A comprehensive journey through OpenAI’s GPT model evolution from 2018 to 2025. From the 117M parameter GPT-1 to today’s trillion-parameter GPT-5.2, explore the revolutionary advances in context windows, pricing, capabilities, and market adoption that have transformed AI.
Read more →Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Building Interoperable Healthcare Data Systems for AI: A Complete Guide to FHIR, Standards, and Governance
Healthcare AI fails when data remains siloed. This article explores how FHIR, SNOMED CT, and platform thinking enable interoperable healthcare data systems for AI at scale, with insights from EU, UK, and Ireland initiatives.
Read more →Azure Container Apps Dynamic Sessions: Secure Code Execution for AI Agents
AI agents that can write and execute code introduce significant security risks—from data exfiltration to resource abuse. Azure Container Apps Dynamic Sessions provides a solution: ephemeral, sandboxed execution environments that isolate agent-generated code from your production infrastructure. This comprehensive guide explores how to implement secure code execution for AI code interpreters, automated testing agents, and […]
Read more →Data Quality for AI: Ensuring High-Quality Training Data
Data quality determines AI model performance. After managing data quality for 100+ AI projects, I’ve learned what matters. Here’s the complete guide to ensuring high-quality training data. Figure 1: Data Quality Framework Why Data Quality Matters Data quality directly impacts model performance: Accuracy: Poor data leads to poor predictions Bias: Biased data creates biased models […]
Read more →Production Model Deployment Patterns: From REST APIs to Kubernetes Orchestration in Python
After deploying hundreds of ML models to production across startups and enterprises, I’ve learned that model deployment is where most AI projects fail. Not because the models don’t work—but because teams underestimate the engineering complexity of serving predictions reliably at scale. This article shares production-tested deployment patterns from REST APIs to Kubernetes orchestration. 1. The […]
Read more →Migration Guide: From Semantic Kernel & AutoGen to Microsoft Agent Framework – Part 10
Complete migration guide from Semantic Kernel and AutoGen to Microsoft Agent Framework. Before/after code examples and step-by-step instructions.
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