Remove Data Quality Remove Data Science Remove Data-driven Remove Uncertainty
article thumbnail

Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. Those F’s are: Fragility, Friction, and FUD (Fear, Uncertainty, Doubt). These changes may include requirements drift, data drift, model drift, or concept drift.

Strategy 289
article thumbnail

Decision Making with Uncertainty Requires Wideward Thinking

Andrew White

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. As a result, Data, Analytics and AI are in even greater demand. Demand from all these organizations lead to yet more data and analytics. With data comes quality issues.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Data Science, Past & Future

Domino Data Lab

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

article thumbnail

The state of data quality in 2020

O'Reilly on Data

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Adopting AI can help data quality.

article thumbnail

Transforming FSI in ASEAN with Cloud Analytics

CIO Business Intelligence

Its success is one of many instances illustrating how the financial services industry is quickly recognizing the benefits of data analytics and what it can offer, especially in terms of risk management automation, customized experiences, and personalization. . compounded annual growth from 2019 to 2024. .

article thumbnail

What’s New and What’s Next in 2023 for HPC

CIO Business Intelligence

Cloud, sustainability, scale, and exponential data growth—these major factors that set the tone for high performance computing (HPC) in 2022 will also be key in driving innovation for 2023. As leaders in the HPC industry, we are worried about how to cool these data centers. Another big focus is on liquid cooling. [2]

article thumbnail

AI Product Management After Deployment

O'Reilly on Data

From a technical perspective, it is entirely possible for ML systems to function on wildly different data. For example, you can ask an ML model to make an inference on data taken from a distribution very different from what it was trained on—but that, of course, results in unpredictable and often undesired performance. I/O validation.