AI Infrastructure
GPUs, silicon, data centres and the data platforms underneath.
The Context Ladder, Laid Bare: A Cross-Model Look at AI Model Local Deployment on Apple Silicon
A cross-model read of the October 2026 mlx-serve context-ladder leaderboard on an M4 Max box — prefill and decode indices, where models degrade past 8k, and what the numbers actually tell you before you deploy anything locally.
AI Model Local Deployment on Apple Silicon: October 2026 Cohort Leaderboard Across Six Models
A per-dimension leaderboard (quality, repeatability, throughput, latency, context) for six models served locally with mlx-serve on an M4 Max, covering Flash Next, Qwen3.8 27B, Muse Glimmer 30B, MiniCPM-V 4.7 35B-A3B and 1B, and LFM2.5-24B-A2B.
AI Model Local Deployment: Deep Dive Into Muse Glimmer 30B 4-bit on Apple Silicon
Comprehensive deep dive into Muse Glimmer 30B 4-bit performance, throughput, and capability profiles on Apple Silicon M4 Max using mlx-serve.
AI Model Local Deployment: Dense 27B Qwen Behaviour and MTP Speed Gains
A single-model deep dive into Qwen 3.8 27B 4-bit on Apple Silicon M4 Max, measuring how multi-token prediction reshapes decode speed and where quality breaks down under a structured test suite.
Mastering AI Model Local Deployment: A Deep Dive into LiquidAI 24B 4-bit on Apple Silicon
Comprehensive performance analysis and technical deep dive of the LiquidAI 24B 4-bit model pack running on Apple Silicon via mlx-serve, covering edge infrastructure readiness, throughput benchmarks, and quality scorecards.
Two Efficient MoEs, Different Trade-offs: Qwen3.8 Flash Next vs. LFM2.5 in AI Edge Infrastructure
A comprehensive head-to-head comparison of Qwen3.8 Flash Next and LiquidAI LFM2.5-24B-A2B within AI edge infrastructure, evaluating sparse MoE architectures, benchmark metrics on Apple Silicon M4 Max, and edge efficiency trade-offs.
India's Tech Services Giant HCL Is Getting Into the AI Datacenter Business — and OpenAI Quietly Hires Hiro: Timing, Pivots and the AI Value Chain
OpenAI's acquisition of personal finance startup Hiro reveals that sometimes being wrong is the right strategy — and the market simply hasn't caught up yet. A look at Ethan Bloch's 15-startup odyssey, the acqui-hire landscape reshaping AI, and why Indian tech media like ETCIO sees this as a bellwether for AI product strategy globally.
AI Cloud Infrastructure Companies in India: Deploying Llama Vision on GPU Droplets
A comprehensive guide to deploying Llama 3.2 Vision-Instruct models on DigitalOcean GPU Droplets, exploring AI cloud infrastructure in India, scaling strategies, and practical API integration.
The On-Site AI Push: Google Cloud, Accenture, and Cost Allocation for Shared GPU Clusters
Expanded article covering Google Cloud and Accenture's joint AI engineering unit, forward-deployed engineering, and cost allocation for shared GPU clusters.
India’s Tech Services Giant HCL Is Getting Into the AI Datacenter Business: Why AI Infrastructure Outvalues the Models
Research outline and comprehensive analysis on why infrastructure surrounding open AI—such as distribution hubs, model gateways, routing layers, and physical datacenters like India’s tech services giant HCL entering the AI datacenter business—is becoming more commercially valuable than individual models.
Architecting Local Intelligence: Mastering ai model local deployment on Apple Silicon
Exploring how the Mac mini and Mac Studio empower ai model local deployment, software workflows, agentic AI, and modern developer tooling.
Redesigning AI Server Hardware Architecture for the LLM Era
MatX's $500 million Series B, led by Jane Street and Situational Awareness, funds the MatX One — a purpose-built LLM processor based on a splittable systolic array and an SRAM-HBM hybrid memory design. A look at the funding, the architecture, the competitive field, and the execution risks ahead of a 2027 launch.