In our previous AI series, we delved into the realm of adversarial machine learning and introduced a system for classifying AI attacks. In this fourth installment of our AI Series, our focus will shift towards methods to mitigate these attacks. Let’s follow the same structure.. Previously, we categorized AI-related attacks into two main categories: Generative […]
Securing AI Models Read More »
In this part of the AI series, we will cover the topic of adversarial machine learning and attempt to create a taxonomy of AI attacks. We will also discuss mitigation strategies in Part #4. Q1. What is Adversarial Machine Learning? Adversarial machine learning is a technique employed by threat actors to manipulate machine learning models.
A Taxonomy of AI Attacks Read More »
OpenAI introduced a “Preparedness Framework” just before the 2024 holiday season. This framework grants the company’s board of directors the authority to revise decisions made by CEO Sam Altman and the leadership team. It is currently a work in progress, labeled as “beta”, and was developed in response to the events of November 2023 when
The UK AI Safety Summit, along with G7 and US actions, signalled progress in AI last week. Over 100 attendees from various sectors met at Bletchley Park for the world’s first international AI Safety Summit, exploring the future of AI. Several big tech companies and nations signed a ‘landmark’ voluntary agreement to allow governments, including
Global AI Regulations Read More »
Are you ready for the next revolution in retail? Think of an AI that doesn’t just automate tasks but actually acts with intention, much like a well-trained store manager who’s been in the trenches for decades—observing, planning, deciding, and learning on the fly. That’s the vision behind my upcoming book, Foundations of Agentic AI for
Unveiling the Next Frontier of Retail: Meet Agentic AI Read More »
Introduction Imagine you have a new type of user visiting your website or app – not a human customer, but an AI-powered agent. This agent can read, converse, and even take actions on behalf of humans. It’s as if millions of super-smart interns are out there, ready to interact with digital services. Welcome to the
Executive Summary Retailers face complex decisions in assortment planning – determining the optimal mix of products to stock across stores and channels. Traditional methods struggle to account for changing customer preferences, demand uncertainty, and the myriad factors influencing product performance. Reinforcement Learning (RL) offers a data-driven, dynamic approach to optimize assortments in real time. By
Assortment Planning and Optimization with Reinforcement Learning Read More »
Executive Summary Introduction Business leaders are witnessing a rapid evolution in artificial intelligence (AI) capabilities. What began with simple predictive analytics has advanced through prescriptive and generative AI, and is now entering the era of agentic AI. Unlike earlier forms of AI that mainly analyze data or generate content, agentic AI systems can autonomously make
Agentic AI and the Future of Automation Read More »
At AWS re:Invent 2024, Amazon Web Services (AWS) unveiled a comprehensive suite of advancements across artificial intelligence (AI), cloud computing, data management, and analytics, reinforcing its commitment to innovation and customer-centric solutions. 1. Introduction of ‘Nova’ AI Models AWS expanded its generative AI capabilities by launching the “Nova” series of foundation models: 2. Development of
AWS re:Invent 2024 Keynote Announcements Read More »
Executive Summary In the rapidly evolving retail landscape, effective assortment planning and optimization are crucial for retailers to meet customer demands, maximize profitability, and maintain a competitive edge. This article presents a comprehensive exploration of an advanced assortment allocation system designed to address the complexities of modern retail. By integrating sophisticated machine learning techniques, modeling
Assortment Planning and Optimization with AI Read More »
