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. Encourage and reward a Culture of Experimentation that learns from failure, “ Test, or get fired!

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines. But what kind?

Enterprise 315

Enterprise Deep Learning Data Governance Risk 315

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 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. And you, as the product manager, are caught between them.

Management 338

Management Machine Learning Experimentation Metrics 338

Dataiku

OCTOBER 2, 2019

It’s probably safe to say that for at least some of those explorers, the prospect of risk when it comes to data and AI projects is paralyzing, causing them to stay in a phase of experimentation.

Risk 14

Risk Experimentation Management Machine Learning 14

CIO Business Intelligence

DECEMBER 4, 2024

At AWS re:Invent Tuesday, JPMorgan Chase Global CIO Lori Beer detailed the evolving partnership between the financial services giant and AWS, which finds JPMorgan pushing the AWS SageMaker machine learning platform and AWS Bedrock generative AI platform beyond experimentation into production applications.

Experimentation 122

Experimentation Risk Marketing Enterprise 122

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. When we asked respondents with mature practices what risks they checked for, 71% said “unexpected outcomes or predictions.” Risks checked for during development. Bottlenecks to AI adoption.

Enterprise 358

Enterprise Risk Modeling Manufacturing 358

DataRobot Blog

DECEMBER 6, 2022

Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results. Taking a Multi-Tiered Approach to Model Risk Management. Data scientists are in demand: the U.S. Explore these 10 popular blogs that help data scientists drive better data decisions.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

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 299

Advertising Cost-Benefit ROI Machine Learning 299

CIO Business Intelligence

JULY 5, 2024

So, to maximize the ROI of gen AI efforts and investments, it’s important to move from ad-hoc experimentation to a more purposeful strategy and systematic approach to implementation. For AI and other areas, a corporate use policy can help educate users to potential risk areas, and hence manage risk, while still encouraging innovation.

ROI 124

ROI Experimentation Risk Strategy 124

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. 4 Big Bets, Low Risks, Happy Customers. You have just launched something risky, yet you have controlled the risk by reducing exposure of the risky idea. You can control the risk you want to take. # But remember you can control risk.

Testing 113

Testing Experimentation Risk Optimization 113

CIO Business Intelligence

AUGUST 16, 2023

Digital alerts Another project deals with slow-moving vehicles, something that increases the risk of accidents on the roads. Not for experiments For a company like Svevia, there’s no room for experimentation, underlines Wester. “We Since the route optimization came into place, fewer emptyings are required, he notes.

Risk 98

Risk Cost-Benefit Digital Transformation Internet of Things 98

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

Smart Data Collective

MAY 22, 2022

The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience. With AI, the risk score for a device doesn’t depend on individual indicators. Predicting If a Device Is at Risk. Therefore, the risk score is always being adjusted accordingly.

Data-driven 140

Data-driven Risk Experimentation IT 140

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

NOVEMBER 17, 2021

For many years, AI was an experimental risk for companies. Today, AI is not a brand new concept and most enterprises have at least explored AI implementation. As of 2020, 68% of enterprises had used AI, having already adopted AI applications or introduced AI on some level into their business processes.

ROI 110

ROI Enterprise Experimentation Risk 110

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 Strategy Data-driven 115

CIO Business Intelligence

OCTOBER 15, 2024

Recommendation : CIOs should adopt a risk-informed approach, understanding business, customer, and employee impacts before setting application-specific continuous deployment strategies. Shortchanging end-user and developer experiences Many DevOps practices focus on automation, such as CI/CD and infrastructure as code.

Enterprise 143

Enterprise Testing Business Objectives Experimentation 143

DataRobot Blog

JANUARY 10, 2023

Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Clinics and hospitals like Phoenix Children’s use AI to predict which patients are at risk of contracting an illness so that they can then prescribe medication and treatment accordingly. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

CIO Business Intelligence

JUNE 24, 2024

But in the short run, we risk building an astonishing, awe-inspiring technology that few use. If we remain solely focused on just building better and better AI capabilities, we risk creating an amazing technology without clear applications, public acceptance, or concrete returns for businesses.

Risk 141

Risk Experimentation Enterprise Technology 141

CIO Business Intelligence

NOVEMBER 27, 2024

While in the experimentation phase, speed is a priority, the implementation phase requires more attention to resiliency, availability, and compatibility with other tools. Technology: The workloads a system supports when training models differ from those in the implementation phase.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

CIO Business Intelligence

OCTOBER 24, 2024

The long-term impact is even more worrying — companies risk falling behind competitors who are implementing AI strategically. Rosen sees a lot of experimentation without a clear sense of direction, from companies that don’t have a clear idea of what AI projects will match their business needs. The fear of missing out is real.

IT 138

IT Experimentation Measurement Risk 138

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

APRIL 12, 2024

Right now most organizations tend to be in the experimental phases of using the technology to supplement employee tasks, but that is likely to change, and quickly, experts say. 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

NOVEMBER 11, 2024

Amazon Web Services, Microsoft Azure, and Google Cloud Platform are enabling the massive amount of gen AI experimentation and planned deployment of AI next year, IDC points out. For the global risk advisor and insurance broker that includes use cases for drafting emails and documents, coding, translation, and client research.

ROI 137

ROI Cost-Benefit Risk Experimentation 137

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. Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

CIO Business Intelligence

OCTOBER 9, 2022

However, delay too long, and you also risk giving yourself an insurmountable technological handicap if uptake in your industry suddenly accelerates. The benefits of the experimentation and iterative progression Agile enables are never more apparent than when we’re exploring uncertain and dynamic environments.

Cost-Benefit 142

Cost-Benefit Manufacturing Experimentation Risk 142

CIO Business Intelligence

AUGUST 5, 2024

Data Security, Privacy, and Accuracy: One of the major hurdles to implementing AI in healthcare is the risk of accidental exposure to private health information. To learn more, visit us here.

Experimentation 124

Experimentation Risk Metadata Data-driven 124

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

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. Davé and his team’s achievements in AI are due in large part to creating opportunities for experimentation — and ensuring those experiments align with CBRE’s business strategy. And those experiments have paid off.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130

CIO Business Intelligence

JULY 12, 2024

“Not only does this particular low-code solution make rapid experimentation possible, it also offers orchestration capabilities so we can plug different services in and out very quickly,” says Pacynski. And if it doesn’t work, we have the flexibility to take out a component and put it in something different without any hassle.”

Experimentation 124

Experimentation Testing Enterprise Strategy 124

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 Uncertainty 111

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 Consulting 135

CIO Business Intelligence

JUNE 21, 2024

The AI data center pod will also be used to power MITRE’s federal AI sandbox and testbed experimentation with AI-enabled applications and large language models (LLMs). We took a risk. based research organization into an “AI-native organization” that provides the most efficient, intelligent, and critical data for government agencies.

Experimentation 134

Experimentation Data mining Reporting Data Processing 134

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 3, 2024

The complexity and scale of operations in large organizations necessitate robust testing frameworks to mitigate these risks and remain compliant with industry regulations. Medium companies Medium-sized companies—501 to 5,000 employees—were characterized by agility and a strong focus on GenAI experimentation.

Testing 129

Testing Cost-Benefit Experimentation Risk 129

CIO Business Intelligence

NOVEMBER 19, 2024

This stark contrast between experimentation and execution underscores the difficulties in harnessing AI’s transformative power. Intellectual property risks Failing: GenAI can inadvertently use copyrighted material, leading to legal complications. Of those, just three are considered successful.

Consulting 137

Consulting Cost-Benefit Experimentation Optimization 137