CIO Business Intelligence

APRIL 25, 2024

During the summer of 2023, at the height of the first wave of interest in generative AI, LinkedIn began to wonder whether matching candidates with employers and making feeds more useful would be better served with the help of large language models (LLMs). Generative AI, Software Development, Technology Industry

IT 135

IT Experimentation Cost-Benefit Metrics 135

O'Reilly on Data

JANUARY 11, 2022

This trend started with the gigantic language model GPT-3. This may encourage the creation of more large-scale models; it might also drive a wedge between academic and industrial researchers. What does “reproducibility” mean if the model is so large that it’s impossible to reproduce experimental results?

Experimentation 297

Experimentation Modeling Strategy Machine Learning 297

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). Why AI software development is different. This shift requires a fundamental change in your software engineering practice.

Management 332

Management Machine Learning Experimentation Metrics 332

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

CIO Business Intelligence

FEBRUARY 16, 2024

For payroll services company ADP, it has paved the way to becoming a SaaS provider capable of taking on big names in enterprise software. ADP’s innovation lab has already developed many machine learning models and predictive analytics that exploit the company’s data cloud. We are so early in the game and doing a lot of experimentation.

Digital Transformation 110

Digital Transformation Experimentation Cost-Benefit Machine Learning 110

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.

Deep Learning 69

Deep Learning Experimentation Machine Learning Risk 69

O'Reilly on Data

SEPTEMBER 8, 2020

That cyclic process, which is about collaboration between software developers and customers, may be exactly what we need to get beyond the “AI as Oracle” interaction. Most AI systems we’ve seen envision AI as an oracle: you give it the input, it pops out the answer.

Experimentation 297

Experimentation Interactive Modeling Software 297

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 113

Enterprise IT Experimentation Unstructured Data 113

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

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

Experimentation 79

Experimentation Modeling Deep Learning Data-driven 79

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

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

DataKitchen

JANUARY 20, 2021

A centralized team can publish a set of software services that support the rollout of Agile/DataOps. The center of excellence (COE) model leverages the DataOps team to solve real-world challenges. For example, some teams may recognize services revenue in the quarter booked, and others may amortize the revenue over the contract period.

Metrics 243

Metrics Experimentation Measurement Testing 243

CIO Business Intelligence

NOVEMBER 21, 2023

Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions.

IT 130

IT Risk Cost-Benefit Risk Management 130

CIO Business Intelligence

MAY 12, 2022

But there are deeper challenges because predictive analytics software can’t magically anticipate moments when the world shifts gears and the future bears little relationship to the past. Drag-and-drop Modeler for creating pipelines, IBM integrations. Driverless AI offers automated pipeline; AI adapts to incoming data. Open source core.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

IBM Big Data Hub

MARCH 4, 2024

In 2024, companies confront significant disruption, requiring them to redefine labor productivity to prevent unrealized revenue, safeguard the software supply chain from attacks, and embed sustainability into operations to maintain competitiveness. Consider the following: Do you need a public foundation model? times higher ROI.

Enterprise 104

Enterprise ROI Risk Strategy 104

O'Reilly on Data

MARCH 19, 2020

The chatbot was one of the first applications of AI in experimental and production usage. Does the growing engagement in neural networks, reinforcement learning, unsupervised learning, and the increased focus on putting models into production augur a shift in how practitioners in the space frame what they do? What’s in a name?

Deep Learning 276

Deep Learning Machine Learning Data-driven Modeling 276

CIO Business Intelligence

FEBRUARY 7, 2024

Franchetti acknowledges that a KPI- and outcome-driven method is still appropriate for many technology rollouts, but “the organic approach is better for AI, so our deep software development subject matter experts can innovate without a targeted business outcome,” he says. “Of

KPI 89

KPI Measurement Experimentation Finance 89

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 75

Metadata Risk Experimentation Dashboards 75

CIO Business Intelligence

APRIL 2, 2024

Joanne Friedman, PhD, CEO, and principal of smart manufacturing at Connektedminds, says orchestrating success in digital transformation requires a symphony of integration across disciplines : “CIOs face the challenge of harmonizing diverse disciplines like design thinking, product management, agile methodologies, and data science experimentation.

Management 118

Management Digital Transformation Testing Experimentation 118

IBM Big Data Hub

OCTOBER 4, 2022

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Multiple unsupported tools for building and deploying models. Consistent principles guiding the design, development, deployment and monitoring of models are critical in driving responsible, trustworthy AI.

Metadata 101

Metadata Risk Risk Management Experimentation 101

CIO Business Intelligence

MARCH 10, 2022

Fujitsu remains very much interested in the mainframe market, with a new model still on its roadmap for 2024, and a move under way to “shift its mainframes and UNIX servers to the cloud, gradually enhancing its existing business systems to optimize the experience for its end-users.”

Sales 123

Sales Testing Experimentation Data Processing 123

CIO Business Intelligence

JUNE 16, 2022

Analysts and data scientists need flexibility when working with data; experimentation fuels the development of analytics and machine learning models. If data is difficult to work with, experimentation slows down, and consequently, so does innovation.

IT 122

IT Experimentation IoT Data-driven 122

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. The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%).

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

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 86

Digital Transformation Cost-Benefit Informatics Data mining 86

Smart Data Collective

OCTOBER 13, 2022

These patterns could then be used as the basis for additional experimentation by scientists or engineers. It’s applicable in software design, architecture, and medicine , among other industries. . Also, obtaining large amounts of data sufficient to train an AI model can be challenging. Generative Design. Final Thoughts.

Testing 115

Testing Cost-Benefit Experimentation Optimization 115

Depict Data Studio

OCTOBER 26, 2021

I first learned this trick using Adobe software and was pleased it works in the Office suite too, so try it in whatever design software you use frequently if you haven’t already! It helps you – the presenter – organize and clarify your thoughts since they fit this visual model. Creating Cohesive Title Slides.

Visualization 116

Visualization Experimentation Software Strategy 116

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). Platform engineering, internal development platform – Platform engineering is at the forefront of modern software development, driving innovation and collaboration across teams.

Experimentation 71

Experimentation Testing Software Management 71

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 88

Cost-Benefit Modeling Manufacturing Interactive 88

Smarten

APRIL 18, 2023

and GPT-4 families of large language models, and fine-tuned using supervised and reinforcement learning techniques. While new medical techniques and tools can take time to refine and prove, doctors often leverage experimental techniques to save lives. One of the most intriguing AI developments is the recent focus on ChatGPT.

Digital Transformation 52

Digital Transformation Experimentation ROI Technology 52

AWS Big Data

JANUARY 9, 2024

Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Semantic search In semantic search, the search engine uses an ML model to encode text or other media (such as images and videos) from the source documents as a dense vector in a high-dimensional vector space.

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

CIO Business Intelligence

NOVEMBER 2, 2023

Awareness of FinOps practices and the maturity of software that can automate cloud optimization activities have helped enterprises get a better understanding of key cost drivers,” McCarthy says, referring to the practice of blending finance and cloud operations to optimize cloud spend. It depends on what business model you’re in.

Strategy 127

Strategy Data Processing Experimentation Optimization 127

CIO Business Intelligence

OCTOBER 18, 2023

Of roughly 2,500 CIOs surveyed recently by Gartner, 9% say they have already deployed gen AI applications, and a staggering 55% say they will deploy large language models (LLMs) in production by the end of 2025. Snap, LexisNexis, and Lonely Planet are also developing and training LLM models, each leveraging their own data stored on AWS. “We

Risk 134

Risk Manufacturing Enterprise Technology 134

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says. Employees will rally around a new business model, a new market opportunity, a new product offering,’’ Rybchin says. That starts to get people familiar with the agile model.”.

Experimentation 127

Experimentation Consulting Technology Machine Learning 127

Smarten

MAY 17, 2023

x, ChatGPT, Google’s Bard chatbot technology, and the AI service, Language Model for Dialogue Applications (LaMDA), among others.

Digital Transformation 52

Digital Transformation Experimentation Risk Testing 52

Domino Data Lab

APRIL 7, 2019

To build such systems, your software must understand the vocabulary, grammar and semantics of the text’s human language. A good NLP library will make it easy to both train your own NLP models and integrate with the downstream ML or DL pipeline. We assume that you need to build production-grade software. Pretrained models.

Deep Learning 110

Deep Learning Machine Learning Experimentation Modeling 110

Jedox

SEPTEMBER 11, 2019

Experimental” Technology. Is AI truly experimental technology? Just a few years ago, you had to purchase expensive hardware and software and hire a data scientist to build a model that today is most likely available “out of the box.” In most cases, the answer is no. ” Common FP&A Use Cases.

Forecasting 59

Forecasting Experimentation Sales Unstructured Data 59