O'Reilly on Data

MARCH 25, 2025

People have been building data products and machine learning products for the past couple of decades. The coordination tax: LLM outputs are often evaluated by nontechnical stakeholders (legal, brand, support) not just for functionality, but for tone, appropriateness, and risk. This isnt anything new.

Testing 168

Testing Data-driven Software Measurement 168

O'Reilly on Data

SEPTEMBER 15, 2020

Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk. Results are typically achieved through a scientific process of discovery, exploration, and experimentation, and these processes are not always predictable.

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

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

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

DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices.

Machine Learning 87

Machine Learning Marketing Experimentation Data-driven 87

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

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 133

Technology Cost-Benefit Experimentation Machine Learning 133

CIO Business Intelligence

OCTOBER 3, 2024

Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection and other use cases.

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

CIO Business Intelligence

MARCH 7, 2023

But the faster transition often caused underperforming apps, greater security risks, higher costs, and fewer business outcomes, forcing IT to address these issues before starting app modernizations. Integrate a new data source, then scan and mask the data for personally identifiable information.

Digital Transformation 145

Digital Transformation Data Governance Experimentation Machine Learning 145

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 Machine Learning Experimentation Metrics 143

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 130

Experimentation Strategy Machine Learning Interactive 130

CIO Business Intelligence

APRIL 29, 2024

As organizations roll out AI applications and AI-enabled smartphones and devices, IT leaders may need to sell the benefits to employees or risk those investments falling short of business expectations. They need to have a culture of experimentation.” CIOs should be “change agents” who “embrace the art of the possible,” he says.

Forecasting 135

Forecasting Experimentation Risk Machine Learning 135

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

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

MARCH 19, 2025

I first described the overall AI landscape and made sure they realized weve been doing AI for quite a while in the form of machine learning and other deterministic models. This can cause risk without a clear business case. I then described what I think of as the three categories of generative AI. Thats a critical piece.

Metrics 64

Metrics Enterprise Cost-Benefit Experimentation 64

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. He also advises CIOs to foster a culture of continuous learning and upskilling to build internal AI capabilities.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

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 Risk Experimentation Uncertainty 119

CIO Business Intelligence

SEPTEMBER 23, 2024

From the rise of value-based payment models to the upheaval caused by the pandemic to the transformation of technology used in everything from risk stratification to payment integrity, radical change has been the only constant for health plans. The culprit keeping these aspirations in check? It is still the data.

Management 115

Management Experimentation Data-driven Strategy 115

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

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Data-driven 150

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

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

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 111

Experimentation Machine Learning Technology Risk 111

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

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

CIO Business Intelligence

MAY 14, 2024

Like many public health agencies across the US, the King County Medical Examiner’s Office tracks drug overdose deaths to target interventions for populations at risk and save lives. And then what’s really cool is adding on this more experimental aspect with the machine learning capability.”

Deep Learning 97

Deep Learning Machine Learning Reporting Experimentation 97

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

CIO Business Intelligence

JULY 7, 2023

As more individuals use browser-based apps to get their work done, IT leaders need to provide seamless access to corporate apps and tools while minimizing security risks. Finding the right use cases for AI while minimizing risk to the business requires collaboration between IT and the workforce. Caution is king, however.

Measurement 122

Measurement Risk Experimentation Enterprise 122

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

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CIO Business Intelligence

SEPTEMBER 30, 2024

It is one of the few midsize companies with Federal Risk and Authorization Management Program (FedRAMP) authorization, the government’s highest security certification for cloud operators and required for work with federal agencies.

Data Quality 116

Data Quality Experimentation Insurance Statistics 116

CIO Business Intelligence

APRIL 24, 2024

That includes many technologies based on machine learning, such as sales forecasting, lead scoring and qualification, pricing optimization, and customer sentiment analysis. CFOs are traditionally risk averse and expect certainty and accuracy from their technology. But then you’re just playing catch-up.

Sales 128

Sales Finance Experimentation Cost-Benefit 128

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 97

Optimization Data Analytics Analytics Data-driven 97

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 119

Enterprise Experimentation Modeling Data-driven 119

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 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

IBM Big Data Hub

JUNE 10, 2024

Accessing specialized expertise Implementing AI initiatives often requires specialized skills and expertise in areas such as data science, machine learning and AI development. Facilitating rapid experimentation and innovation In the age of AI, rapid experimentation and innovation are essential for staying ahead of the competition.

Experimentation 62

Experimentation Optimization Risk Management Machine Learning 62