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Happy 10th year, JCertif!
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Welcome to Codetown!
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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InfoQ Reading List
Google Releases Gemini 4 Argon for Robotics Control, Simulation, and Policy Improvement
Google has released Gemini 4 Argon framing it as a general-purpose physical-reasoning model for robot control, Real2Sim scene construction, multimodal labeling of robot video, and iterative policy improvement, rather than as a single end-effector policy.
By Daniel DominguezCloudflare Develops Public Certificate Authority for Post-Quantum Web Security
Cloudflare is developing a public certificate authority for Merkle Tree Certificates (MTCs) to reduce the bandwidth overhead of post-quantum cryptography. A Chrome experiment served billions of MTCs to 50% of Chrome Beta 146 for selected domains, reporting 9% faster median performance. Wider deployment depends on browser support, transparency, and production-scale validation.
By Leela KumiliPodcast: Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM
In this episode, Edoardo Vacchi discusses the evolving landscape of WebAssembly on the backend, running Java workloads on GPUs using TornadoVM, and optimizing distributed AI inference using llm-d and vLLM on Kubernetes. Edoardo explains how llm-d manages cache locality (KV and prefix caches), request routing, and batch inference across Kubernetes clusters to maximize expensive GPU utilization.
By Edoardo VacchiAWS Launches TorchNeuron to Run PyTorch Models on AWS Trainium Without Modifications
At the recent PyTorch Conference North America 2026, Amazon introduced TorchNeuron, a native PyTorch backend that enables developers to run existing PyTorch code on AWS Trainium AI chips with virtually no code modifications.
By Sergio De SimoneArticle: Agentic AI Architecture: Current Challenges and Future Opportunities
Agentic AI architecture extends microservices and cloud-native architectures with AI agents that work with context, memory, and protocols such as MCP and A2A. The article covers bounded-context integration, task-dependent coordination strategies, new security risks, and observability needs. It expects gradual adoption alongside existing architectures, with platforms absorbing common components.
By Rafał Gancarz
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