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 We’re using our own databases, testing against our own needs, and building around specific problem sets.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

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. Debugging: Identifying and fixing bugs in code is essential for application security.

Cost-Benefit 75

Cost-Benefit Testing Machine Learning Optimization 75

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

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.” “So, proceed, but don’t over pivot.”

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

CIO Business Intelligence

JUNE 28, 2023

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

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 135

Recreation/Entertainment Experimentation Modeling Data-driven 135

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 122

Risk Experimentation Marketing Risk Management 122

CIO Business Intelligence

MARCH 7, 2023

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

CIO Business Intelligence

JULY 6, 2022

Our strategy is essentially to leverage the public cloud’s economies of scale, to drive business value, to lower risk, to increase resiliency, and really to ensure our infrastructure is evergreen. Because when you can experiment, you can potentially enter a new business quickly, test an idea. And you hear this a lot.

Experimentation 98

Experimentation Strategy Testing Risk 98

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. This has serious implications for software testing, versioning, deployment, and other core development processes.

Management 332

Management Machine Learning Experimentation Metrics 332

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 90

Cost-Benefit Modeling Manufacturing Interactive 90

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

CIO Business Intelligence

JULY 31, 2023

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. How has, say, ChatGPT hit your business model?” How is your business impacted by generative AI?

Strategy 98

Strategy Risk Enterprise Risk Management 98

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 98

Risk Cost-Benefit Strategy Experimentation 98

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

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 141

Risk Manufacturing Enterprise Technology 141

CIO Business Intelligence

NOVEMBER 13, 2023

Transformational leaders must ensure their organizations have the expertise to integrate new technologies effectively and the follow-through to test and troubleshoot thoroughly before going live. IT leaders help facilitate a shift in organizational mindset toward a willingness to take risks and learn from failures.

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

Corinium

JUNE 6, 2019

Regulations and compliance requirements, especially around pricing, risk selection, etc., Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. Build multiple MVPs to test conceptually and learn from early user feedback.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Smart Data Collective

FEBRUARY 4, 2020

Current R&D Models Provide Diminishing Returns. Phase 0 is the first to involve human testing. Phase I involves dialing-in the proper dosage and further testing in a larger patient pool. Without better methodology, difficult-to-treat and ill-understood conditions and diseases are at risk of staying that way.

Experimentation 99

Experimentation Testing Modeling Strategy 99

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. AI Opportunities Generative AI is the basis for sophisticated AI models such as ChatGPT and Dall-E. Conversations suggest that AI is already transforming most major industries.

Advertising 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

IBM Big Data Hub

DECEMBER 14, 2023

Another year has passed—it felt like the whole world was talking about and trying out tools powered by generative AI and Large Language Models (LLMs). The extension of the CIO office’s dedicated data center to the IBM public cloud allowed for experimentation and growth with zero risk.

Experimentation 73

Experimentation Testing Software Management 73

Ontotext

APRIL 3, 2024

Nimit Mehta: I think that 2024 is going to be a buckle-down year, but, at the same time, we’ll see a rapid explosion of experimentation. Nimit Mehta : You are talking about the three big ones: cost, revenue, and risk. And, when you get to the top, it’s about risks and existential threats to the business. What is risk?

Technology 59

Technology Risk Digital Transformation Measurement 59

Alation

DECEMBER 20, 2022

To remain relevant, organizations seek “ digital transformation ,” a business philosophy steeped in change and in which technology plays a heavy hand supporting business models and value propositions. No place is the risk higher than data. These organizations use experimentation and constant market testing to learn and invest.

Digital Transformation 96

Digital Transformation Scorecard Measurement Experimentation 96

AWS Big Data

MAY 2, 2023

Test the feature To test this feature, run the producer DAG. Removal of experimental Smart Sensors. 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. Apache Airflow v2.4.3

Testing 100

Testing Experimentation Management Metadata 100

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

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

CIO Business Intelligence

JUNE 27, 2022

We rely heavily on automated testing. A lot of the current approaches feel very experimental and are tough to see as maintainable, so there’s certainly still room for growth here. We knew we had a great product, with a number of paying customers and a fair approach to pricing so churn risk was low. I thought, really?!

Software 115

Software Experimentation Testing Marketing 115

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

FineReport

DECEMBER 11, 2019

Effective use of big data helps companies analyze critical information more accurately, ultimately improving operational efficiency, reducing costs, reducing risk, accelerating innovation, and increasing revenue. – Data Divination: Big Data Strategies. Data analysis is setting off a revolution.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Cloudera

AUGUST 2, 2018

Leading insurers are underwriting policies with lower risks. Data teams in these insurance firms are leading the charge in rebuilding entire business models around data and analytics. When good stuff happens in the background, and we take it for granted, we know the technology behind the scenes is working.

Data Warehouse 51

Data Warehouse Insurance Experimentation Software 51

CIO Business Intelligence

JULY 11, 2023

In recent years, we have witnessed a tidal wave of progress and excitement around large language models (LLMs) such as ChatGPT and GPT-4. By deploying the LLM within their own VPC, the company can benefit from the AI’s insights without risking the exposure of their valuable data.

Modeling 95

Modeling Testing Experimentation Risk Management 95

The Unofficial Google Data Science Blog

JULY 22, 2020

One reason to do ramp-up is to mitigate the risk of never before seen arms. A ramp-up strategy may mitigate the risk of upsetting the site’s loyal users who perhaps have strong preferences for the current statistics that are shown. For example, imagine a fantasy football site is considering displaying advanced player statistics.

Experimentation 95

Experimentation Statistics Testing Strategy 95

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’ve been doing proof-of-value and different test cases on efficiency opportunities within our organization as it relates to AI,” he says.

Sales 119

Sales Finance Experimentation Cost-Benefit 119

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 363

Management Experimentation B2B Machine Learning 363

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 69

Cost-Benefit Metrics Insurance Measurement 69

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 264

IT Modeling Testing Risk 264

Occam's Razor

JUNE 4, 2018

Not easy, but your business model has to change to survive.). Not wanting to risk it, I click on the Find in Store link you see at the bottom of the page. Such is the case with A/B testing. My wife thinks I’ll look prettier in the red, I think the Mustard really looks like my color. :). I still do it less than I should.

Strategy 124

Strategy Cost-Benefit Testing Sales 124