DataRobot Blog

MARCH 8, 2023

Leveraging DataRobot’s JDBC connectors, enterprise teams can work together to train ML models on their data residing in SAP HANA Cloud and SAP Data Warehouse Cloud, as well as have an option to enrich it with data from external data sources.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

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 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

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

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 104

IT Digital Transformation IoT Cost-Benefit 104

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 113

Experimentation Enterprise Deep Learning Modeling 113

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 127

Machine Learning Data Science Experimentation IoT 127

CIO Business Intelligence

MARCH 12, 2024

Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others. Junior developers are reporting the biggest productivity boosts, but this remains an area of active research and experimentation,” Tandon says.

Software 130

Software Experimentation Testing Cost-Benefit 130

Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. This also achieves workload isolation, so we can run mission critical workloads independent from experimental and exploratory ones and nobody steps on anyone’s toes by accident.

Data Warehouse 85

Data Warehouse Experimentation Cost-Benefit Dashboards 85

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 117

Enterprise Experimentation Modeling Data-driven 117

CIO Business Intelligence

JULY 3, 2023

But the rise of large language models (LLMs) is starting to make true knowledge management (KM) a reality. These models can extract meaning from digital data at scale and speed beyond the capabilities of human analysts. Data exists in ever larger silos, but real knowledge still resides in employees.

Management 104

Management Experimentation Modeling Enterprise 104

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. At DataKitchen, we’re trying to give people the tools and best practices to help them succeed with data and keep their job enjoyable and rewarding.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

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 125

Big Data Data Analytics Analytics Predictive Modeling 125

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 95

Unstructured Data Cost-Benefit Experimentation Machine Learning 95

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 104

KPI Measurement Experimentation Finance 104

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

MAY 12, 2022

Most tools offer visual programming interfaces that enable users to drag and drop various icons optimized for data analysis. Drag-and-drop Modeler for creating pipelines, IBM integrations. A high level of automation encourages deploying these models into production to generate a constant stream of insights and predictions.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

Cloudera

OCTOBER 18, 2023

In fact, some of the insights presented in this blog have been assisted by the power of large language models (LLMs), highlighting the synergy between human expertise and AI-driven insights. Portfolio Optimization Analyze a portfolio of investments and identify opportunities to optimize returns while managing risk.

Cost-Benefit 77

Cost-Benefit Testing Machine Learning Optimization 77

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 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

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 78

Metadata Risk Experimentation Dashboards 78

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 89

Cost-Benefit Modeling Manufacturing Interactive 89

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

IBM Big Data Hub

FEBRUARY 1, 2024

Today, more than 130 central banks are actively exploring CBDCs and publishing periodic reports on the functional and non-functional requirements of CBDC platforms, including the evolving architectural considerations and the outcomes of their various CBDC experimentations.

Experimentation 101

Experimentation Modeling Finance Reporting 101

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. Platforms and practices not optimized for AI. This includes capturing of the metadata, tracking provenance and documenting the model lifecycle.

Metadata 102

Metadata Risk Risk Management Experimentation 102

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 113

Enterprise IT Experimentation Unstructured Data 113

CIO Business Intelligence

JUNE 28, 2023

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 103

Digital Transformation Cost-Benefit Informatics Data mining 103

Smart Data Collective

OCTOBER 13, 2022

These patterns could then be used as the basis for additional experimentation by scientists or engineers. Assembly Line Optimization. Assembly line optimization is a process that allows companies to identify and optimize their production processes, from the design phase to the assembly line. Generative Design.

Testing 114

Testing Cost-Benefit Experimentation Optimization 114

Occam's Razor

MAY 22, 2006

This post is a primer on the delightful world of testing and experimentation (A/B, Multivariate, and a new term from me: Experience Testing). Experimentation and testing help us figure out we are wrong, quickly and repeatedly and if you think about it that is a great thing for our customers, and for our employers.

Experimentation 103

Experimentation Testing Optimization Measurement 103

CIO Business Intelligence

NOVEMBER 2, 2023

“Awareness of FinOps practices and the maturity of software that can automate cloud optimization activities have helped enterprises get a better understanding of key cost drivers,” McCarthy says, referring to the practice of blending finance and cloud operations to optimize cloud spend. It depends on what business model you’re in.

Strategy 140

Strategy Data Processing Experimentation Optimization 140

CIO Business Intelligence

OCTOBER 1, 2022

The digital transformation of P&G’s manufacturing platform will enable the company to check product quality in real-time directly on the production line, maximize the resiliency of equipment while avoiding waste, and optimize the use of energy and water in manufacturing plants. Data and AI as digital fundamentals.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

DataRobot

MARCH 10, 2021

Set the goal to be achieved or optimized. Deploy the machine learning model into production. The experimenters simulated experiences in online travel and online dating, varying the time people waited for a search result. Fit pattern-matching algorithms. Humans and AI Best Practices.

Experimentation 145

Experimentation Machine Learning Key Performance Indicator Reporting 145

CIO Business Intelligence

MAY 8, 2023

So it launched a collaboration with Chemical Abstract Services (CAS), a division of the American Chemistry Society, to leverage CAS SciFinder, which, unlike generic search engines, is optimized for searching for chemical molecules from an electronic catalog of more than 200 million compounds.

Manufacturing 94

Manufacturing Experimentation Digital Transformation Technology 94

CIO Business Intelligence

DECEMBER 29, 2023

Adaptability and useability of AI tools For CIOs, 2023 was the year of cautious experimentation for AI tools. To effectively address this priority, organizations must focus on developing and executing comprehensive strategies that encompass several key aspects, such as data classification, security, and resource optimization.”

Cost-Benefit 139

Cost-Benefit Digital Transformation Consulting Strategy 139

Cloudera

SEPTEMBER 17, 2020

A large oil and gas company was suffering over not being able to offer users an easy and fast way to access the data needed to fuel their experimentation. To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

Cloudera

APRIL 9, 2021

Specifically, we’ll focus on training Machine Learning (ML) models to forecast ECC part production demand across all of its factories. This integration is key in assuring that models evolve with the data – to avoid, for example, model drift. model packaging, deployment and serving. model monitoring.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

CIO Business Intelligence

MARCH 10, 2022

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.”

Sales 128

Sales Testing Experimentation Data Processing 128

CIO Business Intelligence

OCTOBER 18, 2023

Of roughly 2,500 CIOs surveyed recently by Gartner, 9% say they have already deployed gen AI applications, and a staggering 55% say they will deploy large language models (LLMs) in production by the end of 2025. in concert with Microsoft’s AI-optimized Azure platform. John Spottiswood, COO of Jerry, a Palo Alto, Calif.-based

Risk 141

Risk Manufacturing Enterprise Technology 141

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. One instance of how that exploration led to real business benefits was with the application of machine learning to predict optimal product formulation using a set of desired consumer benefits. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133