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 117

Risk Experimentation Marketing Risk Management 117

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 102

Metadata Risk Risk Management Experimentation 102

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

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

Cost-Benefit 76

Cost-Benefit Testing Machine Learning Optimization 76

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 103

Management Experimentation Modeling Enterprise 103

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 112

Enterprise IT Experimentation Unstructured Data 112

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 61

Insurance Experimentation Finance Data Governance 61

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. Creating Summary Data for Unstructured Documents (PDFs, HTML, Websites, etc.)

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

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. CarMax CITO Shamim Mohammed confirms his company was using OpenAI’s GPT-3.x

Risk 132

Risk Manufacturing Enterprise Technology 132

CIO Business Intelligence

AUGUST 17, 2023

But, as with any big new wave, there is a risk of once-promising projects being washed up and there are clear and obvious concerns over governance, quality and security. We ran workshops with every division of our business, educating them on the accelerating innovation in this area, brainstorming opportunities and risks.

Risk 89

Risk Cost-Benefit Strategy Experimentation 89

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 95

Cost-Benefit Modeling Manufacturing Interactive 95

CIO Business Intelligence

JULY 31, 2023

1 question now is to allow or not allow,” says Mir Kashifuddin, data risk and privacy leader with the professional services firm PwC US. Rapidly evolving risks Companies that have blocked the use of gen AI are finding that some workers are still testing it out. How has, say, ChatGPT hit your business model?”

Strategy 94

Strategy Risk Enterprise Risk Management 94

CIO Business Intelligence

JUNE 28, 2023

For all of generative AI’s allure, large enterprises are taking their time, many outright banning tools like ChatGPT over concerns of accuracy, data protection, and the risk of regulatory backlash. Experimentation with a use case driven approach. Caution is king. Looking forward.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

Domino Data Lab

APRIL 7, 2019

A good NLP library will, for example, correctly transform free text sentences into structured features (like cost per hour and is diabetic ), that easily feed into a machine learning (ML) or deep learning (DL) pipeline (like predict monthly cost and classify high risk patients ). Training domain-specific models. Pretrained models.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

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 100

Testing Experimentation Management Metadata 100

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

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

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 138

Cost-Benefit Metrics Insurance Measurement 138

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 123

Sales Finance Experimentation Cost-Benefit 123

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? 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, The GPT-series LLMs are also called “foundation models.” GPT-2, 3, 3.5,

IT 262

IT Modeling Testing Risk 262

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

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 94

Modeling Testing Cost-Benefit Experimentation 94

CIO Business Intelligence

MARCH 5, 2024

Many other platforms, such as Coveo’s Relative Generative Answering , Quickbase AI , and LaunchDarkly’s Product Experimentation , have embedded virtual assistant capabilities but don’t brand them copilots. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation.

Cost-Benefit 112

Cost-Benefit Advertising Experimentation Software 112

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 platforms assist with a multitude of tasks ranging from enforcing data governance to better workload distribution to the accelerated construction of machine learning models.

Machine Learning 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Now, there is a data risk here.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

CIO Business Intelligence

OCTOBER 4, 2023

With a little experimentation, it’s cheap and easy to find applications that can provide business benefits, creating a false perception of value. Then it’s time to assemble the final document. Ballooning costs The most popular gen AI chatbots are free to the public. Often, generative AI will not be a good fit. Is it accessible?

Cost-Benefit 135

Cost-Benefit Manufacturing Machine Learning Experimentation 135

The Unofficial Google Data Science Blog

JUNE 30, 2016

In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects. The choice of space $cal F$ (sometimes called the model ) and loss function $L$ explicitly defines the estimation problem. This is often referred to as the positivity assumption.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. People look toward online resources such as StackOverflow to find out how to use APIs when the documentation doesn’t have an example that fits. Model-Driven Data Queries. Introduction. That’s impressive.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Cloudera

NOVEMBER 25, 2020

For example, it includes patient samples (blood, blood pressure, temperature, and more), patient information (age, gender, where they have lived, family situation, and other details), and treatment history, most of which is currently found only in paper documents. Matthew’s company is not alone in this situation.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

Domino Data Lab

AUGUST 26, 2019

Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Data scientists and researchers ascertain predictive accuracy of models using different techniques, methodologies, and settings, including model parameters and hyperparameters.

Testing 79

Testing Modeling Machine Learning Metrics 79

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2 in frequency in proposal topics; a related term, “models,” is No. An ML-related topic, “models,” was No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

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. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

CIO Business Intelligence

APRIL 15, 2024

We’ve had what I’d consider more traditional AI and machine learning for over a decade, with thousands of models we’ve built and applied, mostly in service to tax by analyzing the millions of tax returns we have,” says H&R Block CIO Alan Lowden. No one wants to implement AI that has a high risk of bias,” he says. “We

Testing 76

Testing Experimentation Data Quality Machine Learning 76

CIO Business Intelligence

SEPTEMBER 27, 2023

Identifying worthwhile use cases Hackajob, a company that provides a platform for organizations to find and recruit IT and developer talent, began piloting generative AI models in the second half of 2022 as part of an informal research and development initiative to explore emerging technology trends.

Strategy 122

Strategy Risk Data-driven Modeling 122

CIO Business Intelligence

AUGUST 1, 2023

The impact of generative AIs, including ChatGPT and other large language models (LLMs), will be a significant transformation driver heading into 2024. Mitigate risks by communicating an LLM governance model The generative AI landscape has more than 100 tools covering test, image, video, code, speech, and other categories.

Digital Transformation 97

Digital Transformation Unstructured Data Strategy Experimentation 97

Cloudera

MAY 31, 2023

Riding the wave of the generative AI revolution, third party large language model (LLM) services like ChatGPT and Bard have swiftly emerged as the talk of the town, converting AI skeptics to evangelists and transforming the way we interact with technology. Samsung may have an opinion on this after their experience.

Enterprise 73

Enterprise Data Processing Experimentation Modeling 73