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Presentation: Powering Enterprise AI Applications with Data and Open Source Software
Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale. By Francisco Javier Arceo
AlphaEvolve Enters Google Cloud as an Agentic System for Algorithm Optimization
Google Cloud announced the private preview of AlphaEvolve, a Gemini-powered coding agent designed to discover and optimize algorithms for complex engineering and scientific problems. The system is now available through an early access program on Google Cloud, targeting use cases where traditional brute-force or manual optimization methods struggle due to vast search spaces. By Robert Krzaczyński
Google Unveils New Tools and Libraries for Building AI Glasses Apps
With the release of the Android XR SDK Developer Preview 3, Google has introduced two new libraries to help developers create AI Glasses experiences, Jetpack Projected and Jetpack Compose Glimmer. ARCore for Jetpack XR has also been expanded to work with AI Glasses, adding motion tracking and geospatial capabilities. By Sergio De Simone
Podcast: Building a More Appealing CLI for Agentic LLMs Based on Learnings from the Textual Framework
Will McGugan, the maker of Textual and Rich frameworks, speaks about the reasoning of developing the two two libraries and the lesson learned. Also, he shares light on Toad, his current project, which he envisions being a more visually appealing way of interacting with agentic LLMs through command line. By Will McGugan
Magika 1.0: Smarter, Faster File Detection with Rust and AI
Google has just released version 1.0 of Magika, a substantial rewrite of its open-source file type detection system. The new version leverages AI to support a broader range of file types and is built in Rust for maximum speed and security. By Sergio De Simone
Learnings from Cultivating Machine Learning Engineers as a Team Manager
As an AI team manager, Vivek Gupta stays broadly informed to guide AI experts effectively and drive the team. Engineers need feedback on both technical and interpersonal skills, Gupta mentioned at Dev Summit Boston. He stresses learning time, asking for help, and cross-team collaboration. Mentorship, data handling, and human-in-the-loop validation are key to success for machine learning engineers. By Ben Linders
Article: InfoQ Java Trends Report 2025
This report summarizes how the InfoQ Java editorial team and several Java Champions currently see the adoption of technology and emerging trends within the Java and JVM space in 2025. We focus on Java the language, as well as related languages like Kotlin and Scala, the Java Virtual Machine (JVM), and Java-based frameworks and utilities. By Michael Redlich, Erik Costlow, Karsten Silz, Trisha Gee, Marit van Dijk, Richard Fichtner, Bert Jan Schrijver
Five AI Security Myths Debunked at InfoQ Dev Summit Munich
Katharine Jarmul challenged five common AI security and privacy myths in her InfoQ Dev Summit Munich 2025 keynote: that guardrails will protect us, better model performance improves security, risk taxonomies solve problems, one-time red teaming suffices, and the next model version will fix current issues. She said that current approaches to AI safety rely too heavily on technical solutions. By Karsten Silz
Presentation: Securing AI Assistants: Strategies and Practices for Protecting Data
Andra Lezza explains the criticality of data security for AI copilots, detailing the OWASP AI Exchange threat model and the OWASP Top 10 LLM risks. She reviews two copilot architectures - independent (single domain) and integrated (multi-tenant) - listing specific threats, controls, and best practices like granular authorization, templates, and DevSecOps to secure the entire AI data supply chain. By Andra Lezza
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stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
cvat
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
n8n
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
FunASR
A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.