Hi, I’m Changyi Yang 👋

Ref: https://www.xiaoyuzhoufm.com/episode/688cc1cc8e06fe8de7d920cd?s=eyJ1IjoiNjE4M2U4NGJlMGY1ZTcyM2JiNjgzZDViIn0%3D The world of Artificial Intelligence often highlights groundbreaking models and dazzling applications. But beneath the surface, a critical, often-overlooked component is driving this revolution: AI Infrastructure (AI Infra). Just as a powerful engine is essential for a high-performance car, robust AI Infra is the backbone of cutting-edge AI. Understanding AI Infra: A Cloud Analogy At its core, AI Infra can be understood through an analogy with cloud computing: Hardware: Think of AI chips (like GPUs) as the fundamental building blocks. Software: This mirrors cloud services, encompassing: Infra as a Service (IaaS): Providing raw compute, storage, and networking. Platform as a Service (PaaS): Offering development platforms and tools. Software as a Service (SaaS): This includes training and inference frameworks, which are crucial for developing and deploying AI models. Similar to the early days of search engine infrastructure, building AI Infra requires immense initial computational power and highly specialized capabilities. To achieve excellence in AI, core infrastructure is indispensable. We are currently in a pivotal moment for AI Infra development. ...

In February of this year, I received an internship offer from Amazon. At the time, I had no concept of what a summer internship would entail and came completely unprepared. As I write this blog post, my return offer status remains unknown, but I hope to provide an objective review of my entire internship experience. Week 1: Onboarding Week 1 was primarily onboarding. On the first day, I learned about my project - pure frontend! I was quite speechless when I found out, especially since the functionality seemed deceptively simple (I would regret this judgment multiple times later). The entire team was an internal platform team, which had the advantage of being very chill, but the downside was that the team’s QPS was on the order of 0.01, meaning there wasn’t particularly significant customer impact. ...

References: Interview on AI Infrastructure Career Path and Insights from AWS/Meta Job Transition and Interview Preparation for AI Infra in North America AI infrastructure has emerged as a key enabler in the acceleration of artificial intelligence technologies, supporting both training and inference processes. From scaling large AI models to optimizing hardware for inference, AI infra professionals are crucial to building the foundational platforms that power next-gen AI applications. Here’s an in-depth look at the latest developments in the field and how they are shaping career paths in AI infrastructure. ...

From AIEngineer: RAG Agents in Prod: 10 Lessons We Learned In the rush toward AI adoption, everyone is chasing cutting-edge models, fine-tuning pipelines, and building impressive prototypes. But the looming question remains: Where’s the ROI? Many companies pour massive resources into AI initiatives only to end up with sleek demos and very little actual business impact. This disconnect runs deeper than tooling—it’s rooted in what we expect AI to be good at. Much like Moravec’s Paradox in robotics (where high-level reasoning is easier for machines than basic perception or motor skills), modern AI excels at things we assume are hard—like coding, summarization, or legal analysis—but struggles with what we think should be easy: understanding context. ...

References: YouTube Video by Jordan Has No Life Kafka Summary Notes This article summarizes my personal understanding after watching the aforementioned video and reading the Kafka paper. I am still a student, so any inaccuracies or misunderstandings are unintentional—corrections are welcome. Kafka is a widely adopted distributed streaming platform. In this article, I will explore the key trade-offs Kafka makes in order to achieve its design goal of efficient log processing, and how these decisions contribute to Kafka’s architecture and performance. ...

The idea of building a personal site started back in September last year. I got a student-discounted instance from Alibaba Cloud (2 cores, 2GB RAM), and even went through the hassle of registering a domain name: changyi.fun. At first, I used WordPress. It worked — until it didn’t. I remember in one of my security classes, the professor specifically called out WordPress for being notoriously insecure. Around the same time, I tried to set up an SSL certificate (in the most complicated way possible via DNS challenge), and ended up completely breaking the site. I didn’t know back then that there were simpler ways. ...