Author: Phillip Joe

  • Perplexity AI’s Ad Integration Plan: A Deep Dive into the Risks and Realities

    Perplexity AI’s Ad Integration Plan: A Deep Dive into the Risks and Realities Perplexity AI’s recent pitch deck has ignited a flurry of reactions across the tech and marketing landscapes, with some lauding the ambition and others, quite frankly, questioning the sanity of its proposed advertising model. Let’s break down…

  • Why Agencies will Ultimately Need to figure out AI Agents to Survive.

    Why Agencies Will Ultimately Need to Figure Out AI Agents to Survive As a long-time agency person, I’ve experienced firsthand the challenges of working in an environment that’s constantly demanding more for less. I’ve been stretched across too many clients with not enough time, yet each one expects bespoke recommendations,…

  • How to Use AI in Marketing?

    Well, there are tons of ways you can use AI in marketing. Marketing is all about getting in front of people, and there are countless places to do that. But what exactly is AI? It’s a lot of things, really, but for this conversation, we’re focusing on generative AI. Generative…

  • A Simple In-Depth Guide to MLflow and Its Use Cases

    A Simple In-Depth Guide to MLflow and Its Use Cases

    MLflow is an open-source platform designed to manage the entire machine learning lifecycle, including experimentation, deployment, and model management. This article dives into how MLflow addresses common challenges in machine learning workflows, illustrating its functionality with practical examples.

  • What’s The Best way to Scale Data and MLPipelines with Airflow, Kubeflow, and Docker(Which One?)

    What’s The Best way to Scale Data and MLPipelines with Airflow, Kubeflow, and Docker(Which One?)

    Data and machine learning pipelines have become a critical components of many modern businesses. These pipelines are used for a variety of tasks, such as data processing, data analysis, model training, and model deployment. However, managing and orchestrating these pipelines can be complex and challenging, particularly as the data volume and models’ complexity continue to grow.…

  • A Simple Quick Guide To Vector Databases (If You Want It)

    A Simple Quick Guide To Vector Databases (If You Want It)

    Discover how vector databases excel in machine learning, AI applications, and real-time analytics, and learn how to select and integrate the right vector database for your needs. Ideal for data enthusiasts eager to enhance their systems with efficient, scalable, and versatile data management solution

  • Snowflake Arctic: The Swiss Army Knife of Enterprise AI

    Snowflake Arctic: The Swiss Army Knife of Enterprise AI

    Hey there, fellow tech aficionados and data sorcerers! If you’ve been dreaming of a world where enterprise AI is not only smart but also budget-friendly and open-source, then grab your snow goggles and a warm cup of cocoa—because we’re about to trek into Snowflake Arctic, the latest and greatest LLM…

  • Unlocking the Potential: A Guide to Increasing Success in ML/AI Projects

    Unlocking the Potential: A Guide to Increasing Success in ML/AI Projects Part 1: Understanding the Challenges and Common Pitfalls Introduction: Artificial Intelligence (AI) and Machine Learning (ML) projects promise to revolutionize businesses and drive process efficiencies. However, it is crucial to acknowledge the challenges and common mistakes that can lead to…