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 →
How data quality and quantity affect the performance and potential of generative models Generative AI is a branch of artificial intelligence that focuses on creating new content or data from scratch, such as images, text, music, or speech. Generative models can learn from existing data and generate novel and realistic samples that can be used... Continue Reading →
The financial services industry is at the forefront of a technological revolution. Artificial Intelligence (AI) is more than just a buzzword; it offers unparalleled opportunities for financial institutions to innovate, streamline operations, and improve customer experiences. This blog post will discuss three compelling use cases for AI in financial services organizations. Before you start incorporating... Continue Reading →
Introduction Machine learning (ML) is a rapidly evolving technology that can bring significant value to various domains and applications. However, developing and deploying ML solutions is not a simple task. It requires a systematic and disciplined approach to manage the entire lifecycle of ML projects, from data collection and preparation to model development and evaluation... Continue Reading →
A large language model (LLM) is an AI model that can understand and generate human language. These models learn from vast amounts of text data, which helps them to capture the nuances and variations of human language and to produce appropriate and coherent text for a given prompt. LLMs are helpful but can be improved... Continue Reading →
Dave's Two Cents 