Browsing: Architecture

Understanding modern AI architectures is harder than ever. Open any Hugging Face repository and you’ll usually find massive config files, layer definitions, parameter counts, and model…

Most AI systems today work in turns. You type or speak, the model waits, processes your input, and then responds. That’s the entire interaction loop. Thinking…

A team researchers from China have released AntAngelMed, a large open-source medical language model that the team describes as the largest and most capable of its…

class MemoryStoreTool(Tool): name = “memory_store” description = “Save an important fact or piece of information to long-term memory.” def __init__(self, memory: MemoryBackend): self._mem = memory def…

Vector databases have graduated from experimental tooling to mission-critical infrastructure. In 2026, vector databases serve as the core retrieval layer for RAG pipelines, semantic search systems,…

Voice AI has a dirty secret. Most text-to-speech systems sound fine — until they don’t. They can read a sentence. What they cannot do is mean…

The fundamental tension in conversational AI has always been a binary choice: respond fast or respond smart. Real-time speech-to-speech (S2S) models — the kind that power…

Training frontier AI models is, at its core, a coordination problem. Thousands of chips must communicate with each other continuously, synchronizing every gradient update across the…

For years, the way large language models handle inference has been stuck inside a box — literally. The high-bandwidth RDMA networks that make modern LLM serving…

The dominant recipe for building better language models has not changed much since the Chinchilla era: spend more FLOPs, add more parameters, train on more tokens.…