Remove 2011 Remove Reporting Remove Uncertainty
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Generative AI sparks family business renaissance: PwC report

CIO Business Intelligence

The next generation of leaders in family businesses is poised to embrace the transformative power of generative AI (GenAI) despite marked resistance from the incumbent leaders, according to a PwC report. The survey findings too echoed Hinojosa’s sentiment.

Reporting 104
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Paul Martin: CIOs don’t retire, they go work on boards

CIO Business Intelligence

Two years of pandemic uncertainty and escalating business risk have sharpened the focus of corporate boards on a technology trend once dismissed as just another IT buzzword. I joined Baxter as CIO in 2011, and in 2016 I was presented with the opportunity to join my first public company board. How did that opportunity come about?

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Cloudera + Hortonworks, from the Edge to AI

Cloudera

Since 2011, our two companies have each innovated to build better products and win more business. Three years later, the core team of developers working inside Yahoo on Hadoop spun out to found Hortonworks. They, too, saw the enormous potential for data at scale in the enterprise. Forward-Looking Statements.

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Why CEOs should test big digital business ideas in tiny countries.

Mark Raskino

The President of Iceland Olafur Ragnar Grimsson explained this phenomenon to me when I had the privilege to interview him in 2011 (Gartner Report: G00212784 ). “So He was talking about something we call the ‘compound uncertainty’ that must be navigated when we want to test and introduce a real breakthrough digital business idea.

Testing 53
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Fact-based Decision-making

Peter James Thomas

Of course the problem is then that Financial Reports (or indeed most Management Reports) are not set up to cope with plus or minus figures, so typically one of £12.4 By the time that people who need to take decisions based on such information are in the loop, the inherent uncertainty of the prediction may have disappeared.

Metrics 49
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Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

Quantification of forecast uncertainty via simulation-based prediction intervals. In the first plot, the raw weekly actuals (in red) are adjusted for a level change in September 2011 and an anomalous spike near October 2012. Prediction Intervals A statistical forecasting system should not lack uncertainty quantification.

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Fitting Bayesian structural time series with the bsts R package

The Unofficial Google Data Science Blog

The data consist of the weekly initial claims for unemployment insurance in the US, as reported by the US Federal Reserve. This model has stationary distribution $$mu_infty sim Nleft(0, frac{sigma^2_eta}{1 - rho^2}right),$$ which means that uncertainty grows to a finite asymptote, rather than infinity, in the distant future.