ARTICLES
The Double-Edged Sword of Generative AI: Understanding & Navigating Risks in the Enterprise Realm
Executive Summary Generative AI models and LLMs, while offering significant potential for automating tasks and boosting productivity, present risks such as confidentiality breaches, intellectual property infringement, and data privacy violations that CXOs must...
Feature Engineering for Fraud Detection
Introduction Fraud detection is critical in keeping remediating fraud and services safe and functional. First and foremost, it helps to protect businesses and individuals from financial loss. By identifying potential instances of fraud, companies can take steps to...
Machine Learning at the Edge: Elements Needed for Scale
Learn about the elements you need to build an efficient, scalable edge ML architecture. There are four components that can help bring order to the chaos that is running ML at the edge and allow you to build an efficient, scalable edge ML architecture: Central...
When Machine Learning meets privacy
Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations. This posted has been republished by AIIA. To listen to the original podcast, please click HERE....
Centaur at Work: Writing a Newsletter
A Story of Many Failures and One Success In this blog, join me as I embark on the complex journey of semi-automating an AI-focused weekly newsletter. You'll get a first-hand look at a diverse set of tools and tactics that I've put to work on this real-life puzzle....
How To Fine-Tune Hugging Face Transformers on a Custom Dataset
Language models have come a long way in recent years, and their capabilities have expanded rapidly. With the right prompt, a language model can generate text that is almost indistinguishable from what a human would produce. In this post, we'll explore the art of...
Reducing GPU Costs for Production AI
This tech talk explores how you can efficiently use GPU resources for production inference. There are several ways to reduce GPU costs for production AI, including using cost-effective GPU options, using cloud providers, using containerization, using GPU acceleration...
The Only 3 ML Tools You Need
Image by Author At a rapid pace, many machine learning techniques have moved from proof of concepts to powering crucial pieces of technology that people rely on daily. In attempts to capture this newly unlocked value, many teams have found themselves caught up in the...
Seven Reasons Why Realtime Machine Learning Is Here To Stay
A very powerful trend is playing out right now — more and more top tech companies are making a larger part of their machine learning as realtime as possible. So much so that many are skipping the offline phase [1] and directly starting with realtime ML systems. More...
The Shapley Value for ML Models: What is a Shapley value, and why is it crucial to many explainability techniques?
This post was co-written with David Kurokawa. In our previous post, we made a case for why explainability is a crucial element to ensuring the quality of your AI/ML model. We also introduced a taxonomy of explanation methods to help compare and contrast different...
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