IBM Big Data Hub

MARCH 4, 2024

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Otherwise, the risks become too significant.

Enterprise 109

Enterprise ROI Risk Strategy 109

IBM Big Data Hub

DECEMBER 4, 2023

And the abundance of data available for training models has opened up vast possibilities for experimentation and learning. Ensuring that generative AI models adhere to ethical guidelines and that adequate processes are in place to mitigate risks and biases is essential.

Experimentation 67

Experimentation Modeling Metrics Machine Learning 67

CIO Business Intelligence

FEBRUARY 21, 2024

We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We We now use AI to help faculty understand some of those risk factors,” says Fozard. We’ve done a lot of experimentation on these adaptive tools that use AI,” says Ventimiglia.

Recreation/Entertainment 135

Recreation/Entertainment Experimentation Modeling Data-driven 135

CIO Business Intelligence

NOVEMBER 13, 2023

Foster a culture of innovation: Digital transformation requires innovation and experimentation, and thus a culture for embracing new technologies and ideas. IT leaders help facilitate a shift in organizational mindset toward a willingness to take risks and learn from failures.

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

DataRobot Blog

OCTOBER 18, 2022

Model Observability – the ability to track key health and service metrics for models in production – remains a top priority for AI-enabled organizations. Learn more about the DataRobot AI Cloud and the ability to accelerate your experimentation and production timelines. DataRobot Booth at Big Data & AI Toronto 2022.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Information governance enables enterprises to achieve strategic goals, mitigate risk, and reduce costs. Conversations suggest that AI is already transforming most major industries.

Advertising 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

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 356

Enterprise Modeling Risk Manufacturing 356

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. Measure user adoption and engagement metrics to not just understand products take-up, but also to enhance the overall product propositions.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Sisense

JANUARY 21, 2020

One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. A new drug promising to reduce the risk of heart attack was tested with two groups. When the data is combined, it seems that the drug reduces the risk of getting a heart attack.

Testing 104

Testing Risk Data-driven Statistics 104

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

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 27, 2022

Tyson: You’re coming up to two years since you added Sentry’s ability to monitor for performance which has some pretty fine-grained metrics in terms of identifying where bottlenecks are located in code. A lot of the current approaches feel very experimental and are tough to see as maintainable, so there’s certainly still room for growth here.

Software 115

Software Experimentation Testing Marketing 115

AWS Big Data

MAY 2, 2023

If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. Removal of experimental Smart Sensors. Let’s demonstrate this with a code example. Apache Airflow v2.4.3

Testing 97

Testing Experimentation Management Metadata 97

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. Now nearly half of code suggestions are accepted.

Cost-Benefit 143

Cost-Benefit Metrics Insurance Measurement 143

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. As copilot technology capabilities are changing rapidly, leaders should frequently identify metrics and evaluate strategies.

Cost-Benefit 125

Cost-Benefit Advertising Experimentation Software 125

DataRobot Blog

MARCH 16, 2023

Why model-driven AI falls short of delivering value Teams that just focus model performance using model-centric and data-centric ML risk missing the big picture business context. New Snowflake integrations and the SAP joint solution have tightened the data to experimentation to deployment loop.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

CIO Business Intelligence

JULY 11, 2023

For example, a good result in a single clinical trial may be enough to consider an experimental treatment or follow-on trial but not enough to change the standard of care for all patients with a specific disease. The company must ensure that their sensitive information remains confidential and protected from potential competitors.

Modeling 95

Modeling Testing Experimentation Risk Management 95

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 Cost-Benefit 150

Occam's Razor

JULY 6, 2016

Yes, I worry that Analysts, and Marketers, are spending too much time with their head buried in custom reports and advance segments and smart calculated metrics and strategic or tactical dashboards. I've always thought they pushed the edge and took risks. They are all things I love and have repeatedly asked you to care for.

Testing 86

Testing Marketing Experimentation Cost-Benefit 86

DataRobot Blog

SEPTEMBER 30, 2022

By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Adoption of AI/ML is maturing from experimentation to deployment. How do you track the integrity of a machine learning model in production? Model Observability can help.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

CIO Business Intelligence

FEBRUARY 3, 2023

Cybersecurity threats require business language lift This heightened business demand, along with the Royal moniker, does, however, come with risks. Three of the team—two cyber engineers and a risk manager—were hired directly from the University in their third years, prior to graduation. “We

IT 52

IT Experimentation Scorecard Digital Transformation 52

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Another pattern that I’ve seen in good PMs is that they’re very metric-driven.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

APRIL 18, 2022

They run the risk of miscommunication and misaligned business, technology, and operational strategy across the CXO team. They also advise communicating the dashboard’s value consistently since that will drive effective dashboard use, both to increase adoption and to improve company performance on key dashboard metrics, the brief says.

Digital Transformation 145

Digital Transformation Dashboards Cost-Benefit Consulting 145

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. The ability to measure results (risk-reducing evidence). Ensure a culture that supports a steady process of learning and experimentation.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. We use performance metrics such as bias and mean squared error for the estimation of $delta$, our causal estimand of interest, defined as the average effect of treatment on the treated.

Statistics 44

Statistics Optimization Modeling Experimentation 44

AWS Big Data

JULY 20, 2023

Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate. Orca monitored the cluster status and resource usage of Amazon EMR by utilizing the available metrics through Amazon CloudWatch.

Data Lake 83

Data Lake Analytics Snapshot Optimization 83

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 112

Testing Experimentation Risk Optimization 112

Domino Data Lab

JUNE 10, 2020

It establishes a consistent approach for monitoring across teams and models so you can break down departmental silos, eliminate inconsistent or infrequent monitoring practices, and establish a standard for model health metrics across your organization. In Domino 4.2

Data Science 82

Data Science Enterprise Experimentation Modeling 82

Occam's Razor

MARCH 23, 2010

Because every tool uses its own sweet metrics definitions, cookie rules, session start and end rules and so much more. Yet case studies in some sense reduced risk, even if they were simply over blown marketing fluff written by the vendor. There is such little risk to actually trying. Likely not. Omniture cannot save you.

Analytics 118

Analytics Consulting Metrics Experimentation 118

The Unofficial Google Data Science Blog

MAY 31, 2016

A geo experiment is an experiment where the experimental units are defined by geographic regions. This means it is possible to specify exactly in which geos an ad campaign will be served – and to observe the ad spend and the response metric at the geo level. They are non-overlapping geo-targetable regions. by turning campaigns off).

Advertising 42

Advertising Testing Sales Statistics 42

Cloudera

JUNE 6, 2019

In this case, an individual with different types of workloads may have access to multiple clusters; the admin trades increased risk of a noisy neighbor for better infrastructure efficiency. 3) By workload priority. A third strategy splits clusters based on the overall priority of the workloads running on those clusters.

Metadata 88

Metadata Data Lake Optimization Strategy 88

Domino Data Lab

MAY 8, 2019

That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Given how so much of IT gets driven by concerns about risks and costs, in practice auditability tops the list for many business stakeholders. Ergo, less interpretable.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

JANUARY 9, 2012

If you are doing lame stuff, why try harder in an analytics context by asking for Economic Value or Visitor Loyalty or Conversation Rate or a thousand other super powerful and insightful metrics ? We don't take risk and try things, imaginative (possibly glorious) things, because we believe the price of failure is so high.

Marketing 140

Marketing B2B Measurement Risk 140

Occam's Razor

OCTOBER 23, 2006

Start with measuring these Outcomes metrics (revenue, leads, profit margins, improved product mix, number of new customers etc). Get competitive data (we are at x% of zz metric and our competition is at x+9% of zz metric). Great for a couple months and then you lose the audience. 6 Reporting is not Analysis. Your Choice? .

Data-driven 117

Data-driven Metrics KPI Reporting 117

Domino Data Lab

AUGUST 26, 2019

To support the iterative and experimental nature of industry work, Domino reached out to Addison-Wesley Professional (AWP) for appropriate permissions to excerpt the “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. algorithm leaf_size metric metric_params n_jobs n_neighbors p weights.

Testing 79

Testing Modeling Machine Learning Metrics 79

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise. The DataRobot AI Platform is the next generation of AI.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59