Your central hub for AI news and updates on Infrastructure. We're tracking the latest articles, discussions, tools, and videos from the last 7 days.
Fyra's Brief
At AWS re:Invent 2025, Amazon emphasized enterprise AI with AI agents that can learn and work independently, upgraded CPUs, and advanced LLM capabilities.
AWS re:Invent 2025 emphasizes enterprise AI focus with AI agents, custom LLMs, and advanced CPUs, further strengthening their position in the industry.
Fyra's Brief
The Celonis Process Intelligence Engine has been successfully implemented in various public sectors, improving accountability, reducing costs, and enhancing transparency.
The implementation of Celonis's Process Intelligence Engine in the public sector has shown promising results in improving accountability and reducing costs, highlighting the potential for widespread adoption in the industry.
Fyra's Brief
NVIDIA CUDA 13.1 introduces CUDA Tile, a tile-based programming model, and updates to the CUDA platform for improved performance and accelerated computing.
CUDA 13.1 is a crucial update that enables developers to unlock new levels of performance and efficiency in GPU programming, making it a must-read for all AI professionals.
Fyra's Brief
Amazon SageMaker AI now enables serverless model fine-tuning with popular AI models, reducing the process from months to days through easy-to-use interface and auto-provisioning of compute resources.
Amazon SageMaker AI's serverless model fine-tuning capability marks a significant step in democratizing AI model customization and deployment without substantial infrastructure investments.
Fyra's Brief
AWS announced AI Factories, allowing businesses to run AI systems on-premises, addressing data sovereignty concerns and competing directly with Nvidia's offerings.
The AI Factories offering could disrupt the cloud-based AI services market, but its success will depend on the scalability and adoption of in-house AI systems.
Fyra's Brief
NVIDIA has introduced a new KV cache quantization format, NVFP4, which reduces memory footprint by up to 50% and improves performance across various inference workloads with minimal accuracy loss.
NVIDIA's NVFP4 KV cache introduction enables new possibilities for large-scale inference performance, but further research is needed to explore its full potential.
Fyra's Brief
Continue's Mission Control now features Metrics, enabling transparent tracking of cloud agent performance, productivity, and automation trends.
The release of Metrics in Mission Control is a significant step forward for AI professionals, offering a much-needed visibility into cloud agent performance and automation trends.
Fyra's Brief
Amazon SageMaker HyperPod now offers checkpointless training that eliminates the need for traditional checkpoint-based recovery, and elastic training that enables AI workloads to automatically scale based on resource availability.
This update is beneficial for AI professionals as it reduces model training completion times and increases efficiency, enabling them to focus on enhancing model performance.
Fyra's Brief
NVIDIA unveils Aerial Omniverse Digital Twin for AI-native 6G networks, enabling efficient design, testing, and deployment of complex RAN systems.
The AODT is a critical step towards developing AI-native 6G networks, enabling more efficient design, testing, and deployment of complex RAN systems.
Fyra's Brief
Pika partnered with fal to bring its powerful Model 2.2 to Pika's high-performance inference infrastructure, enabling seamless AI video creation for millions of developers.
The partnership between Pika and fal brings high-quality AI video creation capabilities to millions of developers, accelerating innovation in the creative AI space.
Fyra's Brief
NVIDIA released data center energy optimized power profiles to improve energy efficiency and performance in power-constrained facilities.
This article matters to AI professionals as it highlights NVIDIA's efforts to enhance data center energy efficiency, a critical concern for AI workloads.
Fyra's Brief
Alphabet's AI chip technology is seen as a significant growth driver for the company, with Gemini 3 receiving strong reviews, potentially worth $900 billion in future revenue.
Alphabet's AI chip technology has significant growth potential, but the company's dominance in the market raises concerns about potential monopolies and price increases.
foundry local runs AI models locally with on-device inference to keep data on device and reduce cloud dependencies...
Just happened to cross this and thought this seemed interesting. Here are some benchmarks: **Test Configuration** * **Hardware**: AMD EPYC 9004 Seri...
Run Windows Subsystem For Android on your Windows 10 and Windows 11 PC using prebuilt binaries with Google Play Store (MindTheGapps) and/or Magisk or ...
Community talk
BREAKING: OpenAI begins construction on massive $4.6 Billion "GPU Supercluster" in Australia (550MW Hyperscale Campus)
BREAKING: OpenAI to build massive $4.6 Billion "GPU Supercluster" in Australia (550MW Hyperscale Campus by 2027)
BREAKING: OpenAI and NextDC to build massive $4.6 Billion "GPU Supercluster" in Australia (Sovereign AI)
Vector db comparison
Is it possible to run two seperate llama-server.exe processes that share the same layers and weights stored in DRAM?
Speed of DeepSeek with RAM offload
https://livebench.ai - Open Weight Models Only
At What Point Does Owning GPUs Become Cheaper Than LLM APIs ? I
NVIDIA CEO on new JRE podcast: Robots,AI Scaling Laws and nuclear energy
Thoughts on decentralized training with Psyche?
Running LLM over RAM
Why so few benchmarks with the pcie p2p patches kernel module?
Are models creators choosing to not do QAT?
[Project] I built a Distributed LLM-driven Orchestrator Architecture to replace Search Indexing
The hidden cost of your AI chatbot