CIO Business Intelligence

AUGUST 21, 2024

According to Gartner, an agent doesn’t have to be an AI model. Starting in 2018, the agency used agents, in the form of Raspberry PI computers running biologically-inspired neural networks and time series models, as the foundation of a cooperative network of sensors. “It Adding smarter AI also adds risk, of course. “At

Risk 136

Risk Insurance Cost-Benefit Software 136

O'Reilly on Data

MAY 27, 2020

Under school district policy, each of Audrey’s eleven- and twelve-year old students is tested at least three times a year to determine his or her Lexile, a number between 200 and 1,700 that reflects how well the student can read. They test each student’s grasp of a particular sentence or paragraph—but not of a whole story.

Risk 355

Risk Testing Reporting Measurement 355

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. Should we risk loss of control of our civilization?” The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them.

Metrics 289

Metrics Reporting Measurement Finance 289

O'Reilly on Data

MAY 25, 2021

GPT-3 is essentially an auto-complete bot whose underlying Machine Learning (ML) model has been trained on vast quantities of text available on the Internet. I’d like to share my thoughts on GPT-3 in terms of risks and countermeasures, and discuss real examples of how I have interacted with the model to support my learning journey.

Modeling 350

Modeling Marketing Testing Machine Learning 350

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. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

JUNE 13, 2024

Not instant perfection The NIPRGPT experiment is an opportunity to conduct real-world testing, measuring generative AI’s computational efficiency, resource utilization, and security compliance to understand its practical applications. It is not training the model, nor are responses refined based on any user inputs.

Testing 119

Testing Experimentation Data Processing Modeling 119

CIO Business Intelligence

SEPTEMBER 9, 2024

As IT landscapes and software delivery processes evolve, the risk of inadvertently creating new vulnerabilities increases. These risks are particularly critical for financial services institutions, which are now under greater scrutiny with the Digital Operational Resilience Act ( DORA ).

Risk Management 115

Risk Management Risk Management IT 115

CIO Business Intelligence

MAY 17, 2022

Even if the AI apocalypse doesn’t come to pass, shortchanging AI ethics poses big risks to society — and to the enterprises that deploy those AI systems. The following real-world implementation issues highlight prominent risks every IT leader must account for in putting together their company’s AI deployment strategy.

Risk 145

Risk Consulting Data Science Machine Learning 145

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

CIO Business Intelligence

JANUARY 19, 2023

Giving up control: rewards outweigh the risks The benefits of greater delegation include an increase in the velocity of decision making and an increased sense of ownership and accountability, says Cisco Sanchez, SVP and CIO at Qualcomm, which has been increasing the pace of delegation. They just need visibility.

Testing 134

Testing Digital Transformation Risk Management 134

O'Reilly on Data

MAY 14, 2020

Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model. In reality, many candidate models (frequently hundreds or even thousands) are created during the development process. Modelling: The model is often misconstrued as the most important component of an AI product.

Management 363

Management Experimentation B2B Machine Learning 363

O'Reilly on Data

JUNE 7, 2022

DeepMind’s new model, Gato, has sparked a debate on whether artificial general intelligence (AGI) is nearer–almost at hand–just a matter of scale. Gato is a model that can solve multiple unrelated problems: it can play a large number of different games, label images, chat, operate a robot, and more. If we had AGI, how would we know it?

Modeling 363

Modeling Interactive Optimization Deep Learning 363

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 279

Modeling Machine Learning Risk Advertising 279

DataKitchen

NOVEMBER 20, 2021

A DataOps Engineer can make test data available on demand. We have automated testing and a system for exception reporting, where tests identify issues that need to be addressed. It then autogenerates QC tests based on those rules. Let’s say a data scientist has developed a model that works perfectly with training data.

Testing 246

Testing Machine Learning Data Warehouse Reporting 246

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority. Finalize testing.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

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 267

IT Modeling Testing Risk 267

CIO Business Intelligence

AUGUST 20, 2024

million to fine-tune gen AI models, and $20 million to build custom models from scratch, according to recent estimates from Gartner. Most SMBs don’t have the resources to create and maintain their own AI models, and they will need to work with partners to run AI models, he adds.

Risk 131

Risk Cost-Benefit Insurance ROI 131

O'Reilly on Data

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” And it was good.

Machine Learning 253

Machine Learning Testing Modeling Cost-Benefit 253

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Machine Learning 331

Machine Learning Predictive Modeling Software Modeling 331

DataKitchen

NOVEMBER 27, 2024

Without contextual specificity, these dimensions risk becoming check-the-box exercises rather than actionable frameworks that help organizations identify and address the root causes of data quality issues. At the same time, a data scientist might need to focus on model input features such as timeliness or uniqueness.

Data Quality 219

Data Quality Dashboards Metrics Cost-Benefit 219

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 124

Modeling Cost-Benefit IT ROI 124

KDnuggets

MARCH 17, 2022

Check out this article on using CTGANs to create synthetic datasets for reducing privacy risks, training and testing machine learning models, and developing data-centric AI products.

Machine Learning 149

Machine Learning Testing Risk Modeling 149

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk.

Advertising 299

Advertising Cost-Benefit ROI Machine Learning 299

O'Reilly on Data

JULY 11, 2023

He’s asking whether large language models eliminate programming as we know it, and he’s excited that the answer is “yes”: eventually, if not in the immediate future. Programmers who work for those companies risk losing their jobs to AI. Matt Welsh has been talking and writing about the end of programming as such.

Testing 250

Testing Software Visualization Interactive 250

IBM Big Data Hub

SEPTEMBER 7, 2023

Today we are announcing our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai , our studio for generative AI, foundation models and machine learning. Collectively named “Granite,” these multi-size foundation models apply generative AI to both language and code.

Modeling 101

Modeling Risk Unstructured Data Enterprise 101

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 338

Management Machine Learning Experimentation Metrics 338

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 182

Testing Data Quality Predictive Modeling Metrics 182

David Menninger's Analyst Perspectives

SEPTEMBER 24, 2024

erroneous results), and an equal amount (32%) mentioned legal risk. AI governance should address a number of issues, including data privacy, bias in data and models, drift in model accuracy, hallucinations and toxicity. Red-teaming is a term used to describe human testing of models for vulnerabilities.

Testing 130

Testing Modeling Enterprise Risk 130

DataKitchen

MAY 10, 2024

It highlights how DataKitchen’s Data Observation solutions equip organizations to enhance their development practices, reduce deployment risks, and increase overall productivity. Each addition or modification poses potential risks that could propagate errors into production environments. How Many Tests Ran In The Qa Environment?

Testing 133

Testing Cost-Benefit Data Quality Dashboards 133

CIO Business Intelligence

SEPTEMBER 10, 2024

The US Department of Commerce’s Bureau of Industry and Security (BIS) plans to introduce mandatory reporting requirements for developers of advanced AI models and cloud computing providers.

Reporting 131

Reporting Measurement Testing Risk 131

O'Reilly on Data

JUNE 18, 2024

Last month, TheNew York Times claimed that tech giants OpenAI and Google have waded into a copyright gray area by transcribing the vast volume of YouTube videos and using that text as additional training data for their AI models despite terms of service that prohibit such efforts and copyright law that the Times argues places them in dispute.

Advertising 353

Advertising Modeling Publishing Data Processing 353

CIO Business Intelligence

OCTOBER 3, 2024

From budget allocations to model preferences and testing methodologies, the survey unearths the areas that matter most to large, medium, and small companies, respectively. Healthcare-specific task-oriented models were also highly favored, with more than half (57%) of respondents using these models.

Testing 129

Testing Cost-Benefit Experimentation Risk 129

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

Rocket-Powered Data Science

JUNE 17, 2022

Explore and test-drive it (with a free trial) here. Reference ) Security information and event management (SIEM) on the Splunk platform is enhanced with end-to-end visibility and platform extensibility, with machine learning and automation (AIOps), with risk-based alerting, and with Federated Search (i.e., is here, now!

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

CIO Business Intelligence

OCTOBER 15, 2024

But continuous deployment isn’t always appropriate for your business , stakeholders don’t always understand the costs of implementing robust continuous testing , and end-users don’t always tolerate frequent app deployments during peak usage. CrowdStrike recently made the news about a failed deployment impacting 8.5

Enterprise 143

Enterprise Testing Business Objectives Experimentation 143

CIO Business Intelligence

OCTOBER 23, 2024

Despite AI’s potential to transform businesses, many senior technology leaders find themselves wrestling with unpredictable expenses, uneven productivity gains, and growing risks as AI adoption scales, Gartner said. CIOs should create proofs of concept that test how costs will scale, not just how the technology works.”

Enterprise 141

Enterprise Cost-Benefit Broadcasting Risk 141

O'Reilly on Data

JUNE 20, 2023

Knowing what makes up the supply chain is critical to enforcing the security of the AI system, establishing trust with the consumer of the AI’s output, and protecting your organization from undue risk. AI models are also created and delivered via supply chains. What factors does it weigh? .”

Modeling 204

Modeling Machine Learning Enterprise Technology 204