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. How Model Observability Provides a 360° View of Models in Production. Read the blog. Read the blog.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

CIO Business Intelligence

APRIL 29, 2024

As organizations roll out AI applications and AI-enabled smartphones and devices, IT leaders may need to sell the benefits to employees or risk those investments falling short of business expectations. They need to have a culture of experimentation.” CIOs should be “change agents” who “embrace the art of the possible,” he says.

Experimentation 131

Experimentation Forecasting Risk Consulting 131

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 89

IT Insurance Strategy Risk 89

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 154

Marketing Modeling Finance Experimentation 154

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 123

Experimentation Strategy Machine Learning Interactive 123

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 14, 2024

Like many public health agencies across the US, the King County Medical Examiner’s Office tracks drug overdose deaths to target interventions for populations at risk and save lives. During the second phase, NLP and ML models created and trained by the King County Department of IT extract the pertinent information from these digitized reports.

Deep Learning 66

Deep Learning Machine Learning Reporting Experimentation 66

IBM Big Data Hub

MARCH 4, 2024

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. Consider the following: Do you need a public foundation model?

Enterprise 104

Enterprise ROI Risk Strategy 104

Smart Data Collective

MAY 22, 2022

The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience. With AI, the risk score for a device doesn’t depend on individual indicators. Predicting If a Device Is at Risk. Therefore, the risk score is always being adjusted accordingly.

Data-driven 136

Data-driven Risk Experimentation IT 136

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 141

Digital Transformation Unstructured Data Machine Learning Risk Management 141

CIO Business Intelligence

SEPTEMBER 6, 2023

Since ChatGPT’s release in November of 2022, there have been countless conversations on the impact of similar large language models. While the potential of Generative AI in software development is exciting, there are still risks and guardrails that need to be considered.

Software 117

Software Experimentation Risk Data Lake 117

CIO Business Intelligence

AUGUST 2, 2023

The survey found tension between business leaders seeking competitive advantage, and IT leaders wanting to limit risks. Interestingly, non-IT leaders were more likely to report actively using generative AI (73%) than IT leaders (59%), suggesting there’s plenty of experimentation going on beyond the purview of the IT department.

Enterprise 94

Enterprise Experimentation Manufacturing Risk 94

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 Knowing these lessons before generative AI adoption will likely save time, improve outcomes, and reduce risks and potential costs.

Enterprise 109

Enterprise Experimentation Modeling Data-driven 109

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. Governments like the U.S.

Deep Learning 70

Deep Learning Experimentation Machine Learning Risk 70

O'Reilly on Data

APRIL 19, 2021

Relatively few respondents are using version control for data and models. Tools for versioning data and models are still immature, but they’re critical for making AI results reproducible and reliable. It’s possible that pandemic-induced boredom led more people to respond, but we doubt it. Executive Summary. Respondents.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

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

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

CIO Business Intelligence

FEBRUARY 8, 2024

AI is like the discovery of fire—it’s a great tool if you know how to use it, but if you don’t use it responsibly (or use a model built responsibly), it will burn you. Interacting with AI data or experiences in silos introduces risk and increases inefficiencies because it’s kept separate. Artificial Intelligence

Cost-Benefit 112

Cost-Benefit Experimentation Interactive Risk 112

IBM Big Data Hub

OCTOBER 4, 2022

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. Challenges around managing risk.

Metadata 101

Metadata Risk Risk Management Experimentation 101

Smarten

MAY 17, 2023

Whether you are looking at ChatGPT or Open AI and wondering how it might be applied to your business environment, it is important to understand the current state of this technology, the inherent risks and the possible opportunities. . “So, proceed, but don’t over pivot.”

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

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. Data Team members, have you ever felt overwhelmed? The never-ending flow of new information can be stressful, and it’s hard to know where to start.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

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

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 128

Machine Learning Data Science Experimentation IoT 128

CIO Business Intelligence

APRIL 14, 2023

But just like other emerging technologies, it doesn’t come without significant risks and challenges. According to a recent Salesforce survey of senior IT leaders , 79% of respondents believe the technology has the potential to be a security risk, 73% are concerned it could be biased, and 59% believe its outputs are inaccurate.

Risk 119

Risk Experimentation Marketing Risk Management 119

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

FEBRUARY 21, 2024

For example, top researchers at Florida State University are now developing innovative large language models (LLMs) to help advance research in areas like material science and healthcare — going beyond gen AI used by the general public. We developed a model to predict student outcomes based on metrics from historical evidence,” he says. “We

Recreation/Entertainment 128

Recreation/Entertainment Experimentation Modeling Data-driven 128

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 64

Experimentation Modeling Metrics Machine Learning 64

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

OCTOBER 18, 2023

But if there are any stop signs ahead regarding risks and regulations around generative AI, most enterprise CIOs are blowing past them, with plans to deploy an abundance of gen AI applications within the next two years if not already. A recent survey of nearly 1,000 IT decision-makers conducted by Foundry underscores this.

Risk 136

Risk Manufacturing Enterprise Technology 136

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. These steps also reflect the experimental nature of ML product management.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

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. Imagine a self-driving car piloted by an AGI. It might suggest a restaurant based on preferences and current popularity.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

IBM Big Data Hub

MAY 25, 2023

The Center of Excellence (CoE) already has more than 1,000 consultants with specialized generative AI expertise that are engaging with a global set of clients to drive productivity in IT operations and core business processes like HR or marketing, elevate their customer experiences and create new business models.

Consulting 106

Consulting Experimentation Machine Learning Modeling 106

Cloudera

OCTOBER 18, 2023

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement — to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation.

Cost-Benefit 80

Cost-Benefit Testing Machine Learning Optimization 80

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. Where will the biggest transformation occur first?

Insurance 64

Insurance Experimentation Finance Data Governance 64

DataRobot Blog

JANUARY 17, 2023

Recently, a prospective customer asked me how I reconcile the fact that DataRobot has multiple very successful investment banks using DataRobot to enhance the P&L of their trading businesses with my comments that machine learning models aren’t always great at predicting financial asset prices. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

Ontotext

MAY 31, 2023

The link prediction models are based on the so-called Knowledge Graph Embeddings, which relying on knowledge graph technology. With the help of link prediction models, the graph can be enriched with new information, which is otherwise inaccessible to scientists. How does it work? What are the benefits of Ontotext’s method?

Experimentation 52

Experimentation Cost-Benefit Predictive Modeling Risk 52

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