⫸ HighLevel migrates workloads to Firestore: This article explores how HighLevel, a SaaS platform, improved scalability and performance by migrating to Google Firestore. It highlights Firestore's serverless architecture, real-time capabilities, and role in powering HighLevel's AI solutions, enhancing productivity, reliability, and handling rapid database write surges.
⫸ AWS Cost Optimization: This article provides actionable tips for optimizing AWS cloud costs. It highlights strategies like minimizing data transfer costs, identifying underutilized EC2 instances, and using cost-allocation tags to reduce waste, streamline operations, and enhance budget management effectively.
⫸ Easily recreate your ADX dashboards as Real-Time Dashboards in Fabric: This article explains how to recreate Azure Data Explorer (ADX) dashboards as Real-Time Dashboards in Microsoft Fabric. It covers the benefits of retaining existing data architecture while leveraging Fabric's advanced features and provides step-by-step guidance for transitioning dashboards seamlessly into the Fabric ecosystem.
⫸ Learn the Basics of Well-Structured Data: This article explores data literacy, focusing on understanding, structuring, and using data effectively. It highlights key data traits like volume, history, detail, and consistency, explains well-structured data principles, and offers solutions like splitting and pivoting for improving poorly structured datasets.
⫸ Introducing ChatGPT Pro: This article introduces ChatGPT Pro, a $200 monthly plan designed for professionals tackling complex problems. It includes access to advanced AI models, such as o1 pro mode, offering enhanced compute capabilities for improved accuracy and reliability in fields like data science, programming, and research.
⫸ Sora is here: This article introduces Sora Turbo, an advanced video generation model by OpenAI, now available to ChatGPT Plus and Pro users. It enables realistic video creation from text, images, and videos, offering enhanced storytelling tools with safety features to ensure responsible use.
⫸ Training Language Models on Google Colab: This article provides a guide to fine-tuning Large Language Models on Google Colab without losing progress. It explains using Google Drive to save intermediate results, creating save and load functions for model checkpoints, and ensuring continuity in training across sessions.