Analytics Vidhya

APRIL 8, 2023

In low-income nations, where prices can be unpredictable and challenging to measure, a combination of surveys and machine learning predictions can produce […] The post World Bank’s Machine Learning Model to Save Lives in Low-Income Areas appeared first on Analytics Vidhya.

Machine Learning 305

Machine Learning Modeling Measurement Analytics 305

Analytics Vidhya

DECEMBER 2, 2024

As indicated in machine learning and statistical modeling, the assessment of models impacts results significantly. Meet the F-Beta Score, a more unrestrictive measure that let the user weights precision over recall or […] The post What is F-Beta Score?

Machine Learning 208

Machine Learning Statistics Measurement Modeling 208

O'Reilly on Data

JANUARY 21, 2025

The Evolution of Expectations For years, the AI world was driven by scaling laws : the empirical observation that larger models and bigger datasets led to proportionally better performance. This fueled a belief that simply making models bigger would solve deeper issues like accuracy, understanding, and reasoning.

Cost-Benefit 299

Cost-Benefit Testing Interactive Software 299

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 282

Machine Learning Modeling Testing Risk Management 282

Analytics Vidhya

SEPTEMBER 30, 2022

Introduction Evaluation metrics are used to measure the quality of the model. Selecting an appropriate evaluation metric is important because it can impact your selection of a model or decide whether to put your model into production. This article was published as a part of the Data Science Blogathon.

Metrics 397

Metrics Measurement Data Science Publishing 397

CIO Business Intelligence

JANUARY 23, 2024

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

Measurement 141

Measurement Digital Transformation KPI Metrics 141

O'Reilly on Data

MARCH 25, 2025

Throughout this article, well explore real-world examples of LLM application development and then consolidate what weve learned into a set of first principlescovering areas like nondeterminism, evaluation approaches, and iteration cyclesthat can guide your work regardless of which models or frameworks you choose. How will you measure success?

Testing 174

Testing Data-driven Software Measurement 174

O'Reilly on Data

NOVEMBER 19, 2024

Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., at Facebook—both from 2020.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

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. The model will certainly need to be re-trained from time to time. Thomas Johnson said, “Perhaps what you measure is what you get.

Testing 363

Testing Measurement Consulting Modeling 363

Analytics Vidhya

JANUARY 15, 2024

In a startling revelation, researchers at Anthropic have uncovered a disconcerting aspect of Large Language Models (LLMs) – their capacity to behave deceptively in specific situations, eluding conventional safety measures.

Measurement 315

Measurement Risk Modeling Analytics 315

CIO Business Intelligence

DECEMBER 9, 2024

This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected. Foundation models (FMs) by design are trained on a wide range of data scraped and sourced from multiple public sources.

Enterprise 116

Enterprise ROI Cost-Benefit Measurement 116

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Any metric can and will be abused.

Marketing 364

Marketing Experimentation Metrics Testing 364

Analytics Vidhya

FEBRUARY 20, 2024

In a bid to bolster cybersecurity measures, Google has unveiled Magika, an AI-driven file detection tool aimed at identifying malicious files with unprecedented speed and accuracy.

Deep Learning 289

Deep Learning Measurement Modeling Analytics 289

CIO Business Intelligence

OCTOBER 24, 2024

Take for instance large language models (LLMs) for GenAI. Then there’s reinforcement learning, a type of machine learning model that trains algorithms to make effective cybersecurity decisions. But when it comes to cybersecurity, AI has become a double-edged sword.

Risk 128

Risk Measurement Optimization Machine Learning 128

David Menninger's Analyst Perspectives

JANUARY 15, 2025

ISG Research asserts that by 2027, one-third of enterprises will incorporate comprehensive external measures to enable ML to support AI and predictive analytics and achieve more consistently performative planning models. Few go deeper or gather external data in a way that makes it accessible across an enterprise.

Predictive Modeling 130

Predictive Modeling Forecasting Predictive Analytics Statistics 130

CIO Business Intelligence

NOVEMBER 7, 2024

As digital transformation becomes a critical driver of business success, many organizations still measure CIO performance based on traditional IT values rather than transformative outcomes. This creates a disconnect between the strategic role that CIOs are increasingly expected to play and how their success is measured.

Digital Transformation 128

Digital Transformation Metrics Measurement Key Performance Indicator 128

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

Additionally, while the tools available at the time enabled data teams to respond to quality issues, they did not provide a way to identify quality thresholds or measure improvement, making it difficult to demonstrate to the business the value of time spent remedying data-quality problems. With

Data Quality 130

Data Quality Dashboards Data-driven Software 130

CIO Business Intelligence

DECEMBER 10, 2024

Set clear, measurable metrics around what you want to improve with generative AI, including the pain points and the opportunities, says Shaown Nandi, director of technology at AWS. In HR, measure time-to-hire and candidate quality to ensure AI-driven recruitment aligns with business goals.

Sales 143

Sales Metrics Data-driven Measurement 143

CIO Business Intelligence

NOVEMBER 18, 2024

As a result, organisations are continually investing in cloud to re-invent existing business models and leapfrog their competitors. What began as a need to navigate complex pricing models to better control costs and gain efficiency has evolved into a focus on demonstrating the value of cloud through Unit Economics.

Measurement 111

Measurement Modeling Forecasting Metrics 111

CIO Business Intelligence

DECEMBER 18, 2024

Instead, were witnessing a maturation of the industry, shifting towards more sustainable business models and a focus on profitability. SaaS pricing is evolving While SaaS isnt dead, traditional SaaS subscription models are being strongly and rightfully challenged. AI: Disruption or evolution?

ROI 116

ROI Software Finance Uncertainty 116

CIO Business Intelligence

DECEMBER 20, 2024

From the discussions, it is clear that today, the critical focus for CISOs, CIOs, CDOs, and CTOs centers on protecting proprietary AI models from attack and protecting proprietary data from being ingested by public AI models. isnt intentionally or accidentally exfiltrated into a public LLM model?

Risk 105

Risk Measurement Interactive Modeling 105

CIO Business Intelligence

NOVEMBER 7, 2024

The government also plans to introduce measures to support businesses, particularly small and medium-sized enterprises (SMEs), in adopting responsible AI management practices through a new self-assessment tool. Meanwhile, the measures could also introduce fresh challenges for businesses, particularly SMEs.

Risk 130

Risk Management Measurement Consulting 130

CIO Business Intelligence

FEBRUARY 4, 2025

Instead of seeing digital as a new paradigm for our business, we over-indexed on digitizing legacy models and processes and modernizing our existing organization. This only fortified traditional models instead of breaking down the walls that separate people and work inside our organizations. And its testing us all over again.

Digital Transformation 144

Digital Transformation Sales Optimization Enterprise 144

Analytics Vidhya

JUNE 6, 2023

China is taking a significant step forward in regulating generative artificial intelligence (Generative AI) services with the release of draft measures by the Cyberspace Administration of China (CAC). These proposed rules aim to manage and regulate the use of Generative AI in the country.

Measurement 306

Measurement Management Analytics Modeling 306

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. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 363

Management Machine Learning Experimentation Metrics 363

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 364

Management Experimentation B2B Machine Learning 364

CIO Business Intelligence

OCTOBER 9, 2024

Depending on your needs, large language models (LLMs) may not be necessary for your operations, since they are trained on massive amounts of text and are largely for general use. As a result, they may not be the most cost-efficient AI model to adopt, as they can be extremely compute-intensive.

Strategy 143

Strategy Modeling Management Data Lake 143

CIO Business Intelligence

OCTOBER 22, 2024

By 2028, 40% of large enterprises will deploy AI to manipulate and measure employee mood and behaviors, all in the name of profit. “AI CMOs view GenAI as a tool that can launch both new products and business models. AI has the capability to perform sentiment analysis on workplace interactions and communications.

Enterprise 135

Enterprise Risk IoT Cost-Benefit 135

CIO Business Intelligence

DECEMBER 20, 2024

Its an offshoot of enterprise architecture that comprises the models, policies, rules, and standards that govern the collection, storage, arrangement, integration, and use of data in organizations. AI and machine learning models. Data modeling takes a more focused view of specific systems or business cases. Curate the data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

CIO Business Intelligence

MARCH 25, 2025

Using the companys data in LLMs, AI agents, or other generative AI models creates more risk. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time. Playing catch-up with AI models may not be that easy.

Risk 123

Risk Cost-Benefit Data-driven Digital Transformation 123

CIO Business Intelligence

OCTOBER 23, 2024

To address this, Gartner has recommended treating AI-driven productivity like a portfolio — balancing operational improvements with high-reward, game-changing initiatives that reshape business models. You must understand the cost components and pricing model options, and you need to know how to reduce these costs and negotiate with vendors.

Enterprise 141

Enterprise Cost-Benefit Broadcasting Risk 141

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 sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., PyTorch, TensorFlow, reinforcement learning, self-supervised learning).

Advertising 362

Advertising Cost-Benefit ROI Machine Learning 362

Analytics Vidhya

JUNE 26, 2023

The surge of Big Data has ushered in a new era, where businesses grapple with massive amounts of data measured in petabytes […] The post What is the Difference Between Data Science and Machine Learning? They are utilized by various entities, ranging from novice computer science students to major organizations like Netflix and Amazon.

Machine Learning 323

Machine Learning Data Science Big Data Measurement 323

CIO Business Intelligence

NOVEMBER 14, 2024

Online will become increasingly central, with the launch of new collections and models, as well as opening in new markets, transacting in different currencies, and using in-depth analytics to make quick decisions.” Vibram certainly isn’t an isolated case of a company growing its business through tools made available by the CIO.

ROI 119

ROI B2B Business Objectives Digital Transformation 119

Analytics Vidhya

DECEMBER 21, 2023

Introduction In today’s online world, having strong security measures is more important than ever. Traditional ways of logging in, like using a username and password, are not always secure enough. This has led to more cases of hacking and identity theft.

Deep Learning 316

Deep Learning Measurement Analytics Modeling 316

CIO Business Intelligence

DECEMBER 18, 2024

Our history is rooted in a traditional distribution model of marketing, selling, and shipping vendor products to our resellers. What were the technical considerations moving from a distribution model to a platform? As a platform company, measurement is crucial to success. This is crucial in a value-driven development model.

Digital Transformation 116

Digital Transformation Metrics Measurement ROI 116