O'Reilly on Data

OCTOBER 30, 2023

While I am heartened to hear that the Executive Order on AI uses the Defense Production Act to compel disclosure of various data from the development of large AI models, these disclosures do not go far enough. These include: What data sources the model is trained on. Operational Metrics.

Measurement 298

Measurement Risk Modeling Metrics 298

IBM Big Data Hub

MAY 8, 2023

This blog continues the discussion, now investigating the risks of adopting AI and proposes measures for a safe and judicious response to adopting AI. Risk and limitations of AI The risk associated with the adoption of AI in insurance can be separated broadly into two categories—technological and usage.

Insurance 77

Insurance Risk Testing Data Quality 77

Domino Data Lab

AUGUST 6, 2021

All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

Machine Learning 145

Machine Learning Modeling Testing Risk 145

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

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

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

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

Cloudera

JULY 15, 2021

We recently hosted a roundtable focused on o ptimizing risk and exposure management with data insights. For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Area such as: .

Risk 96

Risk Optimization Management Insurance 96

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 Machine Learning Data Science 145

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform.

Risk 86

Risk Marketing Technology Management 86

CIO Business Intelligence

MAY 3, 2024

During pilot testing, UPS earned 50% reduction in the time agents spent resolving e-mails. The LLM gives agents the ability to confirm all responses suggested by the model. Firms are very concerned that without applying genAI to customer-facing apps, they are at high risk of disruption.” Turbo and GPT4.

Testing 136

Testing Sales Enterprise Digital Transformation 136

CIO Business Intelligence

MARCH 11, 2024

It will improve project management, help with requirements creation, assist developers with coding, cover the system with auto-tests, report defects, and improve deployment. These include security and data privacy concerns, low-quality data, reputational risks, and immature technology, to name a few.

Software 98

Software Testing Data-driven Risk 98

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 284

Metrics Reporting Measurement Finance 284

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 275

Modeling Machine Learning Risk Advertising 275

DataKitchen

MARCH 12, 2024

We kept adding tests over time; it has been several years since we’ve had any major glitches. Our vision was to create a flexible, state-of-the-art data infrastructure that would allow our analysts to transform the data rapidly with a very low risk of error. Data errors can cause compliance risks. That was amazing for the team.”

Metrics 120

Metrics Software Cost-Benefit Testing 120

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 289

Strategy Experimentation Uncertainty Machine Learning 289

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

CIO Business Intelligence

DECEMBER 11, 2023

“This regulation aims to ensure that fundamental rights, democracy, the rule of law and environmental sustainability are protected from high risk AI, while boosting innovation and making Europe a leader in the field,” said the press release issued by European Parliament. It is a myth that the AI Act will hamper innovation.

Risk 127

Risk Testing Insurance Cost-Benefit 127

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

CIO Business Intelligence

APRIL 5, 2024

The EU and US want to foster scientific information exchange between AI experts on either side of the Atlantic in areas such as developing benchmarks and assessing potential risks. At this stage in the development of AI, investment in testing and safety is far more effective than regulation,” Carlsson argued.

Risk 130

Risk Testing Consulting Machine Learning 130

DataRobot Blog

JUNE 3, 2022

The influence of the GPT-3 language model has the potential to be both beneficial and misused. . Generative Pre-trained Transformer 3 (GPT-3) is a language model that utilizes deep-structured learning to predict human-like text. Similarly, no one is focused on smaller models. What is GPT-3? When is enough ever enough?

Risk 52

Risk Predictive Modeling Modeling Technology 52

Cloudera

MARCH 28, 2019

The trouble is, mortgage lenders persist in relying on historical macro-economic assumptions in their models so they risk repeating the errors of a decade ago when banks – and their regulators – failed to recognize the warning signs from a far richer source: low-level micro-economic data. Risk management 3.0.

Risk 72

Risk Management Risk Management Machine Learning 72

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

CIO Business Intelligence

APRIL 5, 2024

Senate Bill 1047 , introduced in the California State Legislature in February, would require safety testing of AI products before they’re released, and would require AI developers to prevent others from creating derivative models of their products that are used to cause critical harms.

Risk 132

Risk Interactive Insurance Strategy 132

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. Contextual Relevance: Ensuring the data fed into LLMs is contextually relevant is paramount.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 129

Enterprise Modeling Testing Data-driven 129

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. You must detect when the model has become stale, and retrain it as necessary. The Core Responsibilities of the AI Product Manager. The AI Product Development Process.

Marketing 362

Marketing Experimentation Metrics Testing 362

AWS Big Data

OCTOBER 26, 2023

Data analysts and database developers want to use this data to train machine learning (ML) models, which can then be used to generate insights on new data for use cases such as forecasting revenue, predicting customer churn, and detecting anomalies. We also need an offline feature store to store features in feature groups.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

Decision Management Solutions

DECEMBER 17, 2021

In the recent McKinsey article discussing designing next-generation credit-decisioning models they outlined four best practices for automated credit-decisioning models for banks as they continue their digital transformations. Digital lending based on high-performance credit-decisioning models, says McKinsey, lead to: Increased revenue.

Modeling 52

Modeling Experimentation Visualization Risk 52

Decision Management Solutions

APRIL 23, 2019

, in which he states there are only three levers of value in insurance: Sell More, Manage Risk Better (aka underwriting and adjusting), and Cost Less to Operate. Let’s dive into greater detail on the second lever – Manage Risk Better. Insurers can also manage risk more effectively through continuous improvement.

Insurance 69

Insurance Risk Technology Management 69

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

OCTOBER 22, 2020

Taking the time to work this out is like building a mathematical model: if you understand what a company truly does, you don’t just get a better understanding of the present, but you can also predict the future. Since I work in the AI space, people sometimes have a preconceived notion that I’ll only talk about data and models.

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

CIO Business Intelligence

SEPTEMBER 7, 2023

Additionally, related issues during use are risk of hallucinations and prompt engineering. Additionally, it’s paramount within the financial services sector to ensure responsible AI and adherence to regulatory guidance for model risk. Exploiting technology vulnerabilities.

Risk Management 98

Risk Management Risk Testing Digital Transformation 98

IBM Big Data Hub

SEPTEMBER 28, 2023

An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. Business-targeted, IBM-developed foundation models built from sound data Business leaders charged with adopting generative AI need model flexibility and choice.

Testing 96

Testing Finance Enterprise Modeling 96

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 132

Machine Learning Testing Risk Modeling 132

CIO Business Intelligence

FEBRUARY 28, 2024

Essentially, the technology involves the replication of the human body in software models. Using these models, healthcare providers can test drugs and therapies with unprecedented speed and accuracy, reducing risks for both patients and physicians.

Informatics 121

Informatics Data-driven Digital Transformation Predictive Analytics 121

IBM Big Data Hub

APRIL 5, 2024

With data nearly everywhere, organizations often possess an existing repository acquired from running traditional HPC simulation and modeling workloads. In the automotive industry, intelligent simulation speeds up innovation in new models. However, in today’s market, consumers demand rapid releases of new models.

Manufacturing 73

Manufacturing Testing Enterprise Modeling 73