CIO Business Intelligence

APRIL 7, 2023

It’s also the fifth-largest data center market in the nation, with a “low natural disaster risk, inexpensive power, and a competitive colocation and cloud market.” The city hasn’t lost its draw as a place for testing and launching new products either — there’s a growing startup community in Columbus.

IT 134

IT Digital Transformation Testing Marketing 134

IBM Big Data Hub

FEBRUARY 8, 2024

1 Slowly but surely, institutional investors started to recognize that companies could potentially improve financial performance and risk management by focusing on ESG issues like greenhouse gas emissions. The signatories committed to working together to help achieve the UN’s SDGs—a pledge that would be put to the test come 2020.

Measurement 84

Measurement Metrics Reporting Strategy 84

Smart Data Collective

FEBRUARY 14, 2023

It’s seemingly compulsory for most developers to build mobile versions of their applications or risk losing millions of potential users. Many people tend to forget their app updates, which can pose significant risks. But, using browser-based apps removes this risk altogether.

Risk 116

Risk Technology Optimization Machine Learning 116

datapine

APRIL 14, 2022

In 2017 the company wanted to take its shopping experience one step further by creating an augmented reality app that allowed users to test a product without having to leave their homes. In 2013, they took a slight risk and introduced a veggie smoothie to their previously fruit-only smoothie menu. Behind the scenes.

Big Data 244

Big Data Recreation/Entertainment Analytics Data-driven 244

erwin

JULY 30, 2020

was released in 2017. It’s tried and tested from an enterprise perspective and an in-demand certification for enterprise architects, so there are relatively low risks associated with adopting it. In 2008, the ownership of the brand was transferred to The Open Group, who have since revised and upgraded the standard.

Enterprise 138

Enterprise Visualization Modeling Testing 138

CIO Business Intelligence

MAY 16, 2023

higher [in 2022] than in 2017.” Blockchain Challenges Privacy and Security: The nature of blockchains as a public ledger presents personal privacy and security risks that likely limit the technology’s adoption in sensitive industries such as healthcare.

Advertising 92

Advertising Recreation/Entertainment Experimentation Enterprise 92

Smart Data Collective

DECEMBER 17, 2020

billion by 2025 , which is a remarkable 303% increase from 2017. The risk of medical errors is also significantly reduced. The automation of clinical workflows eliminates the risk of human error and ensures that nothing is missed during the diagnostic or treatment process. Enhanced safety.

Data-driven 118

Data-driven Big Data Software Risk 118

Smart Data Collective

SEPTEMBER 30, 2022

In 2019, this environment evolved, multiplying the number of blockchain marketing startups from 22 (2017) to 290 (2019) , which is more than 13 times in a year. In the absence of regulation, many blockchain pilot projects were at risk of ending up absolutely impractical. What about challenges?

Advertising 137

Advertising Marketing Technology Uncertainty 137

Jet Global

NOVEMBER 4, 2020

Although the most recent updates to the Organization for Economic Cooperation and Development (OECD) guidelines took place in 2017, some CFOs of multinational companies still don’t fully understand the implications of those changes, and how the changes affect transfer pricing at their companies.

Risk 98

Risk Uncertainty Sales Strategy 98

Cloudera

SEPTEMBER 10, 2021

By more effectively leveraging its petabytes of current and historical data, the IRS is working to stave off costly fraud and waste, more efficiently deliver on fundamental missions, and better protect taxpayers, including from risks such as identity theft.

Machine Learning 66

Machine Learning Statistics Data-driven Big Data 66

CIO Business Intelligence

JANUARY 23, 2023

That app, Microsoft Designer , is currently in closed beta test. the OpenAI model on which ChatGPT is based, is an example of a transformer, a deep learning technique developed by Google in 2017 to tackle problems in natural language processing.

Enterprise 131

Enterprise Deep Learning Recreation/Entertainment Interactive 131

Cloudera

MAY 15, 2018

My narrower vision of the next advancement in analytics is driven (or biased) by my quantitative risk management background and the critical role that computational simulation capabilities have played in many advances in the world of finance. Derman (2016), Cesa (2017) & Bouchard (2018)). Mauro Cesa. “A Additional resources.

Machine Learning 42

Machine Learning Recreation/Entertainment Finance Big Data 42

Smart Data Collective

DECEMBER 23, 2019

But while choosing open source code is important from a competitive perspective, that doesn’t mean it’s a simple or risk-free choice. If these companies don’t act fast, they could face similar blowback to what Equifax endured back in 2017. The shift towards containers is one example of this.

Software 54

Software Management Predictive Analytics Risk 54

IBM Big Data Hub

MAY 26, 2023

In 2017, 94% of hospitals used electronic clinical data from their EHR. With the growth in usage of digital technology and cloud in the life sciences industry, digital information is more readily available and at a greater risk for exploitation.

Consulting 77

Consulting Cost-Benefit Optimization Machine Learning 77

CIO Business Intelligence

APRIL 24, 2023

How we got here The most notable enabling technologies in generative AI are deep learning, embeddings, transfer learning (all of which emerged in the early to mid-2000s), and neural net transformers (invented in 2017). One of the most important of such architectures, the “transformer,” was developed in 2017.

Enterprise 52

Enterprise Deep Learning Modeling Machine Learning 52

IBM Big Data Hub

JULY 19, 2023

Code creation: Code co-pilot, code conversion, create technical documentation, test cases and more. Supply Chain: Demand forecasting, supply chain optimization, risk assessment and mitigation. Once fine tuned, the deployed model was used to inference on a test data to create the AE narratives (see Figure 2 for a sample).

Consulting 62

Consulting Machine Learning Manufacturing Optimization 62

Jen Stirrup

OCTOBER 3, 2019

The future is likely to be even more defined by the technology that is currently evolving – and if companies neglect to take a practical, thoughtful and responsible approach to implementing and developing this software, they run the risk of not being able to catch up with the consequences. . Miller, Wolf and Grodzinsky, 2017).

Technology 40

Technology Machine Learning Interactive Risk 40

bridgei2i

JULY 28, 2020

She’s the founder and CEO of StatWeather, a company, which was recognized as number one in climate technology globally in the year, 2017, by the Energy Risk Awards. We need people who can test. Not just that. Then, if the computer system goes down, then what do we do? Ria Persad, Founder & CEO StatWeather.

Enterprise 98

Enterprise Digital Transformation Insurance B2B 98

Jet Global

SEPTEMBER 4, 2020

When Microsoft released the next generation of the product in 2017, Microsoft Dynamics 365 for Finance and Supply Chain Management (D365F&SCM) , there were some significant changes behind the scenes. As of this writing, that product is still in testing, and no formal release date has been announced. Data Entities.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Alation

FEBRUARY 13, 2020

We also have some primary insurance entities in the group, but the main thing about reinsurance is that we’re taking care of the big and complex risks in the world. I know in February of 2017 Munich Re launched their own innovative platform as a cornerstone for analytics that involved a big data lake and a data catalog.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

Smarten

NOVEMBER 22, 2017

Your organization can test theories and hypotheses in a risk-free environment without making a market misstep and predict the outcome of pricing changes, new product introductions, supplier changes, added locations and other crucial proposed changes.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Cloudera

MAY 18, 2021

These interactions are captured and the resulting synthetic data sets can be analysed for a number of applications, such as training models to detect emergent fraudulent behavior, or exploring “what-if” scenarios for risk management. Value-at-Risk (VaR) is a widely used metric in risk management. Intraday VaR. Citations. [1]

Risk 92

Risk Marketing Risk Management Data-driven 92

CIO Business Intelligence

MARCH 2, 2023

With a talent for developing people and inspiring innovation from her teams, Anita Klopfenstein has built a powerhouse IT organization since joining Little Caesars in 2017 as its CIO. We’re actually gearing up to test it in a store. Define the enemy: What are the risks? The fourth value is ‘Never Give Up,’ which is so powerful.

Uncertainty 52

Uncertainty IT Management Testing 52

O'Reilly on Data

JUNE 19, 2019

A catalog or a database that lists models, including when they were tested, trained, and deployed. Model operations, testing, and monitoring. As machine learning proliferates in products and services, we need a set of roles, best practices, and tools to deploy, manage, test, and monitor ML in real-world production settings.

Modeling 194

Modeling Machine Learning Testing Metrics 194

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. The algorithm learned to identify children, not high-risk patients.

Analytics 145

Analytics Machine Learning Insurance Testing 145

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? All of these models are based on a technology called Transformers , which was invented by Google Research and Google Brain in 2017. It’s by far the most convincing example of a conversation with a machine; it has certainly passed the Turing test.

IT 262

IT Modeling Testing Risk 262

CIO Business Intelligence

MARCH 22, 2022

At Fractal, Tiwari will be responsible for the company’s digital transformation and overseeing IT operations, cybersecurity, and risk management. . In his 20 years’ experience in IT, Verma has led work on security, risk compliance, IoT, RPA, cloud, and business continuity planning. He will be based in Gurugram.

Internet Publishing and Broadcasting 98

Internet Publishing and Broadcasting Digital Transformation Insurance Recreation/Entertainment 98

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ That’s a risk in case, say, legislators – who don’t understand the nuances of machine learning – attempt to define a single meaning of the word interpret. Challenges for Transparency ”. Riccardo Guidotti, et al.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

APRIL 25, 2019

In 2017, the revenue opportunities exceeded $1.9 However, the dominant way to pay for smart contract-based goods and services has been with volatile cryptocurrencies, adding currency risk to businesses that operate on more stable national currencies such as dollars, yuan, or euros. Value opportunity: Digital money.

Cost-Benefit 109

Cost-Benefit Risk Marketing Finance 109

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for See also the paper “ The Case for Open Metadata ” by Mandy Chessell (2017–04–21) at IBM UK for compelling perspectives about open metadata. That definition plus the one-liner provide good starting points.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

MARCH 16, 2021

Leaders need to know how to avoid the risk of unethical, biased, or misunderstood models. Allows a researcher to test the importance of high-level, human interpretable concepts in their network. Automated Concept-based Explanation (ACE) is a hybrid approach that relies on pixel influence but also tests for the presence of concepts.

Modeling 122

Modeling Deep Learning Testing Optimization 122

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

The Unofficial Google Data Science Blog

APRIL 23, 2024

Multiparameter experiments, however, generate richer data than standard A/B tests, and automated t-tests alone are insufficient to analyze them well. Utility or risk for us is close to a step function: it is important to find some improvement, and less important to make that improvement as big as possible right away.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

MAY 20, 2021

Their tests are performed using C4.5-generated This carries the risk of this modification performing worse than simpler approaches like majority under-sampling. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Chawla et al.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

JULY 2, 2019

For more background about program synthesis, check out “ Program Synthesis Explained ” by James Bornholt from 2015, as well as the more recent “ Program Synthesis in 2017-18 ” by Alex Polozov from 2018. A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24). A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

MAY 31, 2022

Google did this in 2017 for more than 85,000 employees and hasn’t suffered a successful phishing attack since then. Why customer accounts are higher risk: Think about your customers who regularly access your mobile apps, websites, service desk, and other channels. Plus, consumers tend to be careless with passwords.

Finance 92

Finance Risk Technology Reporting 92