Experimentation Forecasting Modeling Risk 
DataRobot Blog
DECEMBER 6, 2022
Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. Taking a Multi-Tiered Approach to Model Risk Management. Forecast Time Series at Scale with Google BigQuery and DataRobot. Data scientists are in demand: the U.S.
CIO Business Intelligence
APRIL 29, 2024
As organizations roll out AI applications and AI-enabled smartphones and devices, IT leaders may need to sell the benefits to employees or risk those investments falling short of business expectations. They need to have a culture of experimentation.” CIOs should be “change agents” who “embrace the art of the possible,” he says.
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O'Reilly on Data
JULY 28, 2020
Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.
Jedox
SEPTEMBER 11, 2019
Even though we have so much advanced technology surrounding us, we still cannot just ask, “ Hey Siri, what’s my forecasted EBITDA look like ?” Experimental” Technology. Is AI truly experimental technology? Many of the algorithms used for budgeting, planning, and forecasting are already in use and were proven decades ago.
CIO Business Intelligence
NOVEMBER 21, 2023
Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.
CIO Business Intelligence
APRIL 24, 2024
But to find ways it can help grow a company’s bottom line, CIOs have to do more to understand a company’s business model and identify opportunities where gen AI can change the playing field. We have a HITRUST certified health care environment and we bring in publicly-available models.” And there are audit trails for everything.”
DataRobot Blog
SEPTEMBER 30, 2022
How do you track the integrity of a machine learning model in production? Model Observability can help. By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Model Observability Features.
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