edge computing
edge computing on Beyond Market Intelligence: a running collection of 12 stories we have gathered and hand-picked because they are worth your time. Every post here touches on edge computing in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around edge computing, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
5 Best Local LLMs You Can Run on a Mac mini in 2026
Proprietary large language models offer remarkable capabilities, but configurability and on-device control are increasingly valuable. The Mac mini, powered by Apple Silicon, has surprisingly emerged as a potent platform for local AI processing. Utilizing tools like Ollama and LM Studio, users can now run capable models entirely on their Mac. Explore our ranking of the 5 best local LLMs you can run on a Mac mini in 2026, and discover how to transform your data workflows.
Presentation: Running AI at the Edge: Running Real Workloads Directly in the Browser
James Hall’s presentation, "Running AI at the Edge," explores the growing strategic and technical need to shift AI workloads from cloud environments to local devices—specifically, directly within the browser. Hall demonstrates practical approaches leveraging WebGPU, Transformers.js, and DuckDB to unlock near-native performance in JavaScript. Through compelling case studies, he outlines how to minimize data privacy risks, optimize inference, and establish robust evaluation practices. For those considering publication venues, similar discussions around ARR versus TMLR are frequently encountered—as explored in our recent community post.
Cloudflare Workers Accept Inbound TCP, with gRPC the First Protocol on Top
For eight years, Cloudflare Workers were limited to HTTP. That restriction ends now. Introducing inbound TCP connections via a new `connect(socket)` handler, routed through Spectrum, unlocks powerful new possibilities. Initially focused on gRPC—the first protocol supported—this expands Worker capabilities to include full-duplex communication in any language, effectively bringing container-like functionality to the edge. Workers now support unary and server-streaming through automatic gRPC-web translation. Currently in private beta, this development echoes Cloudflare’s broader innovation, as seen in projects like Kitesurf, a browser engine for automated workloads.
Cloudflare Adds Agent Tracing, with Truncation Limits and Uneven Payload Defaults
Cloudflare has expanded its tracing capabilities with the introduction of Agent Tracing, now incorporating spans for agent invocations, model calls, tool runs, and approvals within Workers traces. This feature enables session replay, offering deeper insights into agent workflows. While traces provide valuable context, users should note that they are not lossless, and payloads may be truncated due to default settings that vary by framework. Starting October 1, 2026, each span will be a billable event.
Cloudflare Introduces Cache Response Rules for Post-Origin Cache Control
Cloudflare's latest innovation, Cache Response Rules, represents a significant advancement in post-origin cache control. Previously limited to request attributes, Cache Rules now evaluate origin responses *before* they’re cached, providing granular control over what content enters the Cloudflare network. This rules engine empowers developers to optimize caching strategies and improve performance with unprecedented precision. For deeper insights into Cloudflare’s ongoing enhancements, explore "Cloudflare Adds Agent Tracing," detailing new span capabilities for agent invocations.
Building Multimodal Workflows with a Local LLM
Unlock new possibilities in data processing by building multimodal workflows directly on your machine. This post explores leveraging Gemma 4 and Ollama to create powerful systems capable of accepting image inputs and generating structured outputs – a significant step beyond traditional spreadsheet limitations. Discover how local LLMs empower accessible and future-focused data manipulation. For a foundational understanding of the underlying mechanics, explore "Backpropagation Explained for Beginners (Part 3): How Backpropagation Really Works," to deepen your knowledge of the neural networks at play.
Semi Edge Inference Idea [D]
The escalating cost of AI inference is a critical challenge. A compelling approach, as proposed by /u/komorra, involves strategically distributing model inference across both server and edge computing—client devices—to potentially alleviate datacenter processing burdens and shift costs. The concept of splitting proprietary models, with portions residing on clients and others on secure servers, offers a future-focused solution. This architecture, potentially realized through specialized client and server models communicating via standardized protocols, echoes initiatives like Cloudflare's recent introduction of Cloudflare Computer, exploring similar agent environments.
Cloudflare Launches Persistent, Stateful, Computer-like Environments for Agents
Cloudflare is redefining the landscape for AI agents with Cloudflare Computer, a new open-source runtime providing a more persistent and stateful environment—essentially, a digital "computer"—instead of fleeting containers. Built upon Cloudflare Isolates for rapid serverless execution, Computer promises significant cost reductions, speed improvements, and enhanced scalability for AI workflows. This innovative approach addresses a critical need as AI increasingly transforms incident response, as explored in our recent article on AI's impact on engineering teams.
AI is exposing the limits of traditional network architecture
AI’s rapid expansion is exposing critical limitations in traditional network architectures, hindering performance, reliability, and cost-effectiveness. Legacy systems, designed for static traffic, struggle to support the unpredictable, always-on demands of continuous inference and agent communication. A recent Bloomberg study commissioned by Tata Communications revealed that while AI is a board-level priority, many enterprises operate on outdated infrastructure. To unlock the full potential of AI investments, organizations must evolve their networks into intelligent, adaptive platforms—a shift Tata Communications is actively enabling.
Podcast: WebAssembly on the JVM: Feature Evolution, Performance, and the Transition to Endive
Unlock the future of server-side computation with our latest podcast episode: "WebAssembly on the JVM: Feature Evolution, Performance, and the Transition to Endive." Andrea Peruffo expertly details WebAssembly's expansion beyond the browser, highlighting significant performance gains through JIT compilation and showcasing real-world applications—from edge computing to modular plugin systems. Discover how this technology is transforming data management and enabling innovative architectures. For deeper insight into optimizing complex systems, explore our article, "The 3× Token Bill We Didn’t See Coming."
Understanding GPU Inference Workloads [D]
Delve into the complexities of GPU inference workloads with our latest exploration, sparked by a community discussion on sourcing compute. We're investigating common pain points encountered when utilizing services like RunPod or Vast.ai, seeking to understand your experiences and optimize deployment strategies. Share your insights in the comments or via direct message – your feedback is invaluable. For a deeper dive into related challenges within live streaming deployments, see our discussion on "CICD / KAFKA / KUBERNETES / Interview questions (MLE)."
AI chip startup Etched defies skeptics, hits $10.3B valuation from big-name investors
Etched, a nascent AI chip startup founded by Harvard dropouts, is rapidly gaining traction, achieving a remarkable $10.3 billion valuation from prominent investors. Unlike traditional approaches reliant on GPUs, Etched's innovative chips and memory components accelerate AI model inference directly, streamlining workflows and unlocking new possibilities. This advancement positions Etched as a key player in the evolving AI landscape. For further insight into the broader impact of AI on various industries, explore our recent piece on how Expedia is leveraging AI to accelerate incident investigation.