
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Why you should care about debugging machine learning models

O'Reilly on Data

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

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Generative AI in Education: Visual Storytelling From Text – A Python Guide

Analytics Vidhya

Explore the extensive possibilities in design, art, and advertising as this comprehensive guide takes you step-by-step through using pre-trained models to craft striking visuals. […] The post Generative AI in Education: Visual Storytelling From Text – A Python Guide appeared first on Analytics Vidhya.

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How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. characters, words, or sentences).

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Multi-Channel Attribution: Definitions, Models and a Reality Check

Occam's Razor

And as if that was not enough, :), I'll close the post with my thoughts on digital marketing attribution models. An example of MCA-O2S is Verizon wanting to know how many in-store offline phone activations are driven by online search advertising, for every online activation that the same search advertising drives. [In

Modeling 154
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Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models

Occam's Razor

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 162
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Selecting the Right AI Business Model for Your Startup

Smart Data Collective

However, it is important to make sure that you understand the potential role of AI and what business model to build around it. However, even the most brilliant idea built around AI technology can fail without a proper business model. Without a good business model, you won’t understand customer needs and how to build your startup.

Modeling 116