Remove Experimentation Remove Interactive Remove ROI Remove Statistics
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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Here are some areas where organizations are seeing a ROI: Text (83%) : Gen AI assists with automating tasks like report writing, document summarization and marketing copy generation.

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Building Smarter Financial Services: The Role of Semantic Technologies, Knowledge Graphs and Generative AI

Ontotext

Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. Show me the ROI.” These are not statistical inferences. So, this is a big driver for the outcome because when you are saving money for the business, you can measure it and see its value.

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

For example auto insurance companies offering to capture real-time driving statistics from policy-holders’ cars to encourage and reward safe driving. What do you recommend to organizations to harness this but also show a solid ROI? And more recently, we have also seen innovation with IOT (Internet Of Things).

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Product Management for AI

Domino Data Lab

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. And then you’ll do a lot of work to get it out and then there’ll be no ROI at the end.

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

So much work in machine learning – either on the academic side which is focused on publishing papers or the industry side which is focused on ROI – tends to emphasize: How much predictive power (precision, recall) does the model have? Use of influence functions goes back to the 1970s in robust statistics.

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10 Fundamental Web Analytics Truths: Embrace 'Em & Win Big

Occam's Razor

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. It would be silly to not pick up the high ROI low cost stuff first right? Oh and when I say Experimentation I don't mean testing button sizes (BOO!).

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