CIO Business Intelligence

FEBRUARY 14, 2024

That’s not just about the cost of preparing a larger data set than you need, which takes expertise that’s still uncommon and commands a high salary, but also what you’re teaching the model. But the usual laundry list of priorities for IT hasn’t gone away.

IT 142

IT Metadata Data-driven Management 142

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

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. Identifying the problem. The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. The worst case scenario is when a business doesn’t have any metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

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. That’s incredibly powerful.” The second is for project staffing.

Enterprise 109

Enterprise IT Experimentation Unstructured Data 109

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.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

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

JUNE 16, 2022

Analysts and data scientists need flexibility when working with data; experimentation fuels the development of analytics and machine learning models. If data is difficult to work with, experimentation slows down, and consequently, so does innovation. Complexity is the enemy of innovation. Data i nnovation in lines of business.

IT 121

IT Experimentation IoT Data-driven 121

O'Reilly on Data

APRIL 4, 2024

The race to the top is no longer driven by who has the best product or the best business model, but by who has the blessing of the venture capitalists with the deepest pockets—a blessing that will allow them to acquire the most customers the most quickly, often by providing services below cost. Friedrich A. I disagree.

Marketing 153

Marketing Modeling Finance Experimentation 153

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. Learn how to leverage Google BigQuery large datasets for large scale Time Series forecasting models in the DataRobot AI platform.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

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

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? Or it might not.

Experimentation 296

Experimentation Modeling Strategy Machine Learning 296

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. Let’s start with the models. And those experiments have paid off.

Experimentation 118

Experimentation Strategy Machine Learning Interactive 118

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

CIO Business Intelligence

JULY 27, 2023

With the ability to instantaneously ingest reams of data using large language models (LLMs), generative AI technologies such as OpenAI’s ChatGPT and Google’s Bard can produce reports, contracts, and application code far surpassing earlier technologies in speed, accuracy, and thoroughness. There is a fear of missing out.

IT 87

IT Insurance Strategy Risk 87

DataRobot

JUNE 17, 2021

At the time, I had a small following of people interested in using Eureqa to derive mathematical formulas and models. Traditionally, science has advanced in many cases by having brilliant researchers compete different hypotheses to explain experimental data, and then design experiments to measure which is correct. So What is Eureqa?

Modeling 52

Modeling Experimentation Machine Learning Measurement 52

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

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 125

Experimentation Cost-Benefit Data Lake Data Science 125

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more. and SAS Text Analytics, Time Series, Experimentation, and Optimization.

Data Science 122

Data Science Machine Learning Predictive Modeling Experimentation 122

Analytics Vidhya

APRIL 14, 2023

Recently, researchers have shown that OpenAI’s generative AI model, GPT-4, has the capability to do scientific research all on its own! The model can design, […] The post GPT-4 Capable of Doing Autonomous Scientific Research appeared first on Analytics Vidhya.

Finance 300

Finance Modeling Analytics Experimentation 300

CIO Business Intelligence

FEBRUARY 16, 2024

For most organizations, a shift to the cloud brings scalability, access to innovative tools, and the possibility of cost savings. For payroll services company ADP, it has paved the way to becoming a SaaS provider capable of taking on big names in enterprise software. An early partner of Amazon, the Roseburg, N.J.-based

Digital Transformation 106

Digital Transformation Experimentation Cost-Benefit Machine Learning 106

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. Junior developers are reporting the biggest productivity boosts, but this remains an area of active research and experimentation,” Tandon says.

Software 126

Software Experimentation Testing Cost-Benefit 126

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. You’re responsible for the design, the product-market fit, and ultimately for getting the product out the door.

Management 332

Management Machine Learning Experimentation Metrics 332

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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 103

Experimentation Enterprise Deep Learning Modeling 103

Dataiku

MAY 23, 2023

Once a data science project has progressed through the stages of data cleaning and preparation, analysis and experimentation, modeling, testing, and evaluation, it reaches a critical point.

Data Science 52

Data Science Experimentation Machine Learning Testing 52

O'Reilly on Data

SEPTEMBER 8, 2020

The programmer could then continue by filling in the actual code, possibly with extensive code completion (and yes, based on a model trained on all the code in GitHub or whatever). Most AI systems we’ve seen envision AI as an oracle: you give it the input, it pops out the answer. That level was the real gold.

Experimentation 297

Experimentation Interactive Modeling Software 297

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, Bin Yu, W. “This has led to considerable confusion about the notion of interpretability. ” and advocate.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

Cloudera

JULY 27, 2021

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype.

Data Science 113

Data Science Enterprise Experimentation Machine Learning 113

Dataiku

MARCH 25, 2024

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. Intrigued, you type in a question about the location, expecting a response from a fellow user.

Visualization 132

Visualization Modeling Experimentation Testing 132

Ontotext

NOVEMBER 2, 2023

However, it will take effort to formalize a shared semantic model that can be mapped to data assets, and turn unstructured data into a format that can be mined for insight. And while there is a great deal of experimentation underway, most organizations have only scratched the surface in a use-case-by-use-case fashion.

IT 69

IT Cost-Benefit Data-driven Technology 69

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. billion in funding rounds.

Management 101

Management Experimentation Modeling Enterprise 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 103

Enterprise Experimentation Modeling Data-driven 103

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. The exam consists of 65 multiple-choice or multiple-response questions, which the candidate has 180 minutes to complete.

Big Data 121

Big Data Data Analytics Analytics Predictive Modeling 121

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

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

APRIL 12, 2024

Tractor Supply Co. prides itself in delivering “legendary” customer service, and it has turned to artificial intelligence to assist with that goal. The rural lifestyle retailer, with more than 2,200 stores across the US, caters to the needs of rural residents with a wide variety of products on its shelves.

Experimentation 90

Experimentation Sales Digital Transformation Metrics 90

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 124

Machine Learning Data Science Experimentation IoT 124