Cloudera

NOVEMBER 19, 2021

We recognise that experimentation is an important component of any enterprise machine learning practice. But, we also know that experimentation alone doesn’t yield business value. Organizations need to usher their ML models out of the lab (i.e., Organizations must think about an ML model in terms of its entire life cycle.

Machine Learning 119

Machine Learning Modeling Experimentation IT 119

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

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. How Model Observability Provides a 360° View of Models in Production. Read the blog. Read the blog.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

CIO Business Intelligence

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. Over time, using machine learning and AI, CBRE has managed to reduce manual lease processing times by 25% and cut positive false alarms in managed commercial facilities by 65%. Let’s start with the models. And those experiments have paid off.

Experimentation 125

Experimentation Strategy Machine Learning Interactive 125

Decision Management Solutions

DECEMBER 17, 2021

In the recent McKinsey article discussing designing next-generation credit-decisioning models they outlined four best practices for automated credit-decisioning models for banks as they continue their digital transformations. Digital lending based on high-performance credit-decisioning models, says McKinsey, lead to: Increased revenue.

Modeling 52

Modeling Experimentation Visualization Risk 52

DataRobot Blog

MARCH 8, 2023

Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes. So in order to get maximum value from AI, it needs to build machine learning models that are unique to each of its business usecase.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

CIO Business Intelligence

MAY 23, 2022

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. The cloud is great for experimentation when data sets are smaller and model complexity is light. Potential headaches of DIY on-prem infrastructure.

Experimentation 130

Experimentation Cost-Benefit Data Lake Data Science 130

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

CIO Business Intelligence

JANUARY 19, 2024

Data science certifications give you an opportunity to not only develop skills that are hard to find in your desired industry, but also validate your data science know-how so recruiters and hiring managers know what they get if they hire you. and SAS Text Analytics, Time Series, Experimentation, and Optimization.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

CIO Business Intelligence

FEBRUARY 16, 2024

ADP’s aggressive digital transformation has not only cut costs and enabled more innovation but, most importantly, it has facilitated the payroll administrator’s evolution into a human capital management (HCM) service provider, which provides services to its customers from “hire to retire,” Nagrath says.

Digital Transformation 114

Digital Transformation Experimentation Cost-Benefit Machine Learning 114

O'Reilly on Data

JANUARY 11, 2022

This trend started with the gigantic language model GPT-3. This may encourage the creation of more large-scale models; it might also drive a wedge between academic and industrial researchers. What does “reproducibility” mean if the model is so large that it’s impossible to reproduce experimental results?

Experimentation 297

Experimentation Modeling Strategy Machine Learning 297

CIO Business Intelligence

APRIL 29, 2024

They need to have a culture of experimentation.” The dotcom bubble, for example, went from great hype to cynicism after the bubble burst, then to proof of viable online business models, he notes. Artificial Intelligence, Staff Management CIOs should be “change agents” who “embrace the art of the possible,” he says.

Experimentation 123

Experimentation Forecasting Risk Consulting 123

Domino Data Lab

SEPTEMBER 10, 2020

Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent features for models, not to mention many cycles of training, tuning, and tweaking models so they’re performant. This means many projects get stuck in endless research and experimentation.

Modeling 101

Modeling IT Data Science Experimentation 101

CIO Business Intelligence

JANUARY 9, 2024

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 113

Enterprise Experimentation Modeling Data-driven 113

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

Experimentation 79

Experimentation Modeling Deep Learning Data-driven 79

CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. If CIOs don’t improve conversions from pilot to production, they may find their investors losing patience in the process and culture of experimentation.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

CIO Business Intelligence

NOVEMBER 21, 2023

But for a select few, the deeper challenges of departmental technologies being funded, procured, and managed without IT involvement are the missed opportunities to better engage and fulfill departmental technology needs. That’s not to downplay the inherent risks of shadow IT.

IT 134

IT Risk Cost-Benefit Risk Management 134

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. Five years later, transformer architecture has evolved to create powerful models such as ChatGPT. Meanwhile, however, many other labs have been developing their own generative AI models.

Experimentation 112

Experimentation Enterprise Deep Learning Modeling 112

CIO Business Intelligence

FEBRUARY 21, 2024

So students should learn about how to use the technology, and how to manage teams that use the tools — especially engineering teams. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We We’ve done a lot of experimentation on these adaptive tools that use AI,” says Ventimiglia.

Recreation/Entertainment 130

Recreation/Entertainment Experimentation Modeling Data-driven 130

DataKitchen

DECEMBER 1, 2022

We want them to be able to focus on the things that move the needle, like getting models in production, understanding their customers better, or making decisions faster. We’re focused on removing the complexity around managing data and making sure data drives value at every step of the process.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

CIO Business Intelligence

MARCH 12, 2024

Software and coding development remain a high-value area for experimentation, in addition to content development and knowledge management, in an effort to boost operational efficiencies,” he says. We had to build a lot of experimental and testing frameworks to continuously evaluate gen AI.”

Software 130

Software Experimentation Testing Cost-Benefit 130

CIO Business Intelligence

NOVEMBER 7, 2022

A developing playbook of best practices for data science teams covers the development process and technologies for building and testing machine learning models. CIOs and CDOs should lead ModelOps and oversee the lifecycle Leaders can review and address issues if the data science teams struggle to develop models.

Machine Learning 128

Machine Learning Data Science Experimentation IoT 128

Domino Data Lab

NOVEMBER 14, 2019

Model interpretability continues to spark public discourse among industry. We have covered model interpretability previously, including a proposed definition of machine learning (ML) interpretability. Yet there are tradeoffs to consider when selecting a model. Errors like these may occur when the model is being constructed.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Test data management and other functions provided ‘as a service’ . The center of excellence (COE) model leverages the DataOps team to solve real-world challenges.

Metrics 243

Metrics Experimentation Measurement Testing 243

IBM Big Data Hub

MAY 9, 2023

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation to become business critical for many organizations. Success in delivering scalable enterprise AI necessitates the use of tools and processes that are specifically made for building, deploying, monitoring and retraining AI models.

Metadata 75

Metadata Risk Experimentation Dashboards 75

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications. The impact of these investments will become evident in the coming years.

Unstructured Data 94

Unstructured Data Cost-Benefit Experimentation Machine Learning 94

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They can also transform the data, create data models, visualize data, and share assets by using Power BI.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

DataRobot Blog

NOVEMBER 15, 2022

A packed keynote session showed how repeatable workflows and flexible technology get more models into production. Our in-booth theater attracted a crowd in Singapore with practical workshops, including Using AI & Time Series Models to Improve Demand Forecasting and a technical demonstration of the DataRobot AI Cloud platform.

Big Data 52

Big Data Experimentation Data-driven Machine Learning 52

IBM Big Data Hub

OCTOBER 4, 2022

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Multiple unsupported tools for building and deploying models. Challenges around managing risk. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle.

Metadata 101

Metadata Risk Risk Management Experimentation 101

IBM Big Data Hub

MARCH 4, 2024

Figure 2: ROI potential by transforming into an AI+ enterprise Organizations with high data maturity that embed an AI+ transformation model into the enterprise fabric and culture can generate up to 2.6 Consider the following: Do you need a public foundation model? times higher ROI. Should you build your own? If so, where will it run?

Enterprise 104

Enterprise ROI Risk Strategy 104

CIO Business Intelligence

MARCH 7, 2023

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

Enterprise 115

Enterprise IT Experimentation Unstructured Data 115

CIO Business Intelligence

APRIL 12, 2024

As part of the rollout, each store is upgraded with an edge computing solution that leverages a container solution for point-of-sale devices, the management of security cameras, AI voice communications, and AI models with computer vision.

Experimentation 100

Experimentation Sales Digital Transformation Metrics 100

CIO Business Intelligence

FEBRUARY 7, 2024

Stephen Franchetti, CIO of Samsara, a fleet management SaaS provider that went public in 2021, believes the only way to optimize your AI strategy (or any emerging technology strategy, in fact) is with a bottoms-up approach. We’ve seen an ongoing iteration of experimentation with a number of promising pilots in production,” he says.

KPI 95

KPI Measurement Experimentation Finance 95

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions.

Deep Learning 69

Deep Learning Experimentation Machine Learning Risk 69

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 101

IT Digital Transformation IoT Cost-Benefit 101

CIO Business Intelligence

JUNE 16, 2022

Any enterprise data management strategy has to begin with addressing the 800-pound gorilla in the corner: the “innovation gap” that exists between IT and business teams. Analysts and data scientists need flexibility when working with data; experimentation fuels the development of analytics and machine learning models.

IT 128

IT Experimentation IoT Data-driven 128

CIO Business Intelligence

AUGUST 2, 2023

Interestingly, non-IT leaders were more likely to report actively using generative AI (73%) than IT leaders (59%), suggesting there’s plenty of experimentation going on beyond the purview of the IT department. Other respondents were managers, directors, or VPs.

Enterprise 96

Enterprise Experimentation Manufacturing Risk 96