My background is a mix of systems engineering and applied machine learning. I’ve worked with PyTorch, Caffe, ML.NET, and DataRobo across research and production environments. Recent projects include LLM fine-tuning, real-time chatbots, AI-driven quality inspection bots, and logistics optimization tools. I’ve also contributed to delivery robot workflows and AI logistics planning systems where reliability matters more than hype. Languages like C++, Rust, Go, and Haskell come into play when performance and correctness are critical. I design AI systems with long-term maintenance in mind.

When Alexa, Amazon's popular virtual assistant, starts spewing nonsense due to a skill, it means that there's a glitch or error in one of the third-party skills enabled on the device. Skills are essentially apps for Alexa, allowing it to perform a wide range of additional functions beyond its built-in features. If a skill is poorly coded, not updated, or simply malfunctions, Alexa might respond to queries with irrelevant, incorrect, or nonsensical information. This scenario can also occur if the skill misunderstands the command due to ambiguous language or poor voice recognition, leading to unexpectedly humorous or confusing replies. Users can resolve such issues by disabling the problematic skill, checking for updates, or rephrasing their commands more clearly.

A Look Back at the Breakthroughs and a Roadmap to What’s Next The year 2025 marked a turning point for artificial intelligence. AI stopped being “experimental” and became operational, agentic, and deeply embedded in real-world workflows. What we saw wasn’t just better models—it was a fundamental shift in how humans and machines work together. As we step into 2026, the conversation is no longer about whether AI will transform industries, but how fast and who will lead that transformation. Let’s break it down. What Happened in AI in 2025 1. AI Agents Went Mainstream 2025 was the year of autonomous and semi-autonomous AI agents. We saw: - Multi-agent systems performing complex workflows - AI agents coordinating tasks across tools - Autonomous research, coding, analysis, and operations - Early enterprise adoption of agent orchestration platforms AI moved from “assistant” to digital worker. 2. Generative AI Became Infrastructure AI stopped being a novelty and became: - Embedded into enterprise software - Integrated into CRMs, ERPs, analytics, and DevOps - A default layer in productivity tools Companies stopped asking “Should we use AI?” and started asking:“How do we govern, scale, and secure it?” 3. AI Governance & Regulation Took Center Stage 2025 brought major focus on: - AI risk management - Explainability and auditability - Responsible AI frameworks - Compliance with global regulations Organizations realized that AI without governance is a liability, not an advantage. 4. No-Code & Low-Code AI Exploded AI development was no longer limited to engineers. Business users began: - Building AI workflows - Automating operations - Creating AI-powered apps - Deploying agents without writing code This democratization accelerated adoption across every industry. 5. AI Skills Became a Career Differentiator AI literacy became as important as digital literacy. Employers began prioritizing: - AI-fluent leaders - Prompt engineers & AI architects - Product managers who understand AI systems - Executives who can align AI with strategy

Welcome to the School of AI Community Blog — a space built for curious minds, builders, leaders, and innovators shaping the future with artificial intelligence. This blog is more than just updates or articles. It’s a shared learning space where ideas meet execution, where theory meets practice, and where the future of AI is explored together—one insight at a time. At School of AI, we believe AI is not just for researchers or engineers. It’s for product leaders, founders, analysts, educators, students, creators, and anyone who wants to understand how intelligent systems are transforming the world around us. This community exists to make AI practical, accessible, and impactful. Here’s what you can expect from this blog: - Deep dives into AI, automation, and emerging technologies - Practical guides, frameworks, and tutorials - Thought leadership on AI strategy, ethics, and innovation - Behind-the-scenes insights from our courses and programs - Community stories, experiments, and lessons learned - Trends shaping the future of work, business, and intelligence Whether you’re just starting your AI journey or leading transformation in your organization, this blog is designed to meet you where you are—and help you move forward with clarity and confidence. Most importantly, this is a community-first space. Your ideas, questions, and contributions matter. We encourage discussion, experimentation, and collaboration. AI is evolving fast, and the best way to keep up is to learn together. We’re excited to have you here. Welcome to the School of AI. Let’s build the future—intelligently.