Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? encouraging and rewarding) a culture of experimentation across the organization. Test early and often. Test and refine the chatbot. Suggestion: take a look at MACH architecture.)

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

JANUARY 14, 2025

By articulating fitness functions automated tests tied to specific quality attributes like reliability, security or performance teams can visualize and measure system qualities that align with business goals. Technical foundation Conversation starter : Are we maintaining reliable roads and utilities, or are we risking gridlock?

Enterprise 119

Enterprise Technology Metrics Measurement 119

CIO Business Intelligence

OCTOBER 17, 2024

While tech debt refers to shortcuts taken in implementation that need to be addressed later, digital addiction results in the accumulation of poorly vetted, misused, or unnecessary technologies that generate costs and risks. million machines worldwide, serves as a stark reminder of these risks.

Risk 108

Risk Experimentation Testing Strategy 108

CIO Business Intelligence

OCTOBER 24, 2024

As they look to operationalize lessons learned through experimentation, they will deliver short-term wins and successfully play the gen AI — and other emerging tech — long game,” Leaver said. The rest of their time is spent creating designs, writing tests, fixing bugs, and meeting with stakeholders. “So

ROI 127

ROI Data-driven Enterprise Experimentation 127

CIO Business Intelligence

JUNE 13, 2024

Proof that even the most rigid of organizations are willing to explore generative AI arrived this week when the US Department of the Air Force (DAF) launched an experimental initiative aimed at Guardians, Airmen, civilian employees, and contractors.

Testing 119

Testing Experimentation Data Processing Modeling 119

CIO Business Intelligence

MARCH 5, 2025

Two years of experimentation may have given rise to several valuable use cases for gen AI , but during the same period, IT leaders have also learned that the new, fast-evolving technology isnt something to jump into blindly. The next thing is to make sure they have an objective way of testing the outcome and measuring success.

Testing 99

Testing Measurement Technology Experimentation 99

CIO Business Intelligence

AUGUST 21, 2024

Adding smarter AI also adds risk, of course. “At The big risk is you take the humans out of the loop when you let these into the wild.” When it comes to security, though, agentic AI is a double-edged sword with too many risks to count, he says. “We That means the projects are evaluated for the amount of risk they involve.

Risk 136

Risk Insurance Cost-Benefit Software 136

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

CIO Business Intelligence

NOVEMBER 7, 2024

This team addresses potential risks, manages AI across the company, provides guidance, implements necessary training, and keeps abreast of emerging regulatory changes. This initiative offers a safe environment for learning and experimentation. We are also testing it with engineering. We have 25% of our employees on Liberty GPT.

Insurance 120

Insurance Experimentation Testing Technology 120

O'Reilly on Data

MARCH 31, 2020

This has serious implications for software testing, versioning, deployment, and other core development processes. The need for an experimental culture implies that machine learning is currently better suited to the consumer space than it is to enterprise companies. And you, as the product manager, are caught between them.

Management 363

Management Machine Learning Experimentation Metrics 363

Corinium

JUNE 6, 2019

Regulations and compliance requirements, especially around pricing, risk selection, etc., Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. Build multiple MVPs to test conceptually and learn from early user feedback.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

OCTOBER 15, 2024

But continuous deployment isn’t always appropriate for your business , stakeholders don’t always understand the costs of implementing robust continuous testing , and end-users don’t always tolerate frequent app deployments during peak usage. CrowdStrike recently made the news about a failed deployment impacting 8.5

Enterprise 143

Enterprise Testing Business Objectives Experimentation 143

Aryng

APRIL 22, 2022

Most managers are good at formulating innovative […] The post How to differentiate the thin line separating innovation and risk in experimentation appeared first on Aryng's Blog. We have seen this as a general trend in start-ups, and we know that it’s an awful feeling!

Experimentation 52

Experimentation Risk Management IT 52

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test. Search and research Microsoft is currently beta testing Bing/Sydney, which is based on GPT-4.

IT 348

IT Modeling Testing Risk 348

CIO Business Intelligence

JULY 12, 2024

They’ve also been using low-code and gen AI to quickly conceive, build, test, and deploy new customer-facing apps and experiences. In a fiercely competitive industry, where CX is critical to differentiation, this approach has enabled them to build and test new innovations about 10 times faster than traditional development.

Experimentation 124

Experimentation Testing Enterprise Strategy 124

CIO Business Intelligence

OCTOBER 3, 2024

From budget allocations to model preferences and testing methodologies, the survey unearths the areas that matter most to large, medium, and small companies, respectively. The complexity and scale of operations in large organizations necessitate robust testing frameworks to mitigate these risks and remain compliant with industry regulations.

Cost-Benefit 129

Cost-Benefit Testing Experimentation Risk 129

CIO Business Intelligence

FEBRUARY 9, 2024

Establish a corporate use policy As I mentioned in an earlier article , a corporate use policy and associated training can help educate employees on some risks and pitfalls of the technology, and provide rules and recommendations to get the most out of the tech, and, therefore, the most business value without putting the organization at risk.

IT 138

IT Experimentation Risk Testing 138

CIO Business Intelligence

AUGUST 16, 2023

But today, Svevia is driving cross-sector digitization projects where new technology for increased safety for road workers and users is tested. Digital alerts Another project deals with slow-moving vehicles, something that increases the risk of accidents on the roads. This leads to environmental benefits and fewer transports.

Risk 98

Risk Cost-Benefit Internet of Things Digital Transformation 98

CIO Business Intelligence

APRIL 12, 2024

Large banking firms are quietly testing AI tools under code names such as as Socrates that could one day make the need to hire thousands of college graduates at these firms obsolete, according to the report. But that’s just the tip of the iceberg for a future of AI organizational disruptions that remain to be seen, according to the firm.

Experimentation 143

Experimentation Reporting Testing Statistics 143

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

CIO Business Intelligence

AUGUST 20, 2024

CIOs have a new opportunity to communicate a gen AI vision for using copilots and improve their collaborative cultures to help accelerate AI adoption while avoiding risks. They must define target outcomes, experiment with many solutions, capture feedback, and seek optimal paths to delivering multiple objectives while minimizing risks.

IT 141

IT Digital Transformation Experimentation Risk 141

CIO Business Intelligence

SEPTEMBER 12, 2024

The familiar narrative illustrates the double-edged sword of “shadow AI”—technologies used to accomplish AI-powered tasks without corporate approval or oversight, bringing quick wins but potentially exposing organizations to significant risks. Establish continuous training emphasizing ethical considerations and potential risks.

Experimentation 111

Experimentation Risk Cost-Benefit Strategy 111

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. Release an updated data viz, then automate a regression test. billion by 2028 , rising at a market growth of 20.3%

Digital Transformation 145

Digital Transformation Data Governance Machine Learning Experimentation 145

Smart Data Collective

OCTOBER 13, 2021

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. It also allows companies to experiment with new concepts and ideas in different ways without relying only on lab tests. Here’s how to stay competitive as technology evolves. Leverage innovation.

Technology 133

Technology Cost-Benefit Experimentation Machine Learning 133

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

CIO Business Intelligence

OCTOBER 21, 2024

“Legacy systems and bureaucratic structures hinder the ability to iterate and experiment rapidly, which is critical for developing and testing innovative solutions. Slow progress frustrates teams and discourages future experimentation.” They’re willing to take risks and be courageous and try new things.

IT 137

IT Experimentation Cost-Benefit Consulting 137

CIO Business Intelligence

JULY 1, 2024

By documenting cases where automated systems misbehave, glitch or jeopardize users, we can better discern problematic patterns and mitigate risks. Real-time monitoring tools are essential, according to Luke Dash, CEO of risk management platform ISMS.online.

Reporting 129

Reporting Risk Management Experimentation Risk 129

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

SEPTEMBER 10, 2024

I built it externally for $50,000 in just five weeks—from concept to market testing. As we navigate this terrain, it’s essential to consider the potential risks and compliance challenges alongside the opportunities for innovation. However, its impact on culture must be carefully considered to maximize benefits and mitigate risks.

IT 122

IT Risk Risk Management Predictive Modeling 122

Domino Data Lab

MAY 15, 2019

Pete indicates, in both his November 2018 and Strata London talks, that ML requires a more experimental approach than traditional software engineering. It is more experimental because it is “an approach that involves learning from data instead of programmatically following a set of human rules.”

Machine Learning 111

Machine Learning Management Experimentation Data Science 111

CIO Business Intelligence

DECEMBER 19, 2023

If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation. And while static application security testing (SAST) was the top-rated tool for usefulness by 82% of respondents, only 28% claim these tools are used on at least 75% of their code base.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

MAY 1, 2024

Pilots can offer value beyond just experimentation, of course. McKinsey reports that industrial design teams using LLM-powered summaries of user research and AI-generated images for ideation and experimentation sometimes see a reduction upward of 70% in product development cycle times.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

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. Artificial Intelligence, Machine Learning

Software 119

Software Risk Experimentation Data Lake 119

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

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

CIO Business Intelligence

APRIL 14, 2023

But just like other emerging technologies, it doesn’t come without significant risks and challenges. According to a recent Salesforce survey of senior IT leaders , 79% of respondents believe the technology has the potential to be a security risk, 73% are concerned it could be biased, and 59% believe its outputs are inaccurate.

Risk 122

Risk Experimentation Marketing Risk Management 122