Remove Data Science Remove Modeling Remove Uncertainty
article thumbnail

The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 210
article thumbnail

Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290
Insiders

Sign Up for our Newsletter

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

article thumbnail

Leveraging Data Science To Grow And Manage Your Team

Smart Data Collective

Fortunately, recruitment software and tools allow for data-driven decision-making that eliminates human bias and uncertainties, ultimately helping you make better decisions during the hiring process with greater accuracy and peace of mind. Big data has the potential to greatly improve the hiring process for our business.

article thumbnail

Systems Thinking and Data Science: a partnership or a competition?

Jen Stirrup

How can systems thinking and data science solve digital transformation problems? Understandably, organizations focus on the data and the technology since data retrieval is often viewed as a data problem. However, the thrust here is not to diminish data science or data engineering.

article thumbnail

Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

One of the firm’s recent reports, “Political Risks of 2024,” for instance, highlights AI’s capacity for misinformation and disinformation in electoral politics, something every client must weather to navigate their business through uncertainty, especially given the possibility of “electoral violence.” “The

IT 122
article thumbnail

Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model.

article thumbnail

Regulatory uncertainty overshadows gen AI despite pace of adoption

CIO Business Intelligence

It’s no surprise, then, that according to a June KPMG survey, uncertainty about the regulatory environment was the top barrier to implementing gen AI. So here are some of the strategies organizations are using to deploy gen AI in the face of regulatory uncertainty. Companies in general are still having problems with data governance.”