Peter Song 
Retrieval-Augmented Generation has transformed how language models interact with knowledge bases, enabling them to access external information beyond their training data. Building a local RAG system with FAISS and Llama3 creates a powerful, privacy-preserving solution that runs entirely on your hardware without external API dependencies. This architecture combines Meta’s open-source Llama3 language model with Facebook’s … Read more
Model quantization has become essential for deploying large language models on consumer hardware, transforming models that would require enterprise GPUs into ones that run on laptops and mobile devices. By reducing the precision of model weights from 32-bit or 16-bit floating point numbers down to 8-bit, 4-bit, or even 2-bit integers, quantization dramatically decreases memory … Read more
Running large language models locally has become increasingly accessible as model architectures evolve and hardware capabilities expand. Whether you’re concerned about privacy, need offline access, want to avoid API costs, or simply enjoy the technical challenge, local LLM deployment offers compelling advantages. The choice between CPU, GPU, and Apple Silicon significantly impacts performance, cost, and … Read more
Machine learning systems in production face a critical challenge: managing features consistently across training and inference while maintaining low latency and high availability. A feature store solves this problem by providing a centralized repository for feature definitions, computations, and serving infrastructure. Building a feature store on AWS leverages the cloud provider’s extensive data and ML … Read more
Modern applications demand real-time data processing capabilities that can scale globally while maintaining consistency and reliability. Building such systems requires careful consideration of database architecture and event streaming infrastructure. CockroachDB, a distributed SQL database, paired with Apache Kafka, the industry-standard event streaming platform, provides a powerful foundation for creating robust real-time data pipelines that can … Read more
When you ask ChatGPT a question, get a product recommendation on Amazon, or watch your smartphone’s face unlock work instantly, it feels like magic. The AI simply understands and responds. But behind every seamless AI interaction lies an intricate system of components, processes, and infrastructure that most users never see. Understanding what happens behind the … Read more
The data revolution has created two critical roles that often confuse people outside the field—and sometimes even those within it. Data engineers and data scientists both work with data, both require technical skills, and both are essential for modern data-driven organizations. Yet these roles are fundamentally different in their focus, responsibilities, and the value they … Read more
Change Data Capture (CDC) has become essential for modern data architectures, enabling real-time data synchronization, analytics, and event-driven workflows. When building CDC pipelines on AWS, combining Kinesis Firehose with AWS Glue creates a powerful, serverless architecture that scales automatically and requires minimal operational overhead. This approach leverages AWS-managed services to capture database changes, stream them … Read more
Midjourney has transformed how creators, artists, designers, and casual users approach image generation, offering an AI-powered tool that translates text descriptions into stunning visual artwork. Unlike traditional design software that requires years of skill development or stock photo sites with limited customization options, Midjourney democratizes image creation—you describe what you envision using natural language, and … Read more
Detecting anomalies—unusual patterns that don’t conform to expected behavior—is crucial across countless domains. Fraudulent transactions hide among millions of legitimate purchases, equipment failures announce themselves through abnormal sensor readings, network intrusions masquerade as normal traffic, and manufacturing defects appear as outliers in quality metrics. While many sophisticated anomaly detection algorithms exist, k-means clustering offers an … Read more
