O'Reilly on Data

OCTOBER 12, 2021

Kevlin Henney and I were riffing on some ideas about GitHub Copilot , the tool for automatically generating code base on GPT-3’s language model, trained on the body of code that’s in GitHub. We know how to test whether or not code is correct (at least up to a certain limit). First, we wondered about code quality.

Testing 300

Testing Measurement Consulting Modeling 300

CIO Business Intelligence

DECEMBER 19, 2023

Be proactive and serve with empathy It cannot be stressed enough how important it is to be active in ensuring that all services delivered to end users are fully vetted and tested to the point where there’s no room for complaints. Service delivery excellence is an attribute that far too many IT leaders fail to prioritize.

IT 139

IT Testing Metrics Optimization 139

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman. ” Watsonx.ai ” Watsonx.ai

Management 86

Management IT Machine Learning Metrics 86

DataKitchen

SEPTEMBER 20, 2021

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246

Testing Metrics Measurement Dashboards 246

O'Reilly on Data

DECEMBER 12, 2019

Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

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. If we want prosocial outcomes, we need to design and report on the metrics that explicitly aim for those outcomes and measure the extent to which they have been achieved.

Metrics 284

Metrics Reporting Measurement Finance 284

Occam's Razor

SEPTEMBER 15, 2011

Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself.

Measurement 166

Measurement Marketing Modeling Key Performance Indicator 166

CIO Business Intelligence

FEBRUARY 26, 2024

For any AI model, you can’t interpret the relevance and reliability of the output if you don’t understand the context of the data.” He points to a recent observation from GitHub CEO Thomas Dohmke, who noted 40% of computer-generated code was adopted by developers beta testing its Copilot AI automated code-writing system.

IT 128

IT Uncertainty Strategy Testing 128

CIO Business Intelligence

MARCH 13, 2024

We did side-by-side testing,” he says. Even though generative AI is a relatively new technology, it’s now difficult to imagine a world without it, given the impact it’s making, and the business value it can create. for every $1 spent. EY is one example of a company widely deploying gen AI.

IT 128

IT Consulting Testing Cost-Benefit 128

Smart Data Collective

SEPTEMBER 13, 2023

For instance, used Dell servers , which are refurbished, offer the same performance as Dell servers of the same make and model; however, they come for a fraction of the cost. Regular audits act as a preventive measure, which is more cost-effective than dealing with post-breach consequences. Financial health.

IT 103

IT Cost-Benefit Data Processing Software 103

Domino Data Lab

JANUARY 20, 2019

What if there was a way to quantitatively measure whether your machine learning (ML) model reflects specific domain expertise or potential bias? Testing with Concept Activation Vectors (TCAV): The Zebra. Introduction. with post-training explanations? on a global level instead of a local level ?

Testing 63

Testing Modeling Machine Learning Data Science 63

Cloudera

OCTOBER 20, 2021

What are the key climate risk measurements and impacts? Stress testing was heavily scrutinized in the post 2008 financial crisis. In a BIS advisory report , it was highlighted that the stress testing scenarios used by the banks were insufficient to capture the extreme risks and fluctuations that were realized. Assess Variables.

Risk 82

Risk Modeling Risk Management Measurement 82

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. The Core Responsibilities of the AI Product Manager. Product managers for AI must satisfy these same responsibilities, tuned for the AI lifecycle. Identifying the problem.

Marketing 362

Marketing Experimentation Metrics Testing 362

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. IBM Db2 can help solve these problems with its built-in ML infrastructure.

Modeling 90

Modeling Statistics Machine Learning Testing 90

DataKitchen

OCTOBER 27, 2022

The first step in solving that pain is to observe what’s happening with your data and analytics ‘estate’ and stick little thermometers at various points in the process and measure. Is the model still predicting accurately? You can’t improve what you can’t measure. The first step to enlightenment.

Dashboards 130

Dashboards Measurement Testing Modeling 130

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

MAY 14, 2024

Enterprises need to ensure that private corporate data does not find itself inside a public AI model,” McCarthy says. You don’t want a mistake to happen and have it end up ingested or part of someone else’s model. We’re keeping that tight control and keeping it in the private cloud.”

IT 52

IT Data Processing Enterprise Modeling 52

CIO Business Intelligence

APRIL 17, 2024

They had ChatGPT write the script, and other gen AI tools to create a digital person who reads the script, a scalable process with at least one measurable benefit: speed. Helping software developers write and test code Similarly in tech, companies are currently open about some of their use cases, but protective of others.

Enterprise 129

Enterprise Testing Digital Transformation Software 129

DataRobot

MAY 27, 2021

Michael earned his MD and PhD degrees from Emory University, and today his research combines mathematical and epidemiological models with high-throughput phage-display–based serological laboratory investigations. In particular, Mina believes that our failure to test effectively has allowed COVID-19 to spread.

Testing 98

Testing Machine Learning Measurement Publishing 98

CIO Business Intelligence

JUNE 13, 2023

Once wild and seemingly impossible notions such as large language models, machine learning, and natural language processing have gone from the labs to the front lines. Now some AI architects are eyeing the long-forgotten model of analog computation where values are expressed as voltages or currents.

IT 145

IT Scorecard Software Modeling 145

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. DataOps ensures that the data retrieved is relevant, high-quality, and up-to-date.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

CIO Business Intelligence

JUNE 8, 2023

There’s a strong need for workers with expertise in helping companies make sense of data, launch cloud strategies, build applications, and improve the overall user experience. This demand has driven up salaries for IT roles, especially those around development, engineering, and support. percent since 2021, according to Dice.

IT 139

IT Digital Transformation Software Risk 139

DataKitchen

MARCH 12, 2024

We kept adding tests over time; it has been several years since we’ve had any major glitches. DataKitchen helped us completely transform our operations by broadening our testing definition. Tests assess important questions, such as “Is the data correct?” Data errors can cause compliance risks. DataKitchen Customer Quotes “.

Metrics 120

Metrics Software Cost-Benefit Testing 120

CIO Business Intelligence

MARCH 5, 2024

India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.

Testing 128

Testing Modeling Cost-Benefit Reporting 128

datapine

JANUARY 24, 2021

Additionally, incorporating a decision support system software can save a lot of company’s time – combining information from raw data, documents, personal knowledge, and business models will provide a solid foundation for solving business problems. That being said, it seems like we’re in the midst of a data analysis crisis.

IT 317

IT Statistics KPI Data-driven 317

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. Data and tool tests. Observability users are then able to see and measure the variance between expectations and reality during and after each run.

Testing 130

Testing Statistics Measurement Metrics 130

CIO Business Intelligence

JULY 28, 2023

Perhaps those individuals have never done well in school, or they struggle taking tests, or get impatient quickly; but because they’ve not spoken with a professional, they may not even be aware. But doing so may require some changes in approach. This is the new corporate reality. Neurodiversity does not define your success.

IT 98

IT Measurement Testing Management 98

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

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? Under Velocity, the Mean Time to Deliver Data metric measures the time it takes to deliver data. The Data Change Request Ratio metric measures the rate of business demand for data. The Mean Time to Recovery metric measures how quickly defects can be resolved. Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

CIO Business Intelligence

APRIL 27, 2023

These IT pros work closely with developers to ensure security measures such as firewalls, encryption, and intrusion detection systems are included in software, systems, networks, and applications. And according to the latest 2023 Dice Tech Salary Report , you don’t need to reach for an executive career in IT to earn a six-figure salary.

IT 116

IT Software Risk Management 116

Domino Data Lab

MARCH 3, 2021

It’s often stated that nothing changes inside an enterprise because you’ve built a model. In some cases, data science does generate models directly to revenue, such as a contextual deal engine that targets people with offers that they can instantly redeem. But what about good decisions?

Metrics 93

Metrics Modeling Sales Data Science 93

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

CIO Business Intelligence

JUNE 13, 2022

She says she believes organizations of all kinds, including her own, should be advancing their use of data to move beyond measuring outputs and even measuring outcomes to “get to impact, to driving long-term delta change.”. All that together, though, is nothing compared to the turbulence that CIOs are seeing today.

IT 144

IT Digital Transformation Strategy Internet of Things 144

Cloudera

OCTOBER 14, 2020

Not many other industries have such a sophisticated business model that encompasses a culture of streamlined supply chains, predictive maintenance, and unwavering customer satisfaction. Step 1: Using the training data to create a model/classifier. Fig 2: Diagram showing how CML is used to build ML training models. The Process.

Machine Learning 98

Machine Learning Modeling Cost-Benefit Testing 98

Domino Data Lab

JULY 17, 2021

The system here will identify, via some meaningful sense, which existing speakers’ model does the utterance match. If the unknown utterance is spoken by a speaker outside the list of existing speakers, the model will nonetheless map it to some speaker from that list. The existing applications of person authentication include :-.

Modeling 64

Modeling Testing Machine Learning Measurement 64