CIO Business Intelligence

MAY 3, 2024

The LLM gives agents the ability to confirm all responses suggested by the model. Gownder, in a blog post last November as UPS was putting its solution into limited production. As a result, UPS is investing in training the model on its corporate data set. For MeRA, UPS started with Microsoft OpenAI LLMs, GPT 3.5 Turbo and GPT4.

Testing 140

Testing Sales Enterprise Digital Transformation 140

Domino Data Lab

JULY 20, 2022

We've blogged before about the importance of model validation, a process that ensures that the model is performing the way it was intended and that it solves the problem it was designed to solve. Enter Deepchecks - an open source Python package for testing and validating machine learning models and data.

Machine Learning 98

Machine Learning Testing Modeling Data Integration 98

IBM Big Data Hub

JANUARY 3, 2024

Most everyone has heard of large language models, or LLMs, since generative AI has entered our daily lexicon through its amazing text and image generating capabilities, and its promise as a revolution in how enterprises handle core business functions. Enter the world of Large Speech Models, or LSMs.

Modeling 110

Modeling Interactive Metrics Testing 110

IBM Big Data Hub

MAY 8, 2024

Process visualization: Convert results into models or develop to collaborate and enrich. Constant evaluation of evolving business needs, coupled with technologies and product features, defines the pathway to market differentiation. Establish a performance baseline. Establish as-is processes. Adjust for unique processes.

Measurement 91

Measurement Technology Visualization Optimization 91

IBM Big Data Hub

OCTOBER 30, 2023

While features and capabilities are important to evaluate, it’s also important to consider pricing to ensure the right solution that will meet your needs. Let’s take a look at some key pricing features to consider when evaluating an APM or observability platform.

Data Processing 80

Data Processing Optimization Modeling IT 80

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. Evaluating the performance of generative AI models ensures that they meet desired standards and can provide reliable outputs.

Experimentation 67

Experimentation Modeling Metrics Machine Learning 67

AWS Big Data

MARCH 27, 2024

For a POC on Amazon Redshift, we recommend a three-phase process of discovery, implementation, and evaluation. It defines through multiple sessions the scope of the POC and the list of tasks that need to be completed and later evaluated. Evaluation phase The evaluation phase is the POC assessment and the final step of the process.

Testing 103

Testing Data Warehouse Metrics Cost-Benefit 103

IBM Big Data Hub

APRIL 8, 2024

Top CHROs are already at work on this challenge, using their comprehensive understanding of the workforce and how to design roles and skills within an operating model to best leverage the strengths of both humans and AI. The CHRO’s primary challenge is to orchestrate the new human plus AI workforce. That’s only the beginning.

Unstructured Data 70

Unstructured Data Testing Strategy Technology 70

IBM Big Data Hub

MAY 10, 2024

For specific tasks like image processing, signal processing or other AI applications, cloud-based GPU vendors may provide a more cost-effective solution through subscription or pay-as-you-go pricing models. GPUs can rapidly process large datasets and greatly decrease time spent training machine learning models.

Deep Learning 99

Deep Learning Cost-Benefit Manufacturing Optimization 99

IBM Big Data Hub

OCTOBER 25, 2023

Here’s how CTOs and CIOs can evaluate their technology and data estates, assess the opportunity and chart a path forward. Evaluating foundation models Selecting the right foundation models up front can help you deliver more accurate and efficient outcomes for your enterprise. Start small, test and scale.

Cost-Benefit 91

Cost-Benefit ROI Modeling Testing 91

DataRobot

NOVEMBER 16, 2021

As we’ve discussed in this blog series, some are already reaping the rewards of AI through increased productivity, cost savings, etc. Organizations do not realize the full benefits of AI because models are not often deployed. MLOps simplifies model deployment by streamlining the processes between modeling and production deployments.

Cost-Benefit 98

Cost-Benefit Machine Learning Modeling Risk 98

IBM Big Data Hub

MAY 1, 2023

This wave of AI is attributable to what are known as foundation models. What are foundation models? As the name suggests, foundation models can be the foundation for many kinds of AI systems. Using machine learning techniques, these models apply information learned about one situation to another situation.

Modeling 101

Modeling Risk Machine Learning Technology 101

IBM Big Data Hub

DECEMBER 16, 2022

Over the last week, millions of people around the world have interacted with OpenAI’s ChatGPT, which represents a significant advance for generative artificial intelligence (AI) and the foundation models that underpin many of these use cases. How can we ensure that these models are being used responsibly?

Uncertainty 119

Uncertainty Metadata Modeling Data Collection 119

Dataiku

AUGUST 19, 2022

In a recent Dataiku Product Days session, we walked through an example of importing MLflow models as Saved Models in Dataiku, but no worries if you prefer a quick rundown written out. In this blog, we will outline the brief introduction to MLflow Saved Models that was covered in the session.

Modeling 59

Modeling Visualization 59

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 85

Data Science Data Analytics Prescriptive Analytics Analytics 85

Cloudera

NOVEMBER 30, 2021

This guest blog was written by Shanice Omare, Research Manager, Vanson Bourne. The maturity model suggests that those with clear strategies and approaches to transform their technologies are ahead of their competitors. The Enterprise Data Maturity Model – Putting resiliency to the test. Their current uses of data and analytics.

Enterprise 74

Enterprise Reporting Data Strategy Strategy 74

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 127

Enterprise Modeling Testing Data-driven 127

IBM Big Data Hub

MAY 18, 2023

This report outlines the combination of traditional decision automation tools with machine learning models and other technologies. It provides a low-code environment where business experts can manage decision automation projects and apply their knowledge to model decisions without extensive coding or deep AI knowledge.

Reporting 96

Reporting Scorecard Predictive Modeling Machine Learning 96

Cloudera

FEBRUARY 11, 2022

However, to understand what Ethical AI is, we need to have at least a basic understanding of ML, ML models and the data science lifecycle and how they are related. This blog post hopes to provide this foundational understanding. Instead, they are learned by training a model on data. What is A Machine Learning Model .

Machine Learning 97

Machine Learning Sales Data Science Modeling 97

DataKitchen

JULY 12, 2023

These tests allow users to customize testing protocols to fit specific business requirements with a “fill in the blank” model, offering a perfect blend of speed and robustness in data testing. DataOps Automation provides robust testing and evaluation processes throughout the ‘last mile’ of the Data Journey.

Data Quality 130

Data Quality Testing Manufacturing Finance 130

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 95

Testing Finance Enterprise Modeling 95

IBM Big Data Hub

MARCH 25, 2024

Many financial services firms will have to re-evaluate a significant portfolio of investments across the stock market. Get tools to accurately assess potential climate impacts The IBM® Environmental Intelligence Suite models 40 years of historical weather patterns. As a result, their market would shrink.

Insurance 97

Insurance Forecasting Risk Risk Management 97

IBM Big Data Hub

MARCH 27, 2024

Programming languages like Java have incompatible object models with today’s database-specific data structures and formats. Consequently, mapping objects to database-specific models, converting data and generating objects for each query result in expensive latencies of up to 100ms or more, even when retrieving data from cache.

Cost-Benefit 104

Cost-Benefit Data Processing Optimization Modeling 104

IBM Big Data Hub

OCTOBER 19, 2023

OpenHarvest sets out to close a digital divide OpenHarvest is an open source platform with a mobile application that expands access to visual agricultural data, delivers specialized recommendations to farmers through AI and climate modeling, and enables better farm and field management. The solution was an SMS text message.

Forecasting 100

Forecasting Consulting Risk Modeling 100

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 89

Metrics Machine Learning Risk Statistics 89

Cloudera

DECEMBER 19, 2023

In fact, most of the public servants I spoke with were predominantly cautious about the current limitations of generative AI, and underscored the need to ensure that models are used responsibly and ethically. As also expected, most had experimented on their own with large language models (LLM) and image generators.

Optimization 91

Optimization Cost-Benefit Unstructured Data Risk 91

CIO Business Intelligence

JUNE 28, 2023

“When you create an app bundle, AppFabric creates the required AWS Identity and Access Management (IAM) role in your AWS account, which is required to send metrics to Amazon CloudWatch and to access AWS resources such as Amazon Simple Storage Service (Amazon S3) and Amazon Kinesis Data Firehose,” AWS wrote in a blog post.

Enterprise 135

Enterprise Modeling Metrics Machine Learning 135

Dataiku

JUNE 1, 2020

To understand the evaluation process described in this blog post, we need to take a step back and understand what a hyperparameter in machine learning is. A hyperparameter is a parameter of the model whose value is set before the learning process begins.

IT 71

IT Machine Learning Optimization Modeling 71

CIO Business Intelligence

OCTOBER 24, 2023

The capabilities of these new generative AI tools, most of which are powered by large language models (LLM), forced every company and employee to rethink how they work. Vector Databases To make use of a Large Language Model, you’re going to need to vectorize your data. For that, you’ll need an embedding model.

Cost-Benefit 126

Cost-Benefit Modeling Data Quality Statistics 126

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines. Here are the key stages: .

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Also, a column in the dataset indicates if each flight had arrived on time or late.

Modeling 92

Modeling Statistics Machine Learning Testing 92

IBM Big Data Hub

APRIL 10, 2023

As AI may inform more and more decisions within HR such as hiring, evaluation and promotion, an organization’s need to respond to new and expanding regulation will increasingly intersect with its need to address ESG standards. It’s becoming critical that organizations should adopt a data architecture that supports AI governance.

Strategy 95

Strategy Data Architecture Cost-Benefit Reporting 95

IBM Big Data Hub

JANUARY 11, 2024

Generative AI can work with other AI models to increase accuracy and performance, such as augmenting images to improve quality evaluation of a computer vision model. With generative AI, there are fewer “misreads” and overall better-quality assessments.

Manufacturing 73

Manufacturing Cost-Benefit Consulting Testing 73

Cloudera

MAY 13, 2021

While the whitepaper lays out and compares different engines, the purpose of this blog post is to define what factors the whitepaper looks at and why each one is important. Streaming model and time support are also functional aspects to consider. Do you need a stream processing engine with a “stateless” or “stateful” streaming model?

Risk 102

Risk Enterprise Metrics Modeling 102

DataRobot

NOVEMBER 29, 2021

This is a three part blog series in partnership with Amazon Web Services describing the essential components to build, govern, and trust AI systems: People , Process and Technology. We’ll focus on evaluating a model for biased behavior, which can occur during the training process or after it has been deployed in a production environment. .

Technology 52

Technology Metrics Predictive Modeling Modeling 52

IBM Big Data Hub

JULY 26, 2023

Instead of relying on the previous year’s budget, ZBB requires you to evaluate and justify every expense from the ground up, justifying its necessity and alignment with strategic goals. The zero-based budgeting process is a strategic budgeting approach that mandates a fresh evaluation of all expenses during each budgeting cycle.

Cost-Benefit 62

Cost-Benefit Optimization Visualization Data-driven 62

Cloudera

DECEMBER 16, 2021

Organizations were evaluated based on their current use of data and analytics, parties championing the use of data and the extent to which data is used across processes, the presence of enterprise data strategies, and the extent to which capabilities relating to an Enterprise Data Cloud have been achieved. . To find out more, click here.

Data Strategy 86

Data Strategy Snapshot Strategy Reporting 86