CIO Business Intelligence

AUGUST 15, 2024

Meanwhile, “traditional” AI technologies in use at the time, including machine learning, deep learning, and predictive analysis, continue to prove their value to many organizations, he says. As the gen AI hype subsides, Stephenson sees IT leaders reevaluating their strategies in favor of other AI technologies.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143

CIO Business Intelligence

OCTOBER 3, 2024

It’s not the technologies they use. It’s a natural fit and will be interesting to see how these ensemble AI models work and what use cases will go from experimentation to production,” says Dyer. Gen AI is a nascent and fast evolving technology. It’s not the cloud provider they use.

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

CIO Business Intelligence

APRIL 25, 2023

Over the last few months, both business and technology worlds alike have been abuzz about ChatGPT, and more than a few leaders are wondering what this AI advancement means for their organizations. A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. What is ChatGPT?

Experimentation 116

Experimentation Deep Learning Enterprise Modeling 116

Cloudera

AUGUST 20, 2020

Machine Learning (ML) and Artificial Intelligence (AI), while still emerging technologies inside of enterprise organisations, have given some companies the ability to dynamically change their fortunes and reshape the way they are doing business — that is if they are brave enough to experiment and explore the unknown.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

Domino Data Lab

OCTOBER 14, 2020

Experimentation and collaboration are built into the core of the platform. We needed an “evolvable architecture” which would work with the next deep learning framework or compute platform. Likewise, a set of features should be reusable by other frameworks and technologies without expensive format conversions.

Experimentation 99

Experimentation Deep Learning Modeling Testing 99

CIO Business Intelligence

MAY 23, 2022

The traditional approach for artificial intelligence (AI) and deep learning projects has been to deploy them in the cloud. For many nascent AI projects in the prototyping and experimentation phase, the cloud works just fine. Cloud Architecture, IT Leadership

Cost-Benefit 98

Cost-Benefit Experimentation Data Lake Deep Learning 98

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 105

IT Digital Transformation IoT Cost-Benefit 105

Domino Data Lab

FEBRUARY 12, 2020

This post is for people making technology decisions, by which I mean data science team leads, architects, dev team leads, even managers who are involved in strategic decisions about the technology used in their organizations. for reinforcement learning (RL), ? Introduction. If your team has started using ? multiprocessing , ?

Experimentation 137

Experimentation Modeling Data Science Machine Learning 137

Smart Data Collective

DECEMBER 24, 2020

The technology remains limited, as Tiago discovered when using it for his own academic essays. Students can utilize machine learning to create a basic format for their papers, but the technology still needs significant oversight. It should be considered an initial steppingstone, rather than a complete solution. Conclusion.

Machine Learning 122

Machine Learning Experimentation Software Reporting 122

IBM Big Data Hub

DECEMBER 15, 2023

Open-source artificial intelligence (AI) refers to AI technologies where the source code is freely available for anyone to use, modify and distribute. As a result, these technologies quite often lead to the best tools to handle complex challenges across many enterprise use cases.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 90

Unstructured Data Cost-Benefit Machine Learning Experimentation 90

CIO Business Intelligence

AUGUST 21, 2024

It wasn’t just a single measurement of particulates,” says Chris Mattmann, NASA JPL’s former chief technology and innovation officer. “It Meanwhile NASA isn’t alone deploying these early kinds of multiagent systems as companies that deal with operations and logistics have used these technologies for years.

Risk 136

Risk Insurance Cost-Benefit Software 136

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI plays a pivotal role as a catalyst in the new era of technological advancement. PwC calculates that “AI could contribute up to USD 15.7

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. It used deep learning to build an automated question answering system and a knowledge base based on that information.

Management 110

Management Machine Learning Experimentation Metrics 110

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Today’s organizations are realizing success with enterprise-grade AI technologies for fast and secure business growth.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

CDW Research Hub

AUGUST 21, 2019

Finally, perhaps the biggest obstacle faced when adopting an AI project is the time it takes to configure the server, prepare the data, build and train the model, and deploy and infer for deep learning. The kit helps facilitate clients’ AI adoption journey from experimentation to production.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

CIO Business Intelligence

JUNE 12, 2023

The current interest in AI is massive, and companies, as well as the public sector, are exploring the new technology in all its capacities as much as possible. Of course, he says, it’s interesting to try something experimental, but investing requires greater commitment to the business case. It’s the simplest trick,” he says.

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

IBM Big Data Hub

APRIL 18, 2024

This is the potential of artificial general intelligence (AGI), a hypothetical technology that may be poised to revolutionize nearly every aspect of human life and work. However, if AGI development uses similar building blocks as narrow AI, some existing tools and technologies will likely be crucial for adoption.

Cost-Benefit 89

Cost-Benefit Manufacturing Modeling Interactive 89

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Or, maybe I'm just too deep into this stuff. :). Intro to Machine Learning. Machine Learning. Deep Learning.

Marketing 138

Marketing Analytics Machine Learning Strategy 138

Ontotext

NOVEMBER 6, 2019

As more and more industries adopt semantic technology, the needs and usage has become increasingly specific and varied. At the same time, the community there is of users can share the best practices, enabling the cross-pollination of the most successful and most fruitful results of their experimentation. The Plugins.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. The Ethical OS also provides excellent tools for thinking through the impact of technologies. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 364

Marketing Experimentation Metrics Testing 364

O'Reilly on Data

MARCH 19, 2020

Our analysis of ML- and AI-related data from the O’Reilly online learning platform indicates: Unsupervised learning surged in 2019, with usage up by 172%. Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage.

Deep Learning 357

Deep Learning Machine Learning Data-driven Modeling 357

O'Reilly on Data

APRIL 19, 2021

Not surprisingly, computers, electronics, and technology topped the charts, with 17% of the respondents. We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. 58% claimed to be using unsupervised learning. Bottlenecks to AI adoption.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

CIO Business Intelligence

MAY 14, 2024

The ML models include classic ML and deep learning to predict category labels from the narrative text in reports. The IT department also used the Hugging Face online AI service and PyTorch, a Python framework for building deep learning models. Azure Databricks is also employed for data analytics as part of the solution.

Machine Learning 97

Machine Learning Deep Learning Reporting Experimentation 97

Domino Data Lab

MAY 8, 2019

Several technology conferences all occurred within four fun-filled weeks: Strata SF , Google Next , CMU Summit on US-China Innovation, AI NY , and Strata UK , plus some other events. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

SEPTEMBER 11, 2019

In short, what are the issues, trends, and technologies we should be watching? [1]. Deep learning,” for example, fell year over year to No. The challenge is to identify how, when, where, and why to use each of these fit-for-purpose technologies. Which themes and topics tended to intersect or overlap with one another?

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

O'Reilly on Data

JANUARY 7, 2020

Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required. To stay competitive, data scientists need to at least dabble in machine and deep learning.

Deep Learning 288

Deep Learning Machine Learning Experimentation Modeling 288

CIO Business Intelligence

MAY 6, 2025

These capabilities are no longer theoretical or experimental. While the algorithms can vary in complexity, from logistic regression to deep learning, the value lies in what they help us anticipate and prevent. They are live, operational and transforming how companies plan, act and serve their customers.

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78