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

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. Just don't fall for their bashing of all other vendors or their silly claims, false, of "superiority" in terms of running 19 billion combinations of tests or the bonus feature of helping you into your underwear each morning. And I meant every word of it.

Testing 113

Testing Experimentation Risk Optimization 113

Occam's Razor

AUGUST 12, 2013

than multi-channel attribution modeling. By the time you are done with this post you'll have complete knowledge of what's ugly and bad when it comes to attribution modeling. You'll know how to use the good model, even if it is far from perfect. Multi-Channel Attribution Models. Linear Attribution Model.

Modeling 162

Modeling Optimization Marketing Interactive 162

CIO Business Intelligence

JUNE 13, 2024

Proof that even the most rigid of organizations are willing to explore generative AI arrived this week when the US Department of the Air Force (DAF) launched an experimental initiative aimed at Guardians, Airmen, civilian employees, and contractors. It is not training the model, nor are responses refined based on any user inputs.

Testing 119

Testing Experimentation Data Processing Modeling 119

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

Smart Data Collective

OCTOBER 13, 2022

These patterns could then be used as the basis for additional experimentation by scientists or engineers. Generative design is a new approach to product development that uses artificial intelligence to generate and test many possible designs. Automated Testing of Features. Generative Design. Quality Assurance.

Testing 125

Testing Cost-Benefit Experimentation Optimization 125

DataKitchen

JANUARY 20, 2021

Develop/execute regression testing . Test data management and other functions provided ‘as a service’ . The center of excellence (COE) model leverages the DataOps team to solve real-world challenges. Examples of technologies that can be delivered ‘as a service’ include: Source code control repository. Deploy to production.

Metrics 243

Metrics Experimentation Measurement Testing 243

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. Debugging AI Products.

Management 250

Management Metrics Machine Learning Modeling 250

Corinium

JUNE 6, 2019

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. It is also important to have a strong test and learn culture to encourage rapid experimentation. What is the most common mistake people make around data?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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. Outputs from trained AI models include numbers (continuous or discrete), categories or classes (e.g., spam or not-spam), probabilities, groups/segments, or a sequence (e.g.,

Advertising 299

Advertising Cost-Benefit ROI Machine Learning 299

CIO Business Intelligence

JULY 11, 2023

In recent years, we have witnessed a tidal wave of progress and excitement around large language models (LLMs) such as ChatGPT and GPT-4. The No Test Gaps Principle Under the No Test Gaps Principle, it is unacceptable that LLMs are not tested holistically with a reproducible test suite before deployment.

Modeling 95

Modeling Testing Experimentation Risk Management 95

CIO Business Intelligence

OCTOBER 17, 2024

Despite critics, most, if not all, vendors offering coding assistants are now moving toward autonomous agents, although full AI coding independence is still experimental, Walsh says. With existing, human-written tests you just loop through generated code, feeding the errors back in, until you get to a success state.”

Software 141

Software Testing Experimentation Consulting 141

O'Reilly on Data

MARCH 23, 2023

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, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 267

IT Modeling Testing Risk 267

Occam's Razor

AUGUST 13, 2012

Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. I explain three different models (Online to Store, Across Multiple Devices, Across Digital Channels) and for each I've highlighted: 1. What's possible to measure.

Modeling 125

Modeling Metrics Data Quality Data-driven 125

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. Medium companies Medium-sized companies—501 to 5,000 employees—were characterized by agility and a strong focus on GenAI experimentation.

Testing 129

Testing Cost-Benefit Experimentation Risk 129

CIO Business Intelligence

JULY 12, 2024

They’ve also been using low-code and gen AI to quickly conceive, build, test, and deploy new customer-facing apps and experiences. In a fiercely competitive industry, where CX is critical to differentiation, this approach has enabled them to build and test new innovations about 10 times faster than traditional development.

Experimentation 124

Experimentation Testing Enterprise Strategy 124

CIO Business Intelligence

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

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

Domino Data Lab

MAY 15, 2019

Unfortunately, a common challenge that many industry people face includes battling “ the model myth ,” or the perception that because their work includes code and data, their work “should” be treated like software engineering. These steps also reflect the experimental nature of ML product management.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Testing out a new feature.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

CIO Business Intelligence

MARCH 12, 2024

Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others. Gen AI is also reducing the time needed to complete testing, via automation, Ramakrishnan says.

Software 131

Software Experimentation Testing Cost-Benefit 131

IBM Big Data Hub

MAY 17, 2024

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

Modeling 96

Modeling Cost-Benefit Optimization Digital Transformation 96

Occam's Razor

SEPTEMBER 13, 2016

Bonus #2: The Askers-Pukers Business Model. Hypothesis development and design of experimentation. Ok, maybe statistical modeling smells like an analytical skill. If these 50 pass the sniff test, send the survey. Bonus #2: The Askers-Pukers Business Model. Three thoughts that explain the Econsultancy/Lynchpin graph.

Modeling 128

Modeling Reporting Strategy Consulting 128

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 90

Machine Learning Modeling Metadata Recreation/Entertainment 90

CIO Business Intelligence

AUGUST 20, 2024

Our mental models of what constitutes a high-performance team have evolved considerably over the past five years. Post-pandemic, high-performance teams excelled at remote and hybrid working models, were more empathetic to individual needs, and leveraged automation to reduce manual work.

IT 141

IT Digital Transformation Experimentation Risk 141

CIO Business Intelligence

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since.

Experimentation 130

Experimentation Strategy Machine Learning Interactive 130

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Knowledge Discovery 95

AWS Big Data

SEPTEMBER 5, 2024

In the context of Retrieval-Augmented Generation (RAG), knowledge retrieval plays a crucial role, because the effectiveness of retrieval directly impacts the maximum potential of large language model (LLM) generation. document-only) ~ 20%(bi-encoder) higher NDCG@10, comparable to the TAS-B dense vector model.

Metrics 111

Metrics Testing Experimentation Modeling 111

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

CIO Business Intelligence

NOVEMBER 19, 2024

This stark contrast between experimentation and execution underscores the difficulties in harnessing AI’s transformative power. Data privacy and compliance issues Failing: Mismanagement of internal data with external models can lead to privacy breaches and non-compliance with regulations. Of those, just three are considered successful.

Consulting 137

Consulting Cost-Benefit Experimentation Optimization 137

Rocket-Powered Data Science

OCTOBER 16, 2020

We build models to test our understanding, but these models are not “one and done.” In ML, the learning cycle is sometimes called backpropagation, where the errors (inaccurate predictions) of our models are fed back into adjusting the model’s input parameters in a way that aims to improve the output accuracy. (3)

Digital Transformation 142

Digital Transformation Experimentation Data Science Data Strategy 142

CIO Business Intelligence

AUGUST 23, 2024

Data scientists at Bayer have developed several proofs of concept of generative AI models on the new platform that remain in discovery and evaluation phase for “efficacy,” McQueen says, adding that the models won’t be in production until 2025. The R&D pipeline is pretty highly confidential at this point,” he says. It’s additive.”

Data Science 101

Data Science Experimentation Testing Modeling 101

The Unofficial Google Data Science Blog

JANUARY 16, 2018

We present data from Google Cloud Platform (GCP) as an example of how we use A/B testing when users are connected. Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. This simulation is based on the actual user network of GCP.

Testing 58

Testing Experimentation Measurement Modeling 58

CIO Business Intelligence

NOVEMBER 4, 2022

The company’s multicloud infrastructure has since expanded to include Microsoft Azure for business applications and Google Cloud Platform to provide its scientists with a greater array of options for experimentation. For McCowan, the key is to give scientists any and all tools that allow them to explore their hypotheses and test theories.

Data Lake 124

Data Lake IT Experimentation Data-driven 124

CIO Business Intelligence

MAY 9, 2024

Experimentation drives momentum: How do we maximize the value of a given technology? Via experimentation. This can be as simple as a Google Sheet or sharing examples at weekly all-hands meetings Many enterprises do “blameless postmortems” to encourage experimentation without fear of making mistakes and reprisal.

Enterprise 122

Enterprise Experimentation Sales Manufacturing 122

Domino Data Lab

MARCH 20, 2019

Our mission at Domino is to enable organizations to put models at the heart of their business. Today we’re announcing two major new capabilities in Domino that make model development easier and faster for data scientists. This pain point is magnified in organizations with teams of data scientists working on numerous experiments.

Management 97

Management Experimentation Data Science Modeling 97