O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 362

Marketing Experimentation Metrics Testing 362

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management. What Is Model Risk?

Risk Management 64

Risk Management Risk Modeling Enterprise 64

CIO Business Intelligence

MAY 16, 2024

The company is also making available AI connectors that organizations could use to integrate the Camunda platform with generative AI machine learning platforms from OpenAI, Azure OpenAI, and Hugging Face without the need for a lot of experience or development resources, he said. They will be added to Camunda 8.5

Experimentation 108

Experimentation Machine Learning Technology Modeling 108

CIO Business Intelligence

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since.

Experimentation 129

Experimentation Strategy Machine Learning Interactive 129

CIO Business Intelligence

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

NOVEMBER 7, 2022

CIOs seeking big wins in high business-impacting areas where there’s significant room to improve performance should review their data science, machine learning (ML), and AI projects. Have business leaders defined realistic success criteria and areas of low-risk experimentation? Are data science teams set up for success?

Machine Learning 128

Machine Learning Data Science Experimentation IoT 128

CIO Business Intelligence

SEPTEMBER 6, 2023

While the potential of Generative AI in software development is exciting, there are still risks and guardrails that need to be considered. Risks of AI in software development Despite Generative AI’s ability to make developers more efficient, it is not error free. To learn more, visit us here.

Software 119

Software Experimentation Risk Data Lake 119

CIO Business Intelligence

NOVEMBER 15, 2022

Experiment with the “highly visible and highly hyped”: Gartner repeatedly pointed out that organisations that innovate during tough economic times “stay ahead of the pack”, with Mesaglio in particular calling for such experimentation to be public and visible. Artificial Intelligence, Digital Transformation, Innovation, Machine Learning

Digital Transformation 143

Digital Transformation Experimentation Risk Metrics 143

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

Deep Learning 67

Deep Learning Experimentation Machine Learning Risk 67

DataRobot Blog

NOVEMBER 15, 2022

At the event, a financial services panel discussion shared why iteration and experimentation are critical in an AI-driven data science environment. This allows GCash to maintain the pace of innovation and iteration without exposing the business to significant risk. Learn How to Accelerate Business Results with DataRobot AI Cloud.

Big Data 52

Big Data Experimentation Data-driven Machine Learning 52

Smart Data Collective

OCTOBER 13, 2021

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. Big data also helps you identify potential business risks and offers effective risk management solutions. Use machine learning. Machine learning is one of the biggest applications of AI.

Technology 120

Technology Cost-Benefit Experimentation Machine Learning 120

Cloudera

OCTOBER 4, 2023

In financial services, fast-moving data is critical for real-time risk and threat assessments. This also achieves workload isolation, so we can run mission critical workloads independent from experimental and exploratory ones and nobody steps on anyone’s toes by accident.

Data Warehouse 84

Data Warehouse Experimentation Cost-Benefit Dashboards 84

Cloudera

OCTOBER 18, 2023

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement — to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. Automated documentation generation: Generating documentation is time consuming and tedious.

Cost-Benefit 76

Cost-Benefit Testing Machine Learning Optimization 76

CIO Business Intelligence

JANUARY 9, 2024

Many organizations know that commercially available, “off-the-shelf” generative AI models don’t work well in enterprise settings because of significant data access and security risks. Knowing these lessons before generative AI adoption will likely save time, improve outcomes, and reduce risks and potential costs.

Enterprise 117

Enterprise Experimentation Modeling Data-driven 117

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 104

IT Digital Transformation IoT Cost-Benefit 104

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 92

Unstructured Data Cost-Benefit Experimentation Machine Learning 92

IBM Big Data Hub

MAY 25, 2023

In 2023 alone, IBM Consulting has interacted with more than 100 clients and completed dozens of engagements infusing generative AI alongside classical machine learning AI strategies. At the same time, there are reasonable concerns about how to mitigate bias, manage data security, and factor in precision and risk.

Consulting 103

Consulting Experimentation Machine Learning Modeling 103

IBM Big Data Hub

DECEMBER 4, 2023

Advacements in machine learning algorithms, neural networks and the computational power of generative AI, combined with human expertise, intuition and creativity, can unlock new possibilities and achieve levels of innovation that were previously unimaginable.

Experimentation 64

Experimentation Modeling Metrics Machine Learning 64

Corinium

JUNE 6, 2019

Regulations and compliance requirements, especially around pricing, risk selection, etc., It is also important to have a strong test and learn culture to encourage rapid experimentation. Given enough trials and data, Machine Learning techniques are likely to add great value in the forecasting process.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. We now use AI to help faculty understand some of those risk factors,” says Fozard.

Recreation/Entertainment 134

Recreation/Entertainment Experimentation Modeling Data-driven 134

Smart Data Collective

JULY 9, 2023

Optimizing Conversion Rates with Data-Driven Strategies A/B Testing and Experimentation for Conversion Rate Optimization A/B testing is essential for discovering which version of your website’s elements are most effective in driving conversions. Experimentation is the key to finding the highest-yielding version of your website elements.

Optimization 73

Optimization Data Analytics Analytics Data-driven 73

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. A sure-fire formula for driving innovative growth is to “try something new, learn fast, pivot as needed, and scale success,’’ says Mike Crowe, CIO of Colgate-Palmolive. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

DataRobot Blog

OCTOBER 18, 2022

I demonstrated how this “needle in a haystack” problem can be solved by leveraging automated machine learning to rank potentially suspicious alerts enabling AML agents to prioritize investigation of high risk alerts, effectively reducing the number of costly false positives. Monitoring with Machine Learning.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

CIO Business Intelligence

JUNE 12, 2023

It can be about anything from classic data analysis and advanced data analysis, to robotics or machine learning. The vast majority of companies already have a structure for analytics and machine learning, so we’re already there; it doesn’t add much,” she adds. It’s all called AI, she says.

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

CIO Business Intelligence

JUNE 28, 2023

For all of generative AI’s allure, large enterprises are taking their time, many outright banning tools like ChatGPT over concerns of accuracy, data protection, and the risk of regulatory backlash. Experimentation with a use case driven approach. Caution is king.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

The Unofficial Google Data Science Blog

APRIL 23, 2024

To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages. Our experimentation platform supports this kind of grouped-experiments analysis, which allows us to see rough summaries of our designed experiments without much work.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Dataiku

OCTOBER 2, 2019

In 2018, O’Reilly conducted a survey regarding the stage of machine learning adoption in organizations, and among the more than 11,000 respondents, almost half were still in the exploration phase.

Risk 14

Risk Experimentation Management Machine Learning 14

CIO Business Intelligence

FEBRUARY 14, 2024

People aren’t going back and decluttering because there’s no cost to that — except in your risk profile and your decreased search performance,” says Buckley. Artificial Intelligence, Budgeting, CIO, Data Governance, Data Management, Generative AI, IT Governance, IT Leadership, Machine Learning, Security

IT 143

IT Metadata Data-driven Management 143

Decision Management Solutions

DECEMBER 17, 2021

We work with lenders in a variety of markets and have found that decision modeling, building a visual blueprint of your credit risk decisioning, is a critical success factor in moving to next generation credit decisioning. Lower credit losses. More efficient lending. Sounds good, right?

Modeling 52

Modeling Experimentation Visualization Risk 52

CIO Business Intelligence

OCTOBER 1, 2022

P&G is also piloting the use of IIoT, advanced algorithms, machine learning (ML), and predictive analytics to improve manufacturing efficiencies in the production of paper towels. It has moved past what Cretella calls the “experimentation phase” with scaled solutions and increasingly sophisticated AI applications.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

CIO Business Intelligence

OCTOBER 9, 2023

Hyatt’s experimental mindset and listen-first approach are heavily applied to IT’s pursuit of innovation, he says. I think of it almost like a machine learning algorithm called ‘multi-armed bandit,’” that has two axes: exploit and explore, he says. Companies can stick stubbornly to something without pivoting.

Strategy 137

Strategy Technology Experimentation Testing 137

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ).

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

DataRobot Blog

AUGUST 10, 2022

NHS organisations are used to using workforce KPIs to manage staffing levels, but the real opportunity is being able to identify staff that are at risk of leaving post and to implement strategies to retain their much needed talent. Resetting urgent care performance and delivery. Improving patient outcomes through a data-first approach.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

Ontotext

APRIL 3, 2024

W hen you try to automate business processes, semantics, and machine learning , knowledge graphs can bring a lot of value. Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. How do I make sure I can manage risk?”

Technology 59

Technology Risk Digital Transformation Measurement 59

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

CIO Business Intelligence

MAY 10, 2023

focuses on driving mobility and tapping on the then-nascent Internet of Things, the subsequent phase prominently features technology such as artificial intelligence and machine learning and ways to extend their use across every aspect of the business. Whereas digital transformation in its earliest iteration—digital transformation 1.0—focuses

Enterprise 52

Enterprise Digital Transformation Internet of Things B2B 52

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. AGI wouldn’t just perceive its surroundings; it would understand them.

Cost-Benefit 93

Cost-Benefit Modeling Manufacturing Interactive 93