AI Infrastructure
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Serverless MCP Brings AI-Assisted Debugging to AWS Workflows Within Modern IDEs
Serverless computing has significantly streamlined how developers build and deploy applications on cloud platforms like AWS. However, debugging and managing complex architectures—comprising services such...
Allen Institute for AI (Ai2) Launches OLMoTrace: Real-Time Tracing of LLM...
Understanding the Limits of Language Model Transparency
As large language models (LLMs) become central to a growing number of applications—ranging from enterprise decision support to...
LLMs No Longer Require Powerful Servers: Researchers from MIT, KAUST, ISTA,...
HIGGS — the innovative method for compressing large language models was developed in collaboration with teams at Yandex Research, MIT, KAUST and ISTA.
HIGGS makes...
Google AI Introduces Ironwood: A Google TPU Purpose-Built for the Age...
At the 2025 Google Cloud Next event, Google introduced Ironwood, its latest generation of Tensor Processing Units (TPUs), designed specifically for large-scale AI inference...
This AI Paper Introduces a Machine Learning Framework to Estimate the...
Large Language Models (LLMs) have demonstrated significant advancements in reasoning capabilities across diverse domains, including mathematics and science. However, improving these reasoning abilities at...
This AI Paper from ByteDance Introduces MegaScale-Infer: A Disaggregated Expert Parallelism...
Large language models are built on transformer architectures and power applications like chat, code generation, and search, but their growing scale with billions of...
Scalable and Principled Reward Modeling for LLMs: Enhancing Generalist Reward Models...
Reinforcement Learning RL has become a widely used post-training method for LLMs, enhancing capabilities like human alignment, long-term reasoning, and adaptability. A major challenge,...
UB-Mesh: A Cost-Efficient, Scalable Network Architecture for Large-Scale LLM Training
As LLMs scale, their computational and bandwidth demands increase significantly, posing challenges for AI training infrastructure. Following scaling laws, LLMs improve comprehension, reasoning, and...
This AI Paper Unveils a Reverse-Engineered Simulator Model for Modern NVIDIA...
GPUs are widely recognized for their efficiency in handling high-performance computing workloads, such as those found in artificial intelligence and scientific simulations. These processors...
PilotANN: A Hybrid CPU-GPU System For Graph-based ANNS
Approximate Nearest Neighbor Search (ANNS) is a fundamental vector search technique that efficiently identifies similar items in high-dimensional vector spaces. Traditionally, ANNS has served...
NVIDIA AI Open Sources Dynamo: An Open-Source Inference Library for Accelerating...
The rapid advancement of artificial intelligence (AI) has led to the development of complex models capable of understanding and generating human-like text. Deploying these...