Artificial intelligence has entered a phase where models are no longer the center of gravity, behaviors are. We’re deploying systems that reason, retrieve, act, and adapt in real time. They generate content, make decisions, and increasingly operate as semi‑autonomous agents woven into everyday business processes. This shift has opened extraordinary opportunities, but it has also... Continue Reading →
In a continuation of capturing lessons learned while getting my Master’s in Data Science from Boston University, I wanted to focus on how to create a real world project that is repeatable. Most machine learning projects don’t fail because the model is bad. They fail because the project can’t be reproduced, automated, or safely evolved... Continue Reading →
A new year, a new article. A quiet shift is happening in the business world, and it’s reshaping what it means to be a modern leader. While many companies are still experimenting with AI in pockets of the organization, a new class of businesses has already moved far ahead. These are the frontier firms, organizations... Continue Reading →
Machine learning models have transformed industries, from diagnosing diseases to predicting customer behavior. However, building a robust model is just half the battle. The real value comes from understanding what your ML results mean and how to communicate them responsibly. For data scientists, ML engineers, and tech professionals alike, interpreting machine learning results is as... Continue Reading →
Choosing the right path for your data can unlock incredible insights. Let’s demystify the main ways machines learn, so you can pick the best approach for your data science journeys. As I finish up my Master’s in Data Science from Boston University, I want to reflect on what I learn. This is the first post,... Continue Reading →
When Microsoft took the stage at Ignite 2025 conference, it wasn’t just unveiling another enterprise tech upgrade, it was heralding a seismic shift in the landscape of business AI. With the provocative declaration of 2026 as the “Year of the Agent,” Microsoft placed its newly rebranded Microsoft Foundry platform at the heart of this transformative... Continue Reading →
Generative AI is evolving into autonomous AI agents that can independently accomplish tasks with minimal human oversight. These agents streamline work processes by executing decisions and actions autonomously, significantly reducing operational delays. Currently, over half of companies have adopted these systems, which are projected to grow dramatically in market value. However, this increased autonomy necessitates stringent governance to prevent chaos and ensure accountability, marking a shift from mere assistance to achieving concrete outcomes in workflows.
Recent advancements in Large Language Models (LLMs) emphasize the importance of memory for maintaining context in extended dialogues. Two notable architectures, HEMA and Mnemosyne, have emerged: HEMA enhances dialogue memory through dual systems inspired by human cognition, significantly improving recall and coherence without retraining; Mnemosyne is designed for low-resource environments, enabling sustained interactions. Key challenges include managing context window limits, ensuring security, and developing scalable solutions. As research progresses, effective memory systems could transform LLM capabilities.
In the fast-evolving world of AI-driven applications, creating, orchestrating, and managing intelligent agents is becoming more powerful yet complex. Recognizing this shift, Microsoft has unveiled the Microsoft Agent Framework, positioning it as the next-generation platform for building production-grade AI agents and workflows. Released in public preview in October 2025, this open-source framework streamlines the development... Continue Reading →
In the world of large language models (LLMs), few topics generate more intrigue—and complexity—than memory. While we've seen astonishing leaps in capabilities from GPT-3 to GPT-4o and beyond, one crucial bottleneck remains: long-term memory. Today’s LLMs are incredibly good at reasoning over the contents of their prompt. But what happens when that prompt disappears? How... Continue Reading →
Dave's Two Cents 