O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. He first tried to do so by becoming Cervantes, learning Spanish, and forgetting all the history since Cervantes wrote Don Quixote , among other things, but then decided it would make more sense to (re)write the text as Menard himself.

Modeling 277

Modeling Machine Learning Risk Advertising 277

Analytics Vidhya

OCTOBER 6, 2019

Overview What are the next steps after you’ve deployed your machine learning model? Post-deployment monitoring is a crucial step in any machine learning project. The post Deployed your Machine Learning Model?

Machine Learning 289

Machine Learning Modeling Analytics Data Science 289

CIO Business Intelligence

APRIL 12, 2024

These roles include data scientist, machine learning engineer, software engineer, research scientist, full-stack developer, deep learning engineer, software architect, and field programmable gate array (FPGA) engineer. It is used to execute and improve machine learning tasks such as NLP, computer vision, and deep learning.

Deep Learning 124

Deep Learning IT Machine Learning IoT 124

O'Reilly on Data

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. Lessons Learned from Data Warehouse and Data Engineering Platforms. Which path is best?

Data Science 355

Data Science Machine Learning Data Warehouse Deep Learning 355

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. So too is keeping your options open.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions. Query> DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Cloudera

NOVEMBER 29, 2023

In the dynamic world of machine learning operations (MLOps), staying ahead of the curve is essential. That’s why we’re excited to announce the Cloudera Model Registry as generally available, a game-changer that’s set to transform the way you manage your machine learning models in production environments.

Modeling 82

Modeling Machine Learning Metadata Metrics 82

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Why AI software development is different.

Management 332

Management Machine Learning Experimentation Metrics 332

CIO Business Intelligence

DECEMBER 13, 2023

Shumon Zaman, Chief Digital and Information Officer at Ali&Sons explains to CIO Middle East what are the top 7 technologies that have changed the tech landscape in 2023. Technology never stops evolving or constantly experiencing changes and improvements.

Machine Learning 119

Machine Learning Software Testing Risk 119

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” Up until now, we’ve built systems by carefully and painstakingly telling systems exactly what to do, instruction by instruction. In short, we can use machine learning to automate software development itself.

Software 261

Software Machine Learning Risk Data-driven 261

CIO Business Intelligence

JANUARY 19, 2024

Data science certifications give you an opportunity to not only develop skills that are hard to find in your desired industry, but also validate your data science know-how so recruiters and hiring managers know what they get if they hire you. Not finding what you’re looking for? Data scientist is one of the hottest jobs in IT.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Cloudera

MARCH 26, 2024

How do you adapt a foundational model to your specific needs? What about security, privacy, and trust concerns? Cloudera: Your Trusted Partner in AI With over 25 Exabytes of Data Under Management and hundreds of customers leveraging our platform for Machine Learning, Cloudera has a long and successful history as an industry leader.

Cost-Benefit 78

Cost-Benefit Machine Learning Enterprise Modeling 78

O'Reilly on Data

JUNE 27, 2023

Doing so means giving the general public a freeform text box for interacting with your AI model. So, what do you do? So what’s so scary about putting up a text box so people can engage with your chatbot? (The That leads to three problems: By default, that underlying model will respond to any prompt.

Risk Management 226

Risk Management Risk Management Modeling 226

CIO Business Intelligence

SEPTEMBER 29, 2023

If any technology has captured the collective imagination in 2023, it’s generative AI — and businesses are beginning to ramp up hiring for what in some cases are very nascent gen AI skills, turning at times to contract workers to fill gaps, pursue pilots, and round out in-house AI project teams.

Deep Learning 143

Deep Learning Machine Learning Modeling Consulting 143

O'Reilly on Data

FEBRUARY 19, 2021

MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice. The Time Is Now to Adopt Responsible Machine Learning. Responsible Machine Learning (ML) is a movement to make AI systems accountable for the results they produce.

Data Lake 289

Data Lake Data Warehouse Machine Learning Modeling 289

O'Reilly on Data

JUNE 15, 2023

The world changed on November 30, 2022 as surely as it did on August 12, 1908 when the first Model T left the Ford assembly line. The key is to ensure that these machines are aligned with human intentions and values.” That was the date when OpenAI released ChatGPT, the day that AI emerged from research labs into an unsuspecting world.

Metrics 285

Metrics Reporting Measurement Finance 285

Rocket-Powered Data Science

JULY 19, 2023

The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage. What could be faster and easier than on-prem enterprise data sources? A similarly high percentage of tabular data usage among data scientists was mentioned here.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. Interest on the part of companies means the demand side for “machine learning talent” is healthy.

Machine Learning 220

Machine Learning Risk Management Statistics 220

CIO Business Intelligence

JANUARY 24, 2024

Generative AI and large language models (LLMs) like ChatGPT are only one aspect of AI. It’s the culmination of a decade of work on deep learning AI. That decade has given us newfound ways to use AI—from apps that know what you’ll type next, to cars that drive themselves and algorithms for scientific breakthroughs.

Deep Learning 112

Deep Learning Unstructured Data Machine Learning Modeling 112

DataKitchen

OCTOBER 28, 2021

What Is AI Bias? Machine learning (ML) models are computer programs that draw inferences from data — usually lots of data. One way to think of ML models is that they instantiate an algorithm (a decision-making procedure often involving math) in software and then, at relatively low cost, deploy it on a large scale.

Testing 130

Testing IT Manufacturing Metrics 130

O'Reilly on Data

JULY 28, 2020

If you’re an AI product manager (or about to become one), that’s what you’re signing up for. It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. In this article, we turn our attention to the process itself: how do you bring a product to market?

Marketing 362

Marketing Experimentation Metrics Testing 362

Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Organizations need to usher their ML models out of the lab (i.e., COPML accounts for the fact that true production machine learning (i.e.,

Machine Learning 119

Machine Learning Modeling Experimentation IT 119

CIO Business Intelligence

FEBRUARY 9, 2024

The two new features, namely a testing center and the provision of prompt engineering suggestions, are the fruit of significant investment in the company’s AI engineering team, said Claire Cheng, vice president of machine learning and AI engineering at Salesforce.

Testing 135

Testing Enterprise Modeling Machine Learning 135

CIO Business Intelligence

OCTOBER 20, 2023

We learned a ton about how customers react to us, and this is what I mean about changing our organization,” Jeevanjee says. “We We learned a ton about how customers react to us, and this is what I mean about changing our organization,” Jeevanjee says. The methodical approach does not mean Allstate is a technology novice.

Digital Transformation 136

Digital Transformation Insurance Recreation/Entertainment Machine Learning 136

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. How to choose the right ML Framework.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

CIO Business Intelligence

SEPTEMBER 8, 2023

But what exactly should they focus on? What is this model good at and what should be the boundaries on how and where it’s applied? For instance, it might be helpful for students to share work to achieve learning outcomes, but it’s illegal for a bank to share stock transactions from one customer to other groups.

Risk 126

Risk Strategy Modeling Data Processing 126

Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. Artificial General Intelligence The goal of AGI is to create a general thinking machine with self-sufficiency and broad human-like general intelligence. Credit: [link].

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

CIO Business Intelligence

JANUARY 16, 2024

In the rush to establish technical strategies for making good on the promise of generative AI, many CIOs find themselves running headlong into what may be their most challenging task yet: preparing their organization’s end-users — from knowledge workers and assembly line laborers to doctors, accountants, and lawyers — to co-exist with generative AI.

Cost-Benefit 130

Cost-Benefit Enterprise Unstructured Data Technology 130

Domino Data Lab

AUGUST 6, 2021

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards.

Machine Learning 145

Machine Learning Modeling Testing Risk 145

CIO Business Intelligence

NOVEMBER 8, 2023

What caused us to move much faster to the cloud was aligning our technology assets with the capabilities we needed to enable a modern business strategy,” she says. We had to make [that] investment to leverage AI and machine learning models for different analytical capabilities across the entire company,” Kay says.

IT 124

IT Insurance Machine Learning Cost-Benefit 124

CIO Business Intelligence

APRIL 12, 2024

Shoppers can find overalls, live chickens, gun safes, ice fishing augers, ferret food, throw blankets, a farmhouse-shaped egg holder , and welding machines as they walk the aisles of most Tractor Supply stores. It makes the team member much more efficient.” One of our differentiators is we hire team members from the community,” he says.

Experimentation 114

Experimentation Sales Digital Transformation Metrics 114

CIO Business Intelligence

DECEMBER 18, 2023

From climate modelling to energy management, optimizing renewable energy and adapting to extreme weather events, AI is deploying its power to improve our fight against climate change. Artificial Intelligence has emerged as a powerful tool to address the challenges of climate change. Salvador asked.

Consulting 119

Consulting Manufacturing Machine Learning Measurement 119

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 88

Metrics Machine Learning Risk Statistics 88

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 Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

CIO Business Intelligence

MAY 12, 2022

Do you want to know what the future may bring? What are predictive analytics tools? Deployment. Drag-and-drop Modeler for creating pipelines, IBM integrations. Composite AI mixes statistics and machine learning; industry-specific solutions. Predictive analysis tools have an answer. Are they right?

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

MAY 5, 2023

The combination of CarMax’s revolutionary digital business model applied to the used-car business with revolutionary AI tools available to all makes for powerful and profitable business outcomes. x natural language model on pilots before Microsoft’s well publicized $10 billion investment in the nonprofit at the outset of 2023.

Digital Transformation 145

Digital Transformation Cost-Benefit Business Driver Data Lake 145

IBM Big Data Hub

APRIL 18, 2024

Imagine a world where machines aren’t confined to pre-programmed tasks but operate with human-like autonomy and competence. AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90