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

MARCH 14, 2022

In How to Measure Anything , Douglas Hubbard offers an alternative definition of “measurement” to the Oxford English Dictionary’s “the size, length, or amount of something.” Hubbard defines measurement as: “A quantitatively expressed reduction of uncertainty based on one or more observations.”.

Uncertainty 92

Uncertainty Measurement Cost-Benefit Optimization 92

Cloudera

DECEMBER 3, 2021

This involves identifying, quantifying and being able to measure ethical considerations while balancing these with performance objectives. 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. Governance.

Uncertainty 97

Uncertainty Measurement Metrics Risk 97

CIO Business Intelligence

FEBRUARY 8, 2024

The global IT services industry is at a significant crossroads, with the explosive growth of generative AI and deepening economic uncertainties reshaping its future. Although there are efforts to boost industries such as semiconductors, there is much uncertainty about when the impact may be seen.

IT 90

IT Uncertainty Consulting Forecasting 90

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. Machine learning adds uncertainty. Models also become stale and outdated over time.

Management 332

Management Machine Learning Experimentation Metrics 332

DataRobot

AUGUST 30, 2021

An AI system is more than just a model. Best practices in the realm of Operations are as pivotal to an AI system’s trustworthiness as the design of the model itself. Humility Means Recognizing Uncertainty. Recognizing and admitting that uncertainty is a major step in establishing trust. Conclusion. AI you can trust.

Uncertainty 90

Uncertainty Modeling Measurement Software 90

IBM Big Data Hub

FEBRUARY 20, 2024

These proactive measures are made possible by evolving technologies designed to help people adapt to the effects of climate change today. Climate models provide answers Human activities precipitated changes to the Earth’s climate in the 20th century and will largely determine the future climate.

Modeling 119

Modeling Forecasting Reporting Risk 119

CIO Business Intelligence

FEBRUARY 26, 2024

For any AI model, you can’t interpret the relevance and reliability of the output if you don’t understand the context of the data.” Hot: Getting comfortable with uncertainty To address disruptions across multiple aspects of the business, organizations need to be able to pivot quickly, says DeVry University CIO Chris Campbell.

IT 128

IT Uncertainty Strategy Testing 128

CIO Business Intelligence

MAY 9, 2023

Like most CIOs you’ve no doubt leaned on ROI, TCO and KPIs to measure the business value of your IT investments. Those Three Big Acronyms are still important for fine-tuning your IT operations, but success today is increasingly measured in business outcomes. Maybe you’ve even surpassed expectations in each of these yardsticks.

ROI 119

ROI Cost-Benefit KPI Uncertainty 119

CIO Business Intelligence

OCTOBER 4, 2022

In the new report, titled “Digital Transformation, Data Architecture, and Legacy Systems,” researchers defined a range of measures of what they summed up as “data architecture coherence.” He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.

Machine Learning 107

Machine Learning Data Architecture Uncertainty Data-driven 107

CIO Business Intelligence

JUNE 23, 2023

An astounding 93% of respondents noted they strongly agree with the sentence, “I believe my organization needs to embrace a hybrid infrastructure model that spans from mainframe to cloud.” Hybrid cloud solutions are proving to be the most impactful way to modernize an IT organization.

IT 97

IT Risk Management Risk Optimization 97

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

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. Improving annotation quality is crucial for various tasks, including data labeling for machine learning models, document categorization, sentiment analysis, and more.

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

CIO Business Intelligence

JULY 23, 2023

EY recently found that in current economic and financial uncertainty, 94% of tech executives plan to increase their IT investment over the next year. Optimization also rose to the top of IT leaders’ lists: 67% measure success within their IT organization by better optimizing resources.

Optimization 76

Optimization IT Digital Transformation Uncertainty 76

CIO Business Intelligence

DECEMBER 18, 2023

A primary fear is that employees, partners, and organizational stakeholders might share everything from private data to source code into public large language models (LLMs), expose proprietary information and intellectual property, or reveal vulnerabilities to exploit.

Enterprise 114

Enterprise Management Risk Uncertainty 114

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. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

SEPTEMBER 20, 2023

They are afraid of failure and the uncertainty of knowledge work, and so that’s stressful. Agile is an amazing risk management tool for managing uncertainty, but that’s not always obvious.” The key is recognizing that planning must be an agile discipline, not a standalone activity performed independently of agile teams.

Digital Transformation 130

Digital Transformation Uncertainty Metrics Business Objectives 130

Jedox

SEPTEMBER 3, 2020

The unprecedented uncertainty forced companies to make critical decisions within compressed time frames. Many pre-crisis business assumptions and planning models became outmoded overnight. Using these drivers as an overlay to stress-test models add robustness to forecasting and can identify exposure and risks to long-term stability.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

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

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

Jet Global

JULY 23, 2020

Fortunately, the level of uncertainty has fallen considerably, as many businesses are beginning to re-open, albeit with some restrictions and under capacity restrictions. Maintain close relationships with key suppliers and consider taking measures to defend against supply chain interruptions.

Uncertainty 95

Uncertainty Finance Cost-Benefit Reporting 95

Sisense

MARCH 26, 2020

To effectively identify what measures need to be taken, analytics can help to summarize and predict how companies should evolve to survive in a challenging environment. Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. Making smarter staffing decisions.

Management 91

Management Cost-Benefit Uncertainty Digital Transformation 91

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 88

Cost-Benefit Modeling Manufacturing Interactive 88

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Data Variety. This will only become more important as we move into 2021 and a post-pandemic new normal.

Insurance 91

Insurance Digital Transformation Unstructured Data Machine Learning 91

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. You pay only the associated Forecast costs.

Forecasting 80

Forecasting Data Warehouse Machine Learning Modeling 80

BizAcuity

MARCH 18, 2019

Credit scoring systems and predictive analytics model attempt to quantify uncertainty and provide guidance for identifying, measuring and monitoring risk. The consumer lending business is centered on the notion of managing the risk of borrower default. Benefits of Predictive Analytics in Unsecured Consumer Loan Industry.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

CIO Business Intelligence

FEBRUARY 23, 2023

The former rely on batch processing to train machine learning models and generate features (measurable properties of a phenomenon). He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing. Artificial Intelligence, IT Leadership

Uncertainty 87

Uncertainty Strategy Data-driven Machine Learning 87

CIO Business Intelligence

OCTOBER 18, 2023

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 138

Risk Manufacturing Enterprise Technology 138

IBM Big Data Hub

OCTOBER 18, 2022

Most admit uncertainty around ROI and nearly half struggle with adequate insights from their data. Fewer than 1 in 4 agree that sustainability requires financial tradeoffs, but many acknowledge the need to redefine and re-calibrate how they measure performance.

Uncertainty 52

Uncertainty Strategy Measurement Digital Transformation 52

CIO Business Intelligence

JANUARY 4, 2023

Here are the shifts we noted: Delivery Models : Moving from an almost strictly on-premises systems approach (with some remote access services), HPC is embracing remote delivery models. Due to the rapid growth in data sizes, there’s an increased need for HPC solutions that can run large training models.

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

The Unofficial Google Data Science Blog

JULY 18, 2023

E ven after we account for disagreement, human ratings may not measure exactly what we want to measure. Researchers and practitioners have been using human-labeled data for many years, trying to understand all sorts of abstract concepts that we could not measure otherwise. That’s the focus of this blog post.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Perceptual Edge

APRIL 21, 2019

We could argue that the signal-to-noise ratio is the most essential consideration in data visualization—the fundamental guide for all design decisions while creating a data visualization and the fundamental measure of success once it’s out there in the world.

Visualization 76

Visualization Statistics Uncertainty Modeling 76

Sisense

MARCH 24, 2020

Now is the time to apply the full force of business intelligence used by analytics teams to help navigate growing uncertainty. With smart dashboards and KPIs , the BraunAbility team is able to tie discount data from marketing platforms to sales results in order to more effectively measure the impact of any discount.

Analytics 94

Analytics Sales Forecasting Business Intelligence 94

CIO Business Intelligence

SEPTEMBER 12, 2022

The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. It requires bold bets and a willingness to persevere despite setbacks, criticism, and uncertainty,’’ wrote McKinsey senior partners Laura Furstenthal and Erik Roth in a recent blog post. “By Elixirr Consulting.

Experimentation 131

Experimentation Consulting Technology Machine Learning 131

CIO Business Intelligence

JULY 7, 2023

This module validates your ability to measure, assess, and develop the Service Desk practice capability using the ITIL Maturity Model. It covers challenges around volatility, uncertainty, complexity, and ambiguity (VUCA) and how to conduct a full cost benefit analysis to identify potential risks and opportunities.

Cost-Benefit 98

Cost-Benefit Strategy Management Uncertainty 98

Sisense

SEPTEMBER 9, 2019

Then we ran Kraken’s machine learning and predictive modeling engine to get the results. Following a few false starts and some great iterative learning with the BigSquid team, we came away with a solid predictive data model of the warranty costs for future periods. Using Sentiment Analytics to Inform New Product Design Decisions.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Crucially, it takes into account the uncertainty inherent in our experiments. Figure 2: Spreading measurements out makes estimates of model (slope of line) more accurate.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52