CIO Business Intelligence

APRIL 11, 2024

I can’t speak for the entire country but I know that the requirement to adopt a distance learning delivery model at the beginning of the pandemic for all levels of education ranging from K-12 to university studies forced a rapid deployment of technological solutions. Education Industry

Technology 105

Technology Digital Transformation Experimentation Testing 105

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

AWS Big Data

JANUARY 9, 2024

Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word. Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Only items that have words the user typed match the query.

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

AWS Big Data

AUGUST 21, 2023

Lexical search looks for words in the documents that appear in the queries. For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

Data Processing 89

Data Processing Experimentation Visualization Metrics 89

CIO Business Intelligence

NOVEMBER 21, 2023

Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions.

IT 137

IT Risk Cost-Benefit Risk Management 137

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

CIO Business Intelligence

APRIL 2, 2024

Joanne Friedman, PhD, CEO, and principal of smart manufacturing at Connektedminds, says orchestrating success in digital transformation requires a symphony of integration across disciplines : “CIOs face the challenge of harmonizing diverse disciplines like design thinking, product management, agile methodologies, and data science experimentation.

Management 140

Management Digital Transformation Testing Experimentation 140

CIO Business Intelligence

MARCH 7, 2023

Vince Kellen understands the well-documented limitations of ChatGPT, DALL-E and other generative AI technologies — that answers may not be truthful, generated images may lack compositional integrity, and outputs may be biased — but he’s moving ahead anyway. And, he says, using generative AI for coding has worked well.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

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 105

Management Experimentation Modeling Enterprise 105

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 84

Experimentation Modeling Deep Learning Data-driven 84

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

CIO Business Intelligence

DECEMBER 7, 2023

Over the last year, generative AI—a form of artificial intelligence that can compose original text, images, computer code, and other content—has gone from experimental curiosity to a tech revolution that could be one of the biggest business disruptors of our generation. Likewise, they realize that human talent will be central to success.

Insurance 89

Insurance Experimentation Finance Data Governance 89

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. Automated documentation generation: Generating documentation is time consuming and tedious.

Cost-Benefit 75

Cost-Benefit Testing Machine Learning Optimization 75

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. Consistent principles guiding the design, development, deployment and monitoring of models are critical in driving responsible, trustworthy AI.

Metadata 103

Metadata Risk Risk Management Experimentation 103

CIO Business Intelligence

APRIL 14, 2023

In fact, it’s likely your organization has a large number of employees currently experimenting with generative AI, and as this activity moves from experimentation to real-life deployment, it’s important to be proactive before unintended consequences happen. For example, will this cover all forms of AI or just generative AI?

Risk 122

Risk Experimentation Marketing Risk Management 122

Smarten

MAY 17, 2023

x, ChatGPT, Google’s Bard chatbot technology, and the AI service, Language Model for Dialogue Applications (LaMDA), among others. Creating Summary Data for Unstructured Documents (PDFs, HTML, Websites, etc.) To leverage the current state of Open AI and GPT, you can look at simple, out-of-the-box potential.

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. A common pattern is that they adopt a three-step model development process: Prepare the initial dataset and leverage automation, including automated feature engineering, to get an accurate baseline model in minutes.

Machine Learning 52

Machine Learning Modeling Experimentation Visualization 52

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. Snap, LexisNexis, and Lonely Planet are also developing and training LLM models, each leveraging their own data stored on AWS. “We

Risk 141

Risk Manufacturing Enterprise Technology 141

CIO Business Intelligence

JUNE 7, 2023

I can’t speak for the entire country but I know that the requirement to adopt a distance learning delivery model at the beginning of the pandemic for all levels of education ranging from K-12 to university studies forced a rapid deployment of technological solutions.

Digital Transformation 105

Digital Transformation Experimentation Technology Testing 105

Domino Data Lab

APRIL 7, 2019

Other use cases may involve returning the most appropriate answer to a question, finding the most relevant documents for a query or classifying the input document itself. A good NLP library will make it easy to both train your own NLP models and integrate with the downstream ML or DL pipeline. Training domain-specific models.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

Insight

MARCH 12, 2020

The AIgent was built with BERT, Google’s state-of-the-art language model. In this article, I will discuss the construction of the AIgent, from data collection to model assembly. To collect these genre tags and other metadata, I took advantage of the well-documented Goodreads API. features) and metadata (i.e.

Modeling 59

Modeling Metadata Publishing Sales 59

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 98

Cost-Benefit Modeling Manufacturing Interactive 98

CIO Business Intelligence

JUNE 28, 2023

Experimentation with a use case driven approach. At least for now, they seem focused on use cases that improve productivity, with compelling opportunities in the areas of sales & marketing, code generation, and document generation. Exploring the art of the possible and identifying top use cases is the name of the game.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

AWS Big Data

MAY 2, 2023

Removal of experimental Smart Sensors. For detailed release documentation with sample code, visit the Apache Airflow v2.4.0 This feature is particularly useful if you want to externally process various files, evaluate multiple machine learning models, or extraneously process a varied amount of data based on a SQL request.

Testing 97

Testing Experimentation Management Metadata 97

CIO Business Intelligence

AUGUST 17, 2023

We’ve been shortlisting and building out potential proof-of-concept options and modelling revenue impact and already taken one concept through our innovation lab and into live production.” It’s made my life easier because it allows me to write documents and make them richer, but if you rely on this beast it can bite you.

Risk 98

Risk Cost-Benefit Strategy Experimentation 98

Domino Data Lab

AUGUST 6, 2021

When you factor in the requirements of a business-critical machine learning model in a working enterprise environment, the old cat-herding meme won’t even get a smile. Develop: includes accessing and preparing data and algorithms, researching and development of models and experimentation. 4 Steps in the DSLC. Assess the Project.

Data Science 75

Data Science Testing Modeling Publishing 75

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 31, 2023

How has, say, ChatGPT hit your business model?” No good guidance yet As CIOs seek to bring control and risk management to technology that’s generating widespread interest and plenty of experimentation, they’re doing so without pre-existing guidance and support. How is your business impacted by generative AI? This is an issue for CIOs.

Strategy 98

Strategy Risk Enterprise Risk Management 98

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively. Pilots can offer value beyond just experimentation, of course.

Cost-Benefit 140

Cost-Benefit Metrics Insurance Measurement 140

Domino Data Lab

DECEMBER 4, 2020

NCA doesn’t require the assumption of a specific compartmental model for either drug or metabolite; it is instead assumption-free and therefore easily automated [1]. PharmaceUtical Modeling And Simulation (or PUMAS) is a suite of tools to perform quantitative analytics for pharmaceutical drug development [2]. Mean residence time.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

CIO Business Intelligence

APRIL 24, 2024

But to find ways it can help grow a company’s bottom line, CIOs have to do more to understand a company’s business model and identify opportunities where gen AI can change the playing field. We have a HITRUST certified health care environment and we bring in publicly-available models.” And there are audit trails for everything.”

Sales 128

Sales Finance Experimentation Cost-Benefit 128

DataRobot Blog

SEPTEMBER 30, 2022

How do you track the integrity of a machine learning model in production? Model Observability can help. By tracking service, drift, prediction data, training data, and custom metrics, you can keep your models and predictions relevant in a fast-changing world. Model Observability Features.

Slice and Dice 52

Slice and Dice Modeling Metrics Experimentation 52

DataRobot Blog

MARCH 16, 2023

Why model-driven AI falls short of delivering value Teams that just focus model performance using model-centric and data-centric ML risk missing the big picture business context. We are also thrilled to share the innovations and capabilities that we have developed at DataRobot to meet and exceed those requirements.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

Occam's Razor

APRIL 8, 2013

Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

CIO Business Intelligence

APRIL 5, 2023

Midjourney, ChatGPT, Bing AI Chat, and other AI tools that make generative AI accessible have unleashed a flood of ideas, experimentation and creativity. That turns generic documentation into conversational programming where the AI can take your data and show you how to write a query, for example.

Modeling 111

Modeling Testing Cost-Benefit Experimentation 111

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 262

IT Modeling Testing Risk 262