Jedox

APRIL 16, 2020

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

Uncertainty 52

Uncertainty Management Forecasting Predictive Modeling 52

Rocket-Powered Data Science

MAY 21, 2024

Another example is Pure Storage’s FlashBlade ® which was invented to help companies handle the rapidly increasing amount of unstructured data coming into greater use, as required in the training of multi-modal AI models. In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g.,

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

Rocket-Powered Data Science

JULY 19, 2023

The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage. One could say that sentinel analytics is more like unsupervised machine learning, while precursor analytics is more like supervised machine learning.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

O'Reilly on Data

JANUARY 22, 2019

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 133

Modeling Finance Uncertainty Data mining 133

DataRobot

AUGUST 5, 2021

AI and Uncertainty. Some people react to the uncertainty with fear and suspicion. Recently published research addressed the question of “ When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making.”. People are unsure about AI because it’s new. AI you can trust.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

CIO Business Intelligence

JANUARY 11, 2024

To get back in front, IT leaders will have to transform lessons learned from 2023 into actionable, adaptable processes, as veteran technology pros have been remarkably consistent in identifying global and economic uncertainties as key challenges for IT leaders to anticipate in 2024 as well.

IT 116

IT Uncertainty Cost-Benefit Strategy 116

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 82

Uncertainty Manufacturing Data-driven Business Intelligence 82

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 82

Uncertainty Manufacturing Data-driven Business Intelligence 82

Domino Data Lab

MARCH 21, 2023

98% of CDOs and CDAOs say the companies that bring AI and ML solutions to market fastest will be the ones who survive and thrive in the upcoming times of economic uncertainty. In today's economic environment, all organizations need to unlock greater AI value, faster.

Uncertainty 98

Uncertainty Enterprise Marketing Modeling 98

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. While calibration seems like a straightforward and perhaps trivial property, miscalibrated models are actually quite common. Why calibration matters What are the consequences of miscalibrated models?

Modeling 122

Modeling IT Metrics Testing 122

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 240

Management Metrics Machine Learning Modeling 240

The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. It is a big picture approach, worthy of your consideration.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

DECEMBER 3, 2021

Systems should be designed with bias, causality and uncertainty in mind. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Model Drift. System Design. Human Judgement & Oversight.

Uncertainty 100

Uncertainty Measurement Metrics Risk 100

CIO Business Intelligence

APRIL 27, 2023

At this time of dynamic business and market changes, uncertainty, and quickly evolving consumption models for IT infrastructure, every IT executive understands the benefits and necessity of network agility. Machine learning has also greatly advanced over the past several years. There were also limitations in technology.

Management 83

Management Internet of Things Cost-Benefit Uncertainty 83

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes.

Data mining 123

Data mining Data-driven Statistics OLAP 123

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. The resulting structured data is then used to train a machine learning algorithm.

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Given this, it’s crucial to have in Place meticulous testing protocols for the results of models, visualizations, data delivery mechanisms, and overall data utilization.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. Operations.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

SEPTEMBER 13, 2023

Gearing up to build an app that taps the power of highly capable foundation models is not hard for any modern developer. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. Artificial Intelligence, Machine Learning

Uncertainty 81

Uncertainty Interactive Strategy Machine Learning 81

O'Reilly on Data

SEPTEMBER 15, 2021

There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Economic uncertainty caused by the pandemic may be responsible for the declines in compensation. Would your job still be there in a year? Salaries by Tool and Platform.

Machine Learning 362

Machine Learning Statistics Reporting Consulting 362

AWS Big Data

AUGUST 7, 2023

Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

CIO Business Intelligence

DECEMBER 18, 2023

That said, it’s still worthwhile to think about how to use large language model (LLM)-powered tools like ChatGPT in more strategic ways. One is to shoehorn that back into a “strive for perfect artifacts, then submit to audit” model of getting to high-quality decisions. Artificial Intelligence, Machine Learning

Strategy 127

Strategy IT Uncertainty Machine Learning 127

O'Reilly on Data

SEPTEMBER 15, 2020

It also helps companies learn how to translate existing AI capabilities into solving specific real-world problems and use cases. In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical competence results in reduced risk and uncertainty.

Cost-Benefit 290

Cost-Benefit Advertising ROI Machine Learning 290

Timo Elliott

MARCH 6, 2023

He explains how businesses can leverage AI and machine learning to turn anything into a sensor, detect patterns in new ways, and augment human intelligence. He also mentions ASR Group using machine learning to optimize routes for sugar delivery to their 600 customers, reducing logistics costs.

Machine Learning 111

Machine Learning Cost-Benefit Uncertainty ROI 111

Andrew White

FEBRUARY 23, 2021

The D&A trends for 2021 covered in this research can help organizations respond to change, uncertainty and the opportunities they bring over the next three years. To deal with unprecedented levels of business complexity and uncertainty, organizations must improve their ability to accelerate accurate and highly contextualized decisions.

Analytics 90

Analytics Uncertainty Machine Learning Modeling 90

CIO Business Intelligence

FEBRUARY 23, 2024

The completion of such transformative EV and hydrogen fuel cell engineering — amid uncertainty about which technology will prevail as the industry standard — reflects the one constant American Honda’s VP of IT Bob Brizendine has confronted throughout his 36 years with the company: an ever-changing, winding road that never slows down.

IT 120

IT Manufacturing Unstructured Data Strategy 120

CIO Business Intelligence

APRIL 28, 2023

Amazon’s cloud computing division, AWS, is shifting its focus towards large language models (LLMs) and generative AI -based offerings as it continues to see a downward spiral in overall revenue growth. If you think about maybe the bottom layer here, is that all of the large language models are going to run on compute.

Enterprise Optimization 52

Enterprise Optimization Recreation/Entertainment Advertising Uncertainty 52

CIO Business Intelligence

JUNE 25, 2023

After being “awed” by OpenAI’s GPT model acing the AP Bio exam, the model was asked a non-technical question: “What do you say to a father with a sick child?” Fine-tuning models that run “on top” of foundation models requires less data, costs less, and can be completed quickly. Artificial Intelligence, Machine Learning

Finance 95

Finance Uncertainty Strategy Modeling 95

CIO Business Intelligence

SEPTEMBER 6, 2023

Since ChatGPT’s release in November of 2022, there have been countless conversations on the impact of similar large language models. The use of AI-generated code is still in an experimental phase for many organizations due to numerous uncertainties such as its impact on security, data privacy, copyright, and more.

Software 112

Software Experimentation Risk Data Lake 112

CIO Business Intelligence

DECEMBER 4, 2023

From grapes to wine—a journey of uncertainty Wineries must consider many factors to achieve maximum efficiency, yield, and quality. First, there’s the life of the grapes. As the grapes grow, their annual development can be affected by factors such as climate, sunlight, water, vine density, soil, and nutrients.

Uncertainty 69

Uncertainty Digital Transformation Optimization Machine Learning 69

DataRobot

JUNE 1, 2021

Before you put a model into production, you may first need to clear compliance hurdles. Typically, these areas require the most attention: model development, implementation, and use. Managing risk for any model involves understanding which monitoring and risk-mitigation procedures apply. Knowing When to Trust a Model.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

CIO Business Intelligence

MARCH 10, 2023

Digital transformation has brought significant adoption of new technology and business models, including cloud solutions, e-commerce platforms, smart devices, and a significantly more distributed workforce. Artificial Intelligence, IT Leadership, Machine Learning

Digital Transformation 119

Digital Transformation Cost-Benefit ROI Risk 119

IBM Big Data Hub

MAY 13, 2024

For example, healthcare companies are starting to use machine learning technologies to improve and speed up medical diagnoses. HR representatives need to learn how to use this technology to spot potential biases or other uncertainties, so they find valuable prospects.

Digital Transformation 85

Digital Transformation Gap analysis Consulting Machine Learning 85

CIO Business Intelligence

AUGUST 14, 2023

The collaboration between Huabao and SAP continued as plans for a new foundation to support corporate development and business model transformation gathered speed. Capitalizing on SAP’s in-memory database, the solution is renowned for meeting the exact challenges Huabao hoped to address navigating uncertainty and refining business results.

Key Performance Indicator 89

Key Performance Indicator Sales Manufacturing KPI 89

DataRobot

APRIL 5, 2021

The uncertainty in her reply piqued my interest. Some claim that fully interpretable models are the solution, that we should constrain the complexity of algorithms so that a layperson can understand them. Some participants were advised of potential model shortcomings due to specific missing inputs.

Uncertainty 96

Uncertainty Machine Learning Modeling Reporting 96

Cloudera

JULY 15, 2021

In this session we explored what firms are doing to approach the uncertainty with more predictability. Across the industry, the pandemic caused a huge breakdown in model performance due to the change in macroeconomic conditions and government stimulus packages. Observe what the model has to offer even if not the intended output.

Risk 99

Risk Optimization Management Insurance 99

CIO Business Intelligence

JANUARY 9, 2023

Three years ago, IT leaders were squarely focused on how to adopt fledgling AI techniques and approaches into their business models in service of digital transformations that included plans for shifting some workloads to the cloud. How do you future-proof your business in the face of so much uncertainty?

IT 145

IT Uncertainty Cost-Benefit Digital Transformation 145