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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

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ChatGPT, the rise of generative AI

CIO Business Intelligence

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. It’s hard to achieve a deep, experiential understanding of new technology without experimentation. It’s only one example of generative AI. GPT stands for generative pre-trained transformer.

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AI in Analytics: The NLQ Use Case

Sisense

When the app is first opened, the user may be searching for a specific song that was heard while passing by the neighborhood cafe, or the user may want to be surprised with, let’s say, a song from the new experimental album by a Yemen Reggae folk artist. when the user actually meant to compare between Q1 2018 to the whole of 2017?

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New Format for The Bar Chart Reference Page

The Data Visualisation Catalogue

Journal of Experimental Psychology: Applied, 4 (2), 119–138. Qu, H., & Sedlmair, M. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. Readability and Precision in Pictorial Bar Charts. Skau, D., & Kosara, R. Eurographics Conference on Visualization (EuroVis). Harrison, L., & Kosara, R.

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6 trends framing the state of AI and ML

O'Reilly on Data

Reinforcement learning fell by 5% in 2019; it’s up hugely—1,500+%—since 2017, however. The chatbot was one of the first applications of AI in experimental and production usage. We compared aggregated data for the last three years; a full year of data for 2017 and 2018, and through the end of October for 2019. [2]

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Instead, we focus on the case where an experimenter has decided to run a full traffic ramp-up experiment and wants to use the data from all of the epochs in the analysis. When there are changing assignment weights and time-based confounders, this complication must be considered either in the analysis or the experimental design.

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Transforming IT for cloud success

CIO Business Intelligence

So Holden, who has been CIO at Halfords — the UK’s largest retailer of motoring and cycling products and services — since 2017, developed a strategy to reorganize his tech team. ASU started its cloud journey a decade ago with experiments, before becoming more strategic and aggressive about cloud adoption when Gonick became CIO in 2017.

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