O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 317

Management Machine Learning Metrics Modeling 317

O'Reilly on Data

MARCH 25, 2025

People have been building data products and machine learning products for the past couple of decades. Now with LLMs, AI, and their inherent flip-floppiness, an array of new issues arises: Nondeterminism : How can we build reliable and consistent software using models that are nondeterministic and unpredictable?

Testing 177

Testing Data-driven Software Measurement 177

CIO Business Intelligence

AUGUST 30, 2024

As an IT leader, deciding what models and applications to run, as well as how and where, are critical decisions. History suggests hyperscalers, which give away basic LLMs while licensing subscriptions for more powerful models with enterprise-grade features, will find more ways to pass along the immense costs of their buildouts to businesses.

Uncertainty 122

Uncertainty Marketing Cost-Benefit Risk 122

O'Reilly on Data

SEPTEMBER 15, 2020

It also helps companies learn how to translate existing AI capabilities into solving specific real-world problems and use cases. In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical competence results in reduced risk and uncertainty.

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

Jedox

APRIL 16, 2020

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

Uncertainty 94

Uncertainty Management Forecasting Visualization 94

CIO Business Intelligence

NOVEMBER 1, 2024

One of the firm’s recent reports, “Political Risks of 2024,” for instance, highlights AI’s capacity for misinformation and disinformation in electoral politics, something every client must weather to navigate their business through uncertainty, especially given the possibility of “electoral violence.” “The

IT 122

IT Insurance Consulting Risk 122

O'Reilly on Data

SEPTEMBER 15, 2021

There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Economic uncertainty caused by the pandemic may be responsible for the declines in compensation. Would your job still be there in a year? Salaries by Tool and Platform.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

CIO Business Intelligence

NOVEMBER 1, 2024

One of the firm’s recent reports, “Political Risks of 2024,” for instance, highlights AI’s capacity for misinformation and disinformation in electoral politics, something every client must weather to navigate their business through uncertainty, especially given the possibility of “electoral violence.” “The

IT 105

IT Insurance Consulting Risk 105

Rocket-Powered Data Science

MAY 21, 2024

Another example is Pure Storage’s FlashBlade ® which was invented to help companies handle the rapidly increasing amount of unstructured data coming into greater use, as required in the training of multi-modal AI models. In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g.,

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

Rocket-Powered Data Science

JULY 19, 2023

The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage. One could say that sentinel analytics is more like unsupervised machine learning, while precursor analytics is more like supervised machine learning.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

CIO Business Intelligence

JUNE 7, 2024

based company, which claims to be the top-ranked supplier of renewable energy sales to corporations, turned to machine learning to help forecast renewable asset output, while establishing an automation framework for streamlining the company’s operations in servicing the renewable energy market. To achieve that, the Arlington, Va.-based

Forecasting 128

Forecasting IT Machine Learning Modeling 128

CIO Business Intelligence

JULY 23, 2024

It’s, ‘We’ve seen the power of OpenAI—tell me how we’re going to be using large language models in order to transform our business.’” Gen AI can still hallucinate, even if tuned, creating a level of uncertainty when more traditional tools would be more consistent.

Uncertainty 131

Uncertainty Machine Learning Business Intelligence Marketing 131

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. While calibration seems like a straightforward and perhaps trivial property, miscalibrated models are actually quite common. Why calibration matters What are the consequences of miscalibrated models?

Modeling 122

Modeling IT Metrics Testing 122

O'Reilly on Data

FEBRUARY 11, 2020

The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Almost half (48%) of respondents say they use data analysis, machine learning, or AI tools to address data quality issues. Key survey results: The C-suite is engaged with data quality.

Data Quality 363

Data Quality Metadata Data Governance Publishing 363

DataRobot

AUGUST 5, 2021

AI and Uncertainty. Some people react to the uncertainty with fear and suspicion. Recently published research addressed the question of “ When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making.”. People are unsure about AI because it’s new. AI you can trust.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

Jedox

APRIL 16, 2020

Dean Boyer as a guest to the Jedox Blog for our series on “Managing Uncertainty” Mr. Boyer is a Director of Technology Services at Marks Paneth LLP, a premier accounting firm based in the United States. He shares his expertise on how an EPM solution supports managing economic uncertainty, particularly in times of crisis.

Uncertainty 52

Uncertainty Management Forecasting Visualization 52

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS supports the management, operations, and planning levels of an organization in making better decisions by assessing the significance of uncertainties and the tradeoffs involved in making one decision over another. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes.

Data mining 144

Data mining Data-driven Statistics OLAP 144

Smart Data Collective

APRIL 18, 2019

Everyone wants to leverage machine learning, behavior analytics, and AI so IT teams can “up the ante” against attackers. The reality is that “AI solutions” today are based more in machine learning and behavior analytics , which does NOT equate to higher levels of human intelligence and complex decision making.

Behavioral Analytics 98

Behavioral Analytics Advertising Uncertainty Machine Learning 98

O'Reilly on Data

JULY 20, 2021

When we’re building shared devices with a user model, that model quickly runs into limitations. That model doesn’t fit reality: the identity of a communal device isn’t a single person, but everyone who can interact with it. With enough data, models can be created to “read between the lines” in both helpful and dangerous ways.

Risk 337

Risk Software Interactive Modeling 337

Smart Data Collective

MAY 3, 2021

Big data has played a huge role in the evolution of employment models. 2 Saves time and cost with machine learning. Machine learning has made it a lot easier to save money. New cost-structure models use complex machine learning algorithms to improve efficiency. #3

Big Data 130

Big Data Data mining Cost-Benefit Insurance 130

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

SEPTEMBER 2, 2022

The approach we use is to develop analytical models based on use cases, with a clear definition of business problems and value. So far, we have deployed roughly 71 models with a clear operating income and impact on the business. I imagine these models have a direct impact on the customer experience. Khare: Yes, they do.

Uncertainty 98

Uncertainty Manufacturing Data-driven Business Intelligence 98

CIO Business Intelligence

JANUARY 11, 2024

To get back in front, IT leaders will have to transform lessons learned from 2023 into actionable, adaptable processes, as veteran technology pros have been remarkably consistent in identifying global and economic uncertainties as key challenges for IT leaders to anticipate in 2024 as well.

IT 133

IT Uncertainty Cost-Benefit Strategy 133

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

Domino Data Lab

JUNE 2, 2019

We had data science leaders presenting about lessons learned while leading data science teams, covering key aspects including scalability, being model-driven, being model-informed, and how to shape the company culture effectively. Data science leadership: importance of being model-driven and model-informed.

Data Science 110

Data Science Data-driven Machine Learning Modeling 110

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. Operations.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Cloudera

DECEMBER 3, 2021

Systems should be designed with bias, causality and uncertainty in mind. For example, training an interview screening model using education data often contains gender information. As discussed in this article , model design can also be a source of bias too. Model Drift. System Design. Human Judgement & Oversight.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

CIO Business Intelligence

MARCH 10, 2023

Digital transformation has brought significant adoption of new technology and business models, including cloud solutions, e-commerce platforms, smart devices, and a significantly more distributed workforce. Artificial Intelligence, IT Leadership, Machine Learning

Digital Transformation 143

Digital Transformation Cost-Benefit ROI Risk 143

erwin

AUGUST 13, 2020

Technology Disruption : How do we focus on innovation while leveraging existing technology, including artificial intelligence, machine learning, cloud and robotics? Compliance and Legislation : How do we manage uncertainty around legislative change (e.g., And the platform also supports business process modeling and analysis.

Enterprise 143

Enterprise Cost-Benefit Uncertainty ROI 143

DataKitchen

SEPTEMBER 21, 2023

The uncertainty of not knowing where data issues will crop up next and the tiresome game of ‘who’s to blame’ when pinpointing the failure. Given this, it’s crucial to have in Place meticulous testing protocols for the results of models, visualizations, data delivery mechanisms, and overall data utilization.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

CIO Business Intelligence

JANUARY 9, 2023

Three years ago, IT leaders were squarely focused on how to adopt fledgling AI techniques and approaches into their business models in service of digital transformations that included plans for shifting some workloads to the cloud. How do you future-proof your business in the face of so much uncertainty?

IT 145

IT Uncertainty Cost-Benefit Digital Transformation 145

Andrew White

FEBRUARY 23, 2021

The D&A trends for 2021 covered in this research can help organizations respond to change, uncertainty and the opportunities they bring over the next three years. To deal with unprecedented levels of business complexity and uncertainty, organizations must improve their ability to accelerate accurate and highly contextualized decisions.

Analytics 90

Analytics Uncertainty Machine Learning Modeling 90

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. This helps train the AI model by assigning classes to different entities in an image. The resulting structured data is then used to train a machine learning algorithm.

Machine Learning 93

Machine Learning Metrics Uncertainty Deep Learning 93

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series. This classification is based on the purpose, horizon, update frequency and uncertainty of the forecast. Forecasting at the “push of a button”?

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

Domino Data Lab

MARCH 21, 2023

98% of CDOs and CDAOs say the companies that bring AI and ML solutions to market fastest will be the ones who survive and thrive in the upcoming times of economic uncertainty. In today's economic environment, all organizations need to unlock greater AI value, faster.

Uncertainty 98

Uncertainty Enterprise Marketing Modeling 98

Cloudera

DECEMBER 11, 2020

Insurance and finance are two industries that rely on measuring risk with historical data models. To facilitate risk modeling in this new normal, agility and flexibility is required. Finally, he recommends investment in building out a platform that supports the entire machine learning lifecycle to enable the industrialization of ML. .

Insurance 95

Insurance Digital Transformation Unstructured Data Machine Learning 95