InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Vercel Releases JSON-Render: a Generative UI Framework for AI-Driven Interface Composition
Vercel has open-sourced json-render, a framework that enables AI models to create structured user interfaces from natural language prompts. Released under the Apache 2.0 license, it supports multiple frontend frameworks and features a catalog of components defined by developers. Community feedback includes both support and skepticism, highlighting its differences from existing standards.
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Green IT: How to Reduce the Impact of AI on the Environment
AI poses major challenges for green IT: each query consumes vast energy, GPU chips last only 2-3 years, and costs stay hidden from users. Regulatory frameworks like the EU AI Act fall short on enforcement, Ludi Akue said. In her talk What I Wish I Knew When I Started with Green IT she presented model compression, quantization, and novel architectures, using sustainability as a design constraint.
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QCon London 2026: Tools That Enable the Next 1B Developers
At QCon London 2026, Ivan Zarea, director of platform engineering at Netlify, discussed the impact of AI on web development, noting a surge in non-traditional developers among the 11 million users on the platform. He presented three pillars for developer tools: developing expertise, honing taste, and practicing clairvoyance, emphasizing the need for thoughtful architecture in a evolving landscape.
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Uber Launches IngestionNext: Streaming-First Data Lake Cuts Latency and Compute by 25%
Uber launches IngestionNext, a streaming-first data lake ingestion platform that reduces data latency from hours to minutes and cuts compute usage by 25%. Built on Kafka, Flink, and Apache Hudi, it supports thousands of datasets, enabling faster analytics, experimentation, and machine learning workloads globally.
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Revenium Unveils Tool Registry to Expose the True Cost of AI Agents
Revenium has announced the general availability of its Tool Registry, a new capability designed to give enterprises a complete, end-to-end view of what their AI agents actually cost.
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QCon London 2026: Ethical AI is an Engineering Problem
At QCon London 2026, Clara Higuera, responsible AI program lead at BBVA, presented how many of the risks associated with AI systems are fundamentally engineering challenges rather than purely governance or policy issues.
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QCon London 2026: Running AI at the Edge - Running Real Workloads Directly in the Browser
At QCon London 2026, James Hall discussed running AI workloads directly in browsers, highlighting local processing benefits such as enhanced privacy, reduced latency and cost. He examined technologies like Transformers.js and WebGPU, illustrated practical applications, and provided guidelines for browser-based AI implementation, emphasizing appropriate use cases and evaluation principles.
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QCon London 2026: Fixing the AI Infra Scale Problem by Stuffing 1M Sandboxes in a Single Server
Unikraft CEO Felipe Huici demonstrated waking the one-millionth VM on a commodity server in ten milliseconds at QCon London. The talk traced a decade from academic unikernel research to a platform offering stateless scale-to-zero VMs with full isolation. Using Firecracker and VM snapshots, sleeping workloads resume instantly, turning server density from a hardware problem into a scheduling one.
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AWS Expands Aurora DSQL with Playground, New Tool Integrations, and Driver Connectors
Amazon has announced several updates for Aurora DSQL, focusing on usability, integrations, and developer tooling. The improvements include a new interactive Aurora DSQL Playground that lets developers explore and experiment with the database directly in the browser, without registration or associated costs.
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Stripe Engineers Deploy Minions, Autonomous Agents Producing Thousands of Pull Requests Weekly
Stripe engineers describe Minions, autonomous coding agents generating over 1,300 pull requests per week. Tasks can originate from Slack, bug reports, or feature requests. Using LLMs, blueprints, and CI/CD pipelines, Minions produce production-ready changes while maintaining reliability and human review.
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QCon London 2026: Morgan Stanley Rethinks Its API Program for the MCP Era
Morgan Stanley engineers Jim Gough and Andreea Niculcea showed how they're retooling the bank's API program for AI agents using MCP and FINOS CALM. Live demos covered compliance guardrails, deployment gates, and zero-downtime rollouts across 100+ APIs. First API deployment shrank from two years to two weeks. They also demoed Google's A2A protocol running alongside MCP.
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QCon London 2026: Refreshing Stale Code Intelligence
At QCon London 2026, Jeff Smith discussed the growing mismatch between AI coding models and real-world software development. While AI tools are enabling developers to generate code faster than ever, Smith argued that the models themselves are increasingly “stale” because they lack the repository-specific knowledge required to produce production-ready contributions.
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AI Model Discovers 22 Firefox Vulnerabilities in Two Weeks
Claude Opus 4.6 discovered 22 Firefox vulnerabilities in two weeks, including 14 high-severity bugs, as nearly 20% of all critical Firefox vulnerabilities were fixed in 2025. The AI also wrote working exploits for two bugs, demonstrating emerging capabilities that give defenders a temporary advantage but signal an accelerating arms race in cybersecurity.
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Where Do Humans Fit in AI-Assisted Software Development?
An article on Martin Fowler’s blog by Kief Morris examines the role of humans in AI-assisted software engineering, arguing developers are unlikely to move fully “out of the loop.” Instead, teams may work “on the loop,” designing tests, specifications, and feedback mechanisms to guide AI agents, as industry discussions focus on how such systems should be verified and governed.
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QCon London 2026: Rewriting All of Spotify's Code Base, All the Time
At QCon London 2026, Spotify's Jo Kelly-Fenton and Aleksandar Mitic discussed Honk, an AI-powered coding agent that enables code migrations across Spotify's codebase. The system improves migration, reducing timelines drastically and addressing complexities that traditional scripts could not. Key challenges included handling edge cases and standardizing the codebase to facilitate review processes.