def draw_ring(ring: ConsistentHashRing, dist: Dict[str, int], title: str): node_ids = sorted(ring.nodes.keys()) plt.figure(figsize=(8, 8)) ax = plt.gca() ax.set_title(title) if not node_ids: plt.text(0.5, 0.5, “Ring is empty”, ha=”center”, va=”center”) plt.axis(“off”) plt.show() return G = nx.Graph() for nid in node_ids: G.add_node(nid) for i…

For the modern AI developer productivity is often tied to a physical location. You likely have a ‘Big Rig’ at home or the office—a workstation humming with NVIDIA RTX cards—and a ‘Travel Rig,’ a sleek laptop that’s perfect for coffee…

The 7 Biggest Misconceptions About AI Agents (and Why They Matter) (click to enlarge)Image by Author   AI agents are everywhere. From customer support chatbots to code assistants, the promise is simple: systems that can act on your behalf, making…

In this article, you will learn how to cluster a collection of text documents using large language model embeddings and standard clustering algorithms in scikit-learn. Topics we will cover include: Why LLM-based embeddings are well suited for document clustering. How…

In this article, you will learn how speculative decoding works and how to implement it to reduce large language model inference latency without sacrificing output quality. Topics we will cover include: Why large language model inference is often memory-bound rather…

In the high-stakes world of AI, ‘Context Engineering’ has emerged as the latest frontier for squeezing performance out of LLMs. Industry leaders have touted AGENTS.md (and its cousins like CLAUDE.md) as the ultimate configuration point for coding agents—a repository-level ‘North…