InfoQ Homepage Large language models Content on InfoQ
-
Neptune Combines AI‑Assisted Infrastructure as Code and Cloud Deployments
Now available in beta, Neptune is a conversational AI agent designed to act like an AI platform engineer, handling the provisioning, wiring, and configuration of the cloud services needed to run a containerized app. Neptune is both language and cloud-agnostic, with support for AWS, GCP, and Azure.
-
Meta Details GEM Ads Model Using LLM-Scale Training, Hybrid Parallelism, and Knowledge Transfer
Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across its platforms. The model addresses core challenges in recommendation systems (RecSys) by processing billions of daily user-ad interactions where meaningful signals such as clicks and conversions are very sparse.
-
TornadoVM 2.0 Brings Automatic GPU Acceleration and LLM Support to Java
The TornadoVM project recently reached version 2.0, a major milestone for the open-source project that aims to provide a heterogeneous hardware runtime for Java. The project automatically accelerates Java programs on multi-core CPUs, GPUs, and FPGAs. This release is likely to be of particular interest to teams developing LLM solutions on the JVM.
-
Meta's Optimization Platform Ax 1.0 Streamlines LLM and System Optimization
Now stable, Ax is an open-source platform from Meta designed to help researchers and engineers apply machine learning to complex, resource-intensive experimentation. Over the past several years, Meta has used Ax to improve AI models, accelerate machine learning research, tune production infrastructure, and more.
-
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.
-
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.
-
Replit Introduces New AI Integrations for Multi-Model Development
Replit has introduced Replit AI Integrations, a feature that lets users select third-party models directly inside the IDE and automatically generate the code needed to run inference.
-
NVIDIA Dynamo Addresses Multi-Node LLM Inference Challenges
Serving Large Language Models (LLMs) at scale is complex. Modern LLMs now exceed the memory and compute capacity of a single GPU or even a single multi-GPU node. As a result, inference workloads for 70B+, 120B+ parameter models, or pipelines with large context windows, require multi-node, distributed GPU deployments.
-
Arm Launches AI-Powered Copilot Assistant to Migrate Workflows to Arm Cloud Compute
At the recent GitHub Universe 2025 developer conference, Arm unveiled the Cloud migration assistant custom agent, a tool designed to help developers automate, optimize, and accelerate the migration of their x86 cloud workflows to Arm infrastructure.
-
Memori Expands into a Full-Scale Memory Layer for AI Agents across SQL and MongoDB
Memori is an innovative, open-source memory system that empowers AI agents with structured, long-term memory using standard databases like SQL and MongoDB. It seamlessly integrates into existing frameworks, enabling efficient data extraction and retrieval without vendor lock-in. Ideal for developers, Memori's modular design ensures reliability and scalability for next-gen intelligent systems.
-
Google's New LiteRT Accelerator Supercharges AI Workloads on Snapdragon-powered Android Devices
Google has introduced a new accelerator for LiteRT, called Qualcomm AI Engine Direct (QNN), to enhance on-device AI performance on Qualcomm-powered Android devices equipped with Snapdragon 8 SoCs. The accelerator delivers significant gains, offering up to a 100x speedup over CPU execution and 10x over GPU.
-
Google Launches Agent Development Kit for Go
Google has added support for the Go language to its Agent Development Kit (ADK), enabling Go developers to build and manage agents in an idiomatic way that leverages the language's strong concurrency and typing features.
-
Google Brings Colab Integration to Visual Studio Code
Google has announced the availability of a new Visual Studio Code extension that connects local notebooks to a Colab runtime. This allows developers to unify their previously separate local development setup and web-based Colab environment.
-
AnyLanguageModel: Unified API for Local and Cloud LLMs on Apple Platforms
Developers on Apple platforms often face a fragmented ecosystem when using language models. Local models via Core ML or MLX offer privacy and offline capabilities, while cloud services like OpenAI, Anthropic, or Google Gemini provide advanced features. AnyLanguageModel, a new Swift package, simplifies integration by offering a unified API for both local and remote models.
-
Olmo 3 Release Provides Full Transparency into Model Development and Training
The Allen Institute for AI has unveiled Olmo 3, an open-source language model family that empowers developers with full access to the model lifecycle, from training datasets to checkpoints. Featuring reasoning-focused variants and robust tools for post-training modifications, Olmo 3 promotes transparency, experimentation, and community collaboration, driving innovations in AI.