CIO Business Intelligence

DECEMBER 10, 2024

Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, weve already seen the launch and subsequent upgrades of dozens of competing models. From Llama3.1 to Gemini to Claude3.5 From Llama3.1 to Gemini to Claude3.5

Modeling 116

Modeling Insurance Unstructured Data Experimentation 116

KDnuggets

OCTOBER 29, 2024

Automate the machine learning modelling important step with LLMs.

Experimentation 137

Experimentation Modeling Machine Learning 137

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 364

Management Experimentation B2B Machine Learning 364

Analytics Vidhya

OCTOBER 29, 2021

This article was published as a part of the Data Science Blogathon Introduction to Statistics Statistics is a type of mathematical analysis that employs quantified models and representations to analyse a set of experimental data or real-world studies. Data processing is […].

Statistics 358

Statistics Data Science Experimentation Publishing 358

Analytics Vidhya

FEBRUARY 6, 2024

Introduction Creating new neural network architectures can be quite time-consuming, especially in real-world workflows where numerous models are trained during the experimentation and design phase. In addition to being wasteful, the traditional method of training every new model from scratch slows down the entire design process.

Experimentation 318

Experimentation Modeling Analytics Deep Learning 318

Analytics Vidhya

JUNE 13, 2024

Introduction Google’s NotebookLM, an experimental AI-driven notebook, is designed to transform the way we interact with and utilize LLMs.

Experimentation 306

Experimentation Interactive Modeling Analytics 306

CIO Business Intelligence

JANUARY 7, 2025

Transformational CIOs continuously invest in their operating model by developing product management, design thinking, agile, DevOps, change management, and data-driven practices. Focusing on classifying data and improving data quality is the offense strategy, as it can lead to improving AI model accuracy and delivering business results.

Digital Transformation 143

Digital Transformation Experimentation Cost-Benefit Strategy 143

CIO Business Intelligence

JANUARY 2, 2025

Generative AI playtime may be over, as organizations cut down on experimentation and pivot toward achieving business value, with a focus on fewer, more targeted use cases. Either you didnt have the right data to be able to do it, the technology wasnt there yet, or the models just werent there, Wells says of the rash of early pilot failures.

Experimentation 144

Experimentation Digital Transformation Technology Finance 144

Analytics Vidhya

JULY 17, 2023

Google is unveiling its latest experimental offering from Google Labs: NotebookLM, previously known as Project Tailwind. This innovative notetaking software aims to revolutionize how we synthesize information by leveraging the power of language models.

Experimentation 269

Experimentation Software Modeling Analytics 269

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 364

IT Testing Experimentation Software 364

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 360

Experimentation Modeling Strategy Machine Learning 360

CIO Business Intelligence

NOVEMBER 11, 2024

Nate Melby, CIO of Dairyland Power Cooperative, says the Midwestern utility has been churning out large language models (LLMs) that not only automate document summarization but also help manage power grids during storms, for example. Only 13% plan to build a model from scratch.

ROI 137

ROI Cost-Benefit Risk Experimentation 137

O'Reilly on Data

MARCH 25, 2025

Throughout this article, well explore real-world examples of LLM application development and then consolidate what weve learned into a set of first principlescovering areas like nondeterminism, evaluation approaches, and iteration cyclesthat can guide your work regardless of which models or frameworks you choose. Which multiagent frameworks?

Testing 168

Testing Data-driven Software Measurement 168

David Menninger's Analyst Perspectives

MAY 17, 2023

And recently, ChatGPT has raised awareness of AI and instigated research and experimentation into new ways in which AI can be applied. This perspective, the second in a series on generative AI, introduces some of the concepts behind ChatGPT, including large language models and transformers.

Modeling 147

Modeling Experimentation Data-driven Business Intelligence 147

CIO Business Intelligence

DECEMBER 17, 2024

While genAI has been a hot topic for the past couple of years, organizations have largely focused on experimentation. Like any new technology, organizations typically need to upskill existing talent or work with trusted technology partners to continuously tune and integrate their AI foundation models. In 2025, thats going to change.

Experimentation 98

Experimentation ROI Risk Data Quality 98

CIO Business Intelligence

DECEMBER 12, 2024

Confidence from business leaders is often focused on the AI models or algorithms, Erolin adds, not the messy groundwork like data quality, integration, or even legacy systems. In some industries, companies are using legacy software and middleware that arent designed to collect, transmit, and store data in ways modern AI models need, he adds.

IT 134

IT Data Quality Experimentation Machine Learning 134

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 363

Management Machine Learning Experimentation Metrics 363

O'Reilly on Data

JUNE 11, 2024

It is important to be careful when deploying an AI application, but it’s also important to realize that all AI is experimental. It would have been very difficult to develop the expertise to build and train a model, and much more effective to work with a company that already has that expertise. What are your specific use cases?

Modeling 337

Modeling Experimentation Interactive Data-driven 337

CIO Business Intelligence

OCTOBER 17, 2024

Despite critics, most, if not all, vendors offering coding assistants are now moving toward autonomous agents, although full AI coding independence is still experimental, Walsh says. The next evolution of the coding agent model is to have the AI not only write the code, but also write validation tests, run the tests, and fix errors, he adds.

Software 141

Software Testing Experimentation Consulting 141

CIO Business Intelligence

DECEMBER 20, 2024

With the core architectural backbone of the airlines gen AI roadmap in place, including United Data Hub and an AI and ML platform dubbed Mars, Birnbaum has released a handful of models into production use for employees and customers alike.

IT 131

IT Unstructured Data Experimentation Data Lake 131

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.

Experimentation 363

Experimentation Interactive Modeling Software 363

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. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

OCTOBER 24, 2024

In some cases, the AI add-ons will be subscription models, like Microsoft Copilot, and sometimes, they will be free, like Salesforce Einstein, he says. Forrester also recently predicted that 2025 would see a shift in AI strategies , away from experimentation and toward near-term bottom-line gains. growth in device spending.

IT 133

IT Data-driven Recreation/Entertainment Experimentation 133

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 122

Machine Learning Modeling Experimentation IT 122

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g., spam or not-spam), probabilities, groups/segments, or a sequence (e.g.,

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

CIO Business Intelligence

OCTOBER 24, 2024

As they look to operationalize lessons learned through experimentation, they will deliver short-term wins and successfully play the gen AI — and other emerging tech — long game,” Leaver said. They predicted more mature firms will seek help from AI service providers and systems integrators. “For

ROI 127

ROI Data-driven Enterprise Experimentation 127

KDnuggets

APRIL 14, 2023

AutoGPT is an experimental open-source pushing the capabilities of the GPT-4 language model. Just when we got our heads around ChatGPT, another one came along.

Experimentation 152

Experimentation Modeling 152

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 347

Enterprise Deep Learning Data Governance Risk 347

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 319

Finance Modeling Analytics Experimentation 319

CIO Business Intelligence

JANUARY 21, 2025

With traditional OCR and AI models, you might get 60% straight-through processing, 70% if youre lucky, but now generative AI solves all of the edge cases, and your processing rates go up to 99%, Beckley says. Even simple use cases had exceptions requiring business process outsourcing (BPO) or internal data processing teams to manage.

Cost-Benefit 142

Cost-Benefit Data-driven Strategy Marketing 142

CIO Business Intelligence

NOVEMBER 7, 2024

It covers essential topics like artificial intelligence, our use of data models, our approach to technical debt, and the modernization of legacy systems. This initiative offers a safe environment for learning and experimentation. We explore the essence of data and the intricacies of data engineering. I think we’re very much on our way.

Insurance 120

Insurance Experimentation Testing Technology 120

Rocket-Powered Data Science

JULY 6, 2021

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. the monitoring of very important operational ML characteristics: data drift, concept drift, and model security).

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

Management 308

Management Machine Learning Metrics Modeling 308

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

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 346

IT Modeling Testing Risk 346

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. ModelOps and MLOps fall under the umbrella of DataOps,with a specific focus on the automation of data science model development and deployment workflows.

Testing 300

Testing Machine Learning Consulting Data Science 300